Illegal Street Racing and Associated (Hooning) Behaviours
Hooning behaviours i
Illegal street racing and associated (hooning) behaviours
Nerida L. Leal
BPsychSc(Hons), GradCert(Road Safety)
A thesis submitted as fulfilment for the Degree of Doctor of Philosophy
Centre for Accident Research & Road Safety – Queensland School of Psychology and Counselling Queensland University of Technology
2010 ii Hooning behaviours
Hooning behaviours iii
Keywords
Hooning; illegal street racing; vehicle impoundment programs; evaluation; deterrence theory; social learning theory; road safety; Australia.
iv Hooning behaviours
Hooning behaviours v
Abstract
In an Australian context, the term hooning refers to risky driving behaviours such as illegal street racing and speed trials, as well as behaviours that involve unnecessary noise and smoke, which include burn outs, donuts, fish tails, drifting and other skids. Hooning receives considerable negative media attention in Australia, and since the 1990s all Australian jurisdictions have implemented vehicle impoundment programs to deal with the problem. However, there is limited objective evidence of the road safety risk associated with hooning behaviours. Attempts to estimate the risk associated with hooning are limited by official data collection and storage practices, and the willingness of drivers to admit to their illegal behaviour in the event of a crash. International evidence suggests that illegal street racing is associated with only a small proportion of fatal crashes; however, hooning in an Australian context encompasses a broader group of driving behaviours than illegal street racing alone, and it is possible that the road safety risks will differ with these behaviours. There is evidence from North American jurisdictions that vehicle impoundment programs are effective for managing drink driving offenders, and drivers who continue to drive while disqualified or suspended both during and post- impoundment. However, these programs used impoundment periods of 30 – 180 days (depending on the number of previous offences). In Queensland the penalty for a first hooning offence is 48 hours, while the vehicle can be impounded for up to 3 months for a second offence, or permanently for a third or subsequent offence within three years. Thus, it remains unclear whether similar effects will be seen for hooning offenders in Australia, as no evaluations of vehicle impoundment programs for hooning have been published. To address these research needs, this program of research consisted of three complementary studies designed to: (1) investigate the road safety implications of hooning behaviours in terms of the risks associated with the specific behaviours, and the drivers who engage in these behaviours; and (2) assess the effectiveness of current approaches to dealing with the problem; in order to (3) inform policy and practice in the area of hooning behaviour. Study 1 involved qualitative (N = 22) and quantitative (N = 290) research with drivers who admitted engaging in hooning behaviours on Queensland roads. vi Hooning behaviours
Study 2 involved a systematic profile of a large sample of drivers (N = 834) detected and punished for a hooning offence in Queensland, and a comparison of their driving and crash histories with a randomly sampled group of Queensland drivers with the same gender and age distribution. Study 3 examined the post-impoundment driving behaviour of hooning offenders (N = 610) to examine the effects of vehicle impoundment on driving behaviour. The theoretical framework used to guide the research incorporated expanded deterrence theory, social learning theory, and driver thrill-seeking perspectives. This framework was used to explore factors contributing to hooning behaviours, and interpret the results of the aspects of the research designed to explore the effectiveness of vehicle impoundment as a countermeasure for hooning. Variables from each of the perspectives were related to hooning measures, highlighting the complexity of the behaviour. This research found that the road safety risk of hooning behaviours appears low, as only a small proportion of the hooning offences in Study 2 resulted in a crash. However, Study 1 found that hooning-related crashes are less likely to be reported than general crashes, particularly when they do not involve an injury, and that higher frequencies of hooning behaviours are associated with hooning-related crash involvement. Further, approximately one fifth of drivers in Study 1 reported being involved in a hooning-related crash in the previous three years, which is comparable to general crash involvement among the general population of drivers in Queensland. Given that hooning-related crashes represented only a sub-set of crash involvement for this sample, this suggests that there are risks associated with hooning behaviour that are not apparent in official data sources. Further, the main evidence of risk associated with the behaviour appears to relate to the hooning driver, as Study 2 found that these drivers are likely to engage in other risky driving behaviours (particularly speeding and driving vehicles with defects or illegal modifications), and have significantly more traffic infringements, licence sanctions and crashes than drivers of a similar (i.e., young) age. Self-report data from the Study 1 samples indicated that Queensland’s vehicle impoundment and forfeiture laws are perceived as severe, and that many drivers have reduced their hooning behaviour to avoid detection. However, it appears that it is more common for drivers to have simply changed the location of their hooning behaviour to avoid detection. When the post-impoundment driving behaviour of the Hooning behaviours vii sample of hooning offenders was compared to their pre-impoundment behaviour to examine the effectiveness of vehicle impoundment in Study 3, it was found that there was a small but significant reduction in hooning offences, and also for other traffic infringements generally. As Study 3 was observational, it was not possible to control for extraneous variables, and is, therefore, possible that some of this reduction was due to other factors, such as a reduction in driving exposure, the effects of changes to Queensland’s Graduated Driver Licensing scheme that were implemented during the study period and affected many drivers in the offender sample due to their age, or the extension of vehicle impoundment to other types of offences in Queensland during the post-impoundment period. However, there was a protective effect observed, in that hooning offenders did not show the increase in traffic infringements in the post period that occurred within the comparison sample. This suggests that there may be some effect of vehicle impoundment on the driving behaviour of hooning offenders, and that this effect is not limited to their hooning driving behaviour. To be more confident in these results, it is necessary to measure driving exposure during the post periods to control for issues such as offenders being denied access to vehicles. While it was not the primary aim of this program of research to compare the utility of different theoretical perspectives, the findings of the research have a number of theoretical implications. For example, it was found that only some of the deterrence variables were related to hooning behaviours, and sometimes in the opposite direction to predictions. Further, social learning theory variables had stronger associations with hooning. These results suggest that a purely legal approach to understanding hooning behaviours, and designing and implementing countermeasures designed to reduce these behaviours, are unlikely to be successful. This research also had implications for policy and practice, and a number of recommendations were made throughout the thesis to improve the quality of relevant data collection practices. Some of these changes have already occurred since the expansion of the application of vehicle impoundment programs to other offences in Queensland. It was also recommended that the operational and resource costs of these laws should be compared to the road safety benefits in ongoing evaluations of effectiveness to ensure that finite traffic policing resources are allocated in a way that produces maximum road safety benefits. However, as the evidence of risk associated with the hooning driver is more compelling than that associated with hooning behaviour, it was argued that the hooning driver may represent the better target for viii Hooning behaviours
intervention. Suggestions for future research include ongoing evaluations of the effectiveness of vehicle impoundment programs for hooning and other high-risk driving behaviours, and the exploration of additional potential targets for intervention to reduce hooning behaviour. As the body of knowledge regarding the factors contributing to hooning increases, along with the identification of potential barriers to the effectiveness of current countermeasures, recommendations for changes in policy and practice for hooning behaviours can be made.
Hooning behaviours ix
Table of Contents
CHAPTER 1: INTRODUCTION ...... 1 1.1 Introduction ...... 1 1.2 Definition of hooning behaviours ...... 2 1.3 Current approaches to dealing with the problem ...... 4 1.4 Rationale for the research ...... 5 1.5 Theoretical framework for the research ...... 7 1.6 Research aims ...... 8 1.7 Demarcation of scope ...... 9 1.8 Outline of thesis ...... 10 1.9 Chapter summary ...... 12
CHAPTER 2: ILLEGAL STREET RACING AND ASSOCIATED “HOONING” BEHAVIOURS ...... 13 2.1 Introduction ...... 13 2.1.1 Literature search parameters ...... 13 2.2 Who engages in illegal street racing and associated hooning behaviours? . 14 2.3 Factors contributing to hooning behaviour ...... 15 2.3.1 Person-related factors: young driver issues ...... 16 2.3.2 Socio-cultural factors ...... 20 2.3.3 Environmental factors ...... 23 2.4 What are the road safety implications of illegal street racing and associated hooning behaviours? ...... 24 2.4.1 The riskiness of hooning behaviour ...... 25 2.4.2 The involvement of hooning in crashes ...... 25 2.4.3 The general riskiness of involved drivers ...... 28 2.5 Current approaches to dealing with hooning ...... 29 2.5.1 The use of vehicle impoundment in Queensland ...... 31 2.5.2 Purpose of vehicle sanctions ...... 32 2.5.3 Effectiveness of vehicle impoundment programs ...... 35 2.5.4 Effectiveness of vehicle forfeiture programs ...... 41 2.5.5 Summary ...... 42 2.6 Evaluation issues ...... 42 2.6.1 Young drivers and Graduated Driver Licensing systems ...... 43 2.6.2 Data available for use in evaluations ...... 46 2.6.3 Evaluation design issues ...... 48 2.7 Relevant theoretical perspectives ...... 49 2.7.1 Deterrence models ...... 50 2.7.2 Social learning theory ...... 54 2.7.3 Application of theoretical frameworks to hooning behaviour ...... 58 2.8 Chapter summary ...... 59 2.8.1 Research aims and key research questions ...... 60 x Hooning behaviours
CHAPTER 3: STUDY 1A – FACTORS CONTRIBUTING TO ILLEGAL STREET RACING AND ASSOCIATED “HOONING” BEHAVIOURS (QUALITATIVE PHASE) ...... 63 3.1 Introduction ...... 63 3.1.1 Study aims ...... 64 3.2 Method ...... 64 3.2.1 Sampling population ...... 64 3.2.2 Recruitment method ...... 65 3.2.3 Participants ...... 67 3.2.4 Design and measures ...... 67 3.2.5 Procedure ...... 69 3.3 Results ...... 71 3.3.1 Sample characteristics ...... 71 3.3.2 Involved drivers ...... 73 3.3.3 Expanded deterrence theory ...... 74 3.3.4 Social learning theory ...... 80 3.3.5 Influence of others ...... 85 3.3.6 Thrill-seeking ...... 87 3.3.7 Queensland’s vehicle impoundment laws for hooning offences ...... 88 3.3.8 Other issues ...... 91 3.4 Discussion ...... 92 3.4.1 Status of research questions ...... 93 3.4.2 Implications for Study 1b ...... 95 3.4.3 Implications for Studies 2 and 3 ...... 99 3.4.4 Strengths and limitations ...... 99 3.5 Chapter summary ...... 100
CHAPTER 4: STUDY 1B – FACTORS CONTRIBUTING TO ILLEGAL STREET RACING AND ASSOCIATED “HOONING” BEHAVIOURS (QUANTITATIVE PHASE) ...... 103 4.1 Introduction ...... 103 4.1.1 Hypotheses ...... 103 4.2 Method ...... 106 4.2.1 Sampling population ...... 106 4.2.2 Recruitment method ...... 106 4.2.3 Participants ...... 108 4.2.4 Design and measures ...... 108 4.2.5 Procedure ...... 115 4.2.6 Statistical analyses ...... 116 4.3 Results ...... 117 4.3.1 Data cleaning ...... 117 4.3.2 Main dependent variables ...... 119 4.3.3 Demographic characteristics ...... 124 4.3.4 Driving history and vehicle type ...... 127 Hooning behaviours xi
4.3.5 Hypothesis testing...... 130 4.4 Discussion ...... 151 4.4.1 Status of hypotheses ...... 151 4.4.2 Implications for policy and practice ...... 157 4.4.3 Strengths and limitations ...... 160 4.5 Chapter summary ...... 162
CHAPTER 5: STUDY 2A – THE CHARACTERISTICS OF HOONING OFFENDERS AND OFFENCES ...... 163 5.1 Introduction ...... 163 5.1.1 Hypotheses ...... 163 5.2 Method ...... 164 5.2.1 Selection of sample ...... 164 5.2.2 Data sources ...... 165 5.2.3 Procedure ...... 166 5.3 Results ...... 168 5.3.1 Demographic characteristics of hooning offenders ...... 168 5.3.2 Characteristics of hooning offences ...... 170 5.3.3 Application of vehicle impoundment periods for hooning offences ...... 173 5.3.4 Characteristics of the vehicles used in hooning offences ...... 174 5.4 Discussion ...... 177 5.4.1 Status of research questions and hypotheses ...... 177 5.4.2 Implications for policy and practice ...... 180 5.4.3 Strengths and limitations ...... 181 5.5 Chapter summary ...... 182
CHAPTER 6: STUDY 2B – THE ROAD SAFETY RISK OF DRIVERS WITH A HOONING OFFENCE ...... 185 6.1 Introduction ...... 185 6.1.1 Hypotheses ...... 187 6.2 Method ...... 188 6.2.1 Samples ...... 188 6.2.2 Design ...... 189 6.2.3 Data sources ...... 189 6.2.4 Procedure ...... 190 6.3 Results ...... 192 6.3.1 Demographic characteristics of drivers ...... 192 6.3.2 Hypothesis testing...... 193 6.4 Discussion ...... 199 6.4.1 Status of research questions and hypotheses ...... 200 6.4.2 Implications for policy and practice ...... 203 6.4.3 Strengths and limitations ...... 204 6.5 Chapter summary ...... 206 xii Hooning behaviours
CHAPTER 7: STUDY 3 – THE POST-IMPOUNDMENT DRIVING BEHAVIOUR OF HOONING OFFENDERS ...... 209 7.1 Introduction ...... 209 7.1.1 Research questions and hypotheses ...... 209 7.2 Method ...... 211 7.2.1 Samples ...... 211 7.2.2 Design ...... 212 7.2.3 Data sources ...... 213 7.2.4 Procedure ...... 213 7.3 Results ...... 215 7.3.1 Demographic characteristics of drivers ...... 215 7.3.2 Post-impoundment driving behaviour of hooning offenders ...... 215 7.3.3 Hypothesis testing ...... 216 7.4 Discussion ...... 219 7.4.1 Status of hypotheses ...... 219 7.4.2 Implications for policy and practice ...... 221 7.4.3 Study strengths and limitations ...... 221 7.5 Chapter summary ...... 223
CHAPTER 8: DISCUSSION ...... 225 8.1 Introduction ...... 225 8.2 Review of findings ...... 227 8.2.1 RQ1: Who engages in hooning in an Australian context? ...... 227 8.2.2 RQ2: What are the legal, social and psychological factors that contribute to hooning behaviours? ...... 227 8.2.3 RQ3: What are the road safety implications of hooning behaviours? ...... 228 8.2.4 RQ4: Do drivers who engage in hooning also engage in other risky driving behaviours? ...... 230 8.2.5 RQ5: How effective are vehicle impoundment and forfeiture programs at reducing hooning behaviour? ...... 231 8.3 Contribution to theory ...... 233 8.4 Implications for road safety ...... 234 8.4.1 RA1: The road safety implications of hooning behaviours ...... 234 8.4.2 RA2: The effectiveness of current approaches to dealing with the problem ...... 236 8.4.3 RA3: Implications for hooning-related policy and practice ...... 237 8.5 Strengths and limitations of the research ...... 239 8.6 Suggestions for future research ...... 241 8.7 Conclusion ...... 244
REFERENCES ...... 247
APPENDICES ...... 255 Hooning behaviours xiii
List of Figures
Fig. 2.1. Classical deterrence model of hooning behaviour ...... 51 Fig. 2.2. Expanded deterrence model of hooning behaviour ...... 53 Fig. 2.3. Social learning model of hooning behaviour ...... 56 Fig. 4.1. Frequency histogram for raw data for frequency of noise and smoke- related hooning behaviours such as burn outs in the previous month (N = 290) ...... 120 Fig. 4.2. Frequency histogram for square root transformed data for frequency of noise and smoke-related hooning behaviours in the previous month (N = 290) ...... 120 Fig. 4.3. Frequency histogram for raw data for frequency of illegal street racing / speed trials in the previous month (N = 290) ...... 121 Fig. 4.4. Frequency histogram for square root transformed data for frequency of illegal street racing / speed trials in the previous month (N = 290) ... 121 Fig. 4.5. Participant responses to Q70a and 71a “How often have you been able to avoid getting caught by doing it less often?” ...... 133 Fig. 7.1. Mean number of hooning infringements in ‘pre’ and ‘post’ periods as a function of group ...... 217 Fig. 7.2. Mean number of (square root transformed) traffic infringements in ‘pre’ and ‘post’ periods as a function of group ...... 219
xiv Hooning behaviours
Hooning behaviours xv
List of Tables
Table 1.1 “Hooning” driving behaviours associated with illegal street racing ...... 3 Table 2.1 Illegal driving behaviours and vehicle impoundment periods applied under anti-hooning legislation, by Australian state or territory ...... 30 Table 3.1 Focus group variables of interest and initial questions ...... 68 Table 3.2 Participants’ level of education, employment status and usual occupation (N = 22) ...... 71 Table 3.3 Self-reported offence by type for focus group participants (N = 22) ...... 72 Table 4.1 Intentions regarding future (next month) hooning behaviour (N = 290) ...... 122 Table 4.2 Bivariate correlations (Pearson’s correlation coefficient) between dependent measures of hooning behaviour (N = 290) ...... 123 Table 4.3 Number of participants involved in crashes as a driver and passenger by crash type (N = 277) ...... 123 Table 4.4 Participants’ education, employment status and usual occupation (N = 290) ...... 125 Table 4.5 Associations between demographic characteristics and driving history variables and frequency and intentions regarding hooning behaviours ...... 126 Table 4.6 Participants with at least one previous offence by type (N = 271) ..... 127 Table 4.7 Associations between driving history variables and frequency and intentions regarding hooning behaviours (N = 277) ...... 128 Table 4.8 Descriptive statistics for direct and indirect experience with punishment (N = 271) ...... 131 Table 4.9 Use of different punishment avoidance strategies (N = 243) ...... 132 Table 4.10 Friends’ use of different punishment avoidance strategies (N = 243) ...... 132 Table 4.11 Descriptive statistics for perceptions of likelihood of detection for self and “people” generally ...... 134 Table 4.12 Descriptive statistics for perception of certainty and swiftness of punishment for self and others ...... 135 Table 4.13 Descriptive statistics for perceptions of the severity of vehicle impoundment periods for self and others ...... 137 xvi Hooning behaviours
Table 4.14 Perceptions of severity items as a function of penalty period (N = 253) ...... 138 Table 4.15 Bivariate correlations (Pearson’s correlation coefficient) between expanded deterrence theory variables and frequency and intentions regarding hooning behaviours ...... 139 Table 4.16 Descriptive statistics for perceptions relating to the crushing of cars compared to vehicle forfeiture (N = 253) ...... 141 Table 4.17 Descriptive statistics for additional social learning theory variables ...... 143 Table 4.18 Bivariate correlations (Pearson’s correlation coefficient) between additional social learning theory variables and frequency and intentions regarding hooning behaviours ...... 144 Table 4.19 Bivariate correlations (Pearson’s correlation coefficient) between driver thrill-seeking scores and frequency and intentions regarding hooning behaviours (N = 243) ...... 145 Table 4.20 Hierarchical regression analyses for noise and smoke-related hooning behaviours (N = 228) ...... 147 Table 4.21 Hierarchical regression analyses for illegal street racing (N = 228) ... 150 Table 5.1 Demographic characteristics of hooning offenders ...... 168 Table 5.2 Occupation of hooning offenders in Australian Standard Classification of Occupation Major Codes ...... 169 Table 5.3 Characteristics of hooning offences (N = 848) ...... 170 Table 5.4 Characteristics of crashes that occurred with hooning offences (N = 31) ...... 171 Table 5.5 Severity, casualties and circumstances / contributing factors of crashes that occurred with hooning offences (N = 16)...... 173 Table 5.6 Vehicle impoundment period for hooning offences (N = 848) as described in the modus operandi field of the CRISP database ...... 174 Table 5.7 Characteristics of vehicles used in hooning offences (N = 848) ...... 175 Table 6.1 Offence groups and sub-groups created for Study 2b ...... 191 Table 6.2 Comparison of prior traffic infringements of hooning offenders and a random sample of drivers of comparable age (n’s = 802) ...... 194 Table 6.3 Comparison of the traffic infringements of the hooning offender (N = 3645) and comparison (N = 1005) samples ...... 195 Table 6.4 Comparison of prior licence sanctions of hooning offenders and a random sample of drivers of comparable age (n’s = 802) ...... 197
Hooning behaviours xvii
Table 6.5 Prior crashes recorded in Queensland’s Road Crash Information System of hooning offenders and a random sample of drivers of comparable age (n’s = 802) ...... 198 Table 7.1 Pre- and post-impoundment driving behaviour of hooning offenders (N = 610) ...... 215 Table 8.1 Key research questions of program of research by study and thesis chapter ...... 226 Table C4.1 Correlation matrix for hierarchical regression analyses for noise and smoke-related hooning behaviours (N = 228) ...... 307 Table C4.2 Correlation matrix for hierarchical regression analyses for illegal street racing (N = 228) ...... 308
xviii Hooning behaviours
Hooning behaviours xix
Statement of original authorship
The work contained in this thesis has not been previously submitted to meet requirements for an award at this or any other higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made.
Signature: ______
Date: 25th October, 2010 xx Hooning behaviours
Hooning behaviours xxi
Acknowledgements
My sincere thanks go to my Principal Supervisor, Professor Barry Watson, for his support and guidance over the last four years, and his always useful suggestions for “cosmetic changes”. It has been a long haul, but I am glad that my (not always) empty threats to give up on the PhD and manage Pete’s music career, or become a cake decorator, were laughed off. Love your work, Baz I also appreciate the input of my Associate Supervisors, Dr Kerry Armstrong and Dr Mark King, and Final Seminar panel members Associate Professor Katy White, Dr Cassandra Cross and Adjunct Professor Vic Siskind, for their advice on the thesis. The feedback from reviewers of publications from this program of research has also improved this document, and I am grateful for those insights along the way. I also appreciate the comments and suggestions from the thesis examiners. Finally, Judy, Ioni, Kerry and Ange agreed to proof-read the thesis on very short notice, and I thank them all for their friendship and attention to detail. This research was financially supported by the Queensland Government’s Growing the Smart State PhD Funding Program and may be used to assist public policy development. However, the opinions and information contained in the research do not necessarily represent the opinions of the Queensland Government or carry any endorsement by the Queensland Government. The Queensland Government accepts no responsibility for decisions or actions resulting from any opinions or information supplied. As part of this grant program, this project received considerable in-kind support from the Queensland Police Service and Queensland Department of Transport and Main Roads, and I would particularly like to acknowledge Lisa-Marie O’Donnell, Kelly Sultana, Beth Stapleton, Pam Palmer and Nicky Woodman for their untiring efforts in ensuring I was able to access the datasets required for this research. I am also grateful for financial support received in the form of an Australian Postgraduate Award, Institute of Biomedical Health and Innovation (IHBI) top-up scholarship, Grant-in-Aid conference travel funds and project funding from IHBI, the Centre for Accident Research and Road Safety – Queensland (CARRS-Q), and Motor Accident Insurance Commission. I am indebted to the people who came along to my focus groups, and the people who completed my questionnaire, who volunteered a considerable amount of their time to participate in my research, and trusted me with their stories. Without xxii Hooning behaviours
their willingness to share sensitive information about their illegal and other driving activities, a considerable proportion of this program of research would not have been possible. Thanks are also due to my fellow students Dale, Pete, Ange, Kerrie, Ross, Bek and Buddy for their assistance with data collection and data entry in these studies. There is a strong student culture at CARRS-Q, and I am grateful that there were always plenty of friends to help out when I needed it. The work-related and social gatherings have also been a welcome component of the PhD process at CARRS-Q – if only karaoke with Pete and Sparkles was considered a PhD milestone, I may have completed on time… Finally and most importantly, I thank my family for encouraging me and supporting me as I worked to complete this goal – thanks Mum, Dad, Pookie and Airlie – it won’t be long now until I am Dr Snoofs! My husband Stevie is the best, and has looked after our little ladies while I have worked odd hours to complete the thesis with only minimal complaints. They may not know what Mummy’s “big book, but without many pictures” is about, but Emma and Alyssa are the reasons I started this process, and the reasons I’m so proud to (finally!) finish. Hooning behaviours 1
CHAPTER 1: INTRODUCTION
1.1 Introduction
Illegal street racing has received significant negative media attention internationally in recent years, reflecting general public concern about the behaviour. For example, the majority of respondents to Canadian Road Safety Monitor research, an annual public opinion poll, reported being concerned or extremely concerned about street racing, and considered it to be a serious problem (Beirness, Mayhew, Simpson, & Desmond, 2004; Singhal, Simpson, Vanlaar, & Mayhew, 2006). A recent review of the international illegal street racing literature concluded that evidence from social surveys and fatal crash data suggests that the prevalence of street racing has increased over the last decade (Vingilis & Smart, 2009). However, these behaviours are not new. It is possible that the increased attention given to these behaviours by the police through strengthened legislation (and associated recording practices) is contributing to the apparent increase in the behaviour. Further, these behaviours may have been facilitated by advances in telecommunications; for instance, involved persons can record their behaviour using mobile phones or other picture or video recording devices and post videos and photographs on public websites, which may influence public perceptions of prevalence, given greater visibility of the behaviour. The influence of these factors should be borne in mind when interpreting changes in prevalence. Illegal street racing and associated risky and nuisance driving behaviours are collectively known as “hooning” in Australia. These associated behaviours include activities such as “burn outs”, “donuts”, “drifting”, and unnecessary speed or acceleration. While some of these behaviours are potentially risky (i.e., they increase the likelihood of the driver being involved in a crash), others are more of a disruptive nuisance to the general community. While illegal street racing is a term commonly used across jurisdictions in Australia, in the United States and Canada, terms for the associated behaviours can differ, and are described in more detail section 1.2. 2 Hooning behaviours
1.2 Definition of hooning behaviours
There is no clear definition of hooning in the international road safety literature. This absence of a clear definition may be because terms such as “hoon” and “hooning” are Australian colloquialisms, and prior to the implementation of “anti-hooning” legislation, the behaviour was typically dealt with as a public amenity issue (i.e., disturbing the peace). These terms are commonly used by the media and general public in Australia, but may be used to describe different driving behaviours, or young people generally. The label of “hoon” is sometimes applied to car enthusiasts, drivers of modified vehicles, or to young drivers in general. The Centre for Accident Research and Road Safety – Queensland (CARRS-Q) conducted a qualitative exploratory study to examine the experiences and perceptions of local car enthusiasts who are typically associated with street racing, hooning or cruising activities (Armstrong & Steinhardt, 2006). Findings from this research highlighted that that those involved in the car enthusiast scene are not a homogeneous group, as there are a number of sub- groups, of which only some were regarded as “truly” dangerous. They argued that young car enthusiasts who drive the most noticeable or “showy” vehicles are often misclassified as hoons by police and the general public due to the type of vehicle they drive, when the reality is that drivers who engage in hooning behaviours can be anyone, driving any vehicle (Armstrong & Steinhardt, 2006). Some research uses the term hooning to incorporate not only the illegal behaviours included in hooning legislation, but other car-centred activities that are not illegal, such as cruising (e.g., Gee Kee, 2006), which was defined as slowly driving a vehicle along a predetermined route (Gee Kee, 2006), usually with other vehicles. Given the widespread use of the terms “hoon” and “hooning”, and the potential for misclassification of involved drivers, it is important that the behaviours under investigation are clearly defined. In lieu of a commonly accepted definition in the road safety literature, an alternative method of defining hooning behaviours is to adopt a legislative definition. Thus, the definition of hooning behaviours adopted for the purposes of this program of research is consistent with the prescribed offences under Queensland’s “anti-hooning” legislation (Police Powers and Responsibilities Act and Another Act Amendment Act 2002): dangerous operation of a motor vehicle; careless driving of a motor vehicle; racing and speed trials on roads; and wilfully Hooning behaviours 3
starting a vehicle, or driving a vehicle, in a way that makes unnecessary noise or smoke. Unless otherwise stated, the term “hooning” in this thesis will refer to this group of behaviours, defined in Table 1.1. This group of driving behaviours is consistent with behaviours grouped together as hooning in other Australian jurisdictions, discussed in more detail in section 2.5.
Table 1.1 “Hooning” driving behaviours associated with illegal street racing Behaviour Definitiona Speed trials When the acceleration and top-speed capability of a vehicle, or driver skill, are tested, usually on a straight stretch of road of a set distance. Speed trials also include attempts to establish or break records.
Burn out When the rear tyres of a rear-wheel drive vehicle are spun at high revolutions per minute until they heat and smoke. More smoke is generated if the road surface has oil or petrol spills.
Donut When the driver of a rear-wheel drive vehicle has turned the front tyres until the steering is fully locked during a burn out, so that the rear wheels cause the car to rotate and a circular (donut) pattern of tread marks from the rear wheels remains on the road surface.
Drifting When a rear-wheel drive vehicle slides sideways through a turn taken at high speed.
Rolling road blocks The practice of a large number of vehicles travelling as a convoy (or road blockades) across all lanes of a roadway, slowing or blocking other vehicles’ progress until a “race-track” is created. a Definitions adapted from: Armstrong & Steinhardt (2006); Gee Kee (2006); Police Powers and Responsibilities Act 2002.
It is acknowledged that illegal street racing can be either highly organised or spontaneous in nature (Knight, Cook, & Olson, 2004; Peak & Glensor, 2004; Warn, Tranter, & Kingham, 2004). Highly organised races are typically staged at night in industrial areas (Warn et al., 2004), although they may even be held in the middle of a highway. In Sydney, Australia, for example, it has been reported that street racers meet at a central location, and when enough people have gathered, it is decided who will race and where the race will take place (Leigh, 1996). These events can be well- organised, with start and finish lines marked a quarter mile apart (the traditional distance for drag races) (Leigh, 1996). Some groups use walkie-talkies and even police tape and false signs to block the traffic for the duration of a race (Vaaranen & Wieloch, 2002), while others use rolling road blocks. In Canada, illegal street racing 4 Hooning behaviours
can also include an activity known as a “hat race”, where participants put money into a hat and the money is taken to an undisclosed location. The person with the hat calls the participants to inform them where the money is being held, and the first driver to get there wins all of the money (Peak & Glensor, 2004). Unorganised or spontaneous illegal street racing can be defined as impromptu, one-off races between drivers who do not know one another (Peak & Glensor, 2004). For example, drivers stopped at traffic signals on a straight stretch of a double-lane road may race, with the traffic lights providing a starting signal (Warn et al., 2004).
1.3 Current approaches to dealing with the problem
Traffic law is enforced at a provincial level in Australia by state and territory police services. In the past, police typically dealt with hooning behaviours by attending meeting places and issuing vehicle defect notices or tickets for other public nuisance or traffic offences (Leigh, 1996). The purpose of this practice was to discourage illegal street racers from meeting in public places, and to move them along to private spaces or legal meets (Leigh, 1996). However, there has been a shift away from public amenity approaches towards dedicated road safety approaches in recent years. This shift has occurred in the absence of the evidence of the road safety risk of illegal street racing and associated hooning behaviours, which can be attributed to a number of factors. First, illegal street racing and associated hooning behaviours are difficult to identify in official datasets, as these behaviours were not grouped together prior to the implementation of this legislation in Queensland. Further, not all of the prescribed hooning offences have unique codes in police datasets. Finally, illegal street racing and hooning are not specified as factors that may have contributed to crashes on current reporting forms. In Queensland, traffic laws to address hooning behaviours were implemented in response to community complaints about the group of behaviours and the potential for harm (Folkman, 2005; Jarred, 2002). Since the 1990s, all Australian states and territories, as well as New Zealand, have implemented laws targeting hooning behaviours, commonly referred to as “anti- hooning” legislation. Among other sanctions imposed (including fines, demerit points, and licence disqualification), vehicles of drivers charged under anti-hooning Hooning behaviours 5
legislation may be impounded immediately by police. The length of the impoundment period increases with repeat offences within prescribed periods. In cases where there is insufficient evidence to substantiate a hooning offence, many police revert to the previous approach of enforcing vehicle standards and issuing vehicle defect notices or tickets for other traffic offences (Crang, 2006). Hooning represented the first group of driving behaviours to attract vehicle impoundment as a penalty in Australia, with a number of states later introducing similar legislation for drivers charged with repeat drink driving offences, as well as unlicensed driving and driving while disqualified offences. Vehicle impoundment laws were first applied to drink driving offences in New Zealand, shortly followed by illegal street racing and associated offences. Internationally, vehicle impoundment programs in the United States and Canada have typically been applied to drink driving and driving while suspended or disqualified, although some jurisdictions have recently applied similar laws to illegal street racing (e.g., Ontario; Ontario Ministry of Transportation, 2007). To date, no evaluations of vehicle impoundment programs in Australian jurisdictions have been published, although some are in progress. The published literature regarding the effectiveness of vehicle impoundment and forfeiture programs is from North American jurisdictions, where as noted above, the programs are generally designed to target repeat drink drivers and drivers who continue to drive while suspended or disqualified. As hooning behaviours are being treated as a road safety problem in need of a road safety solution in Australian jurisdictions, there is a need to better understand the road safety risks associated with this group of behaviours, and the effectiveness of current approaches to dealing with the problem. This thesis documents a program of research designed to address these research needs.
1.4 Rationale for the research
While searching the published international literature yields articles documenting general risky driving and illegal street racing, there are few published studies that have focussed on the broader group of hooning behaviours, and none from outside Australia. Further, literature searches for studies designed to assess the effectiveness of vehicle impoundment programs yields studies regarding programs 6 Hooning behaviours
addressing other road safety problems from North American jurisdictions. Thus, there are a number of research opportunities to explore in an Australian context that can contribute to the international road safety literature regarding illegal street racing and associated hooning behaviours, and the use of vehicle impoundment and forfeiture programs as a road safety countermeasure. First, there is a need to justify the use of traffic policing resources with objective evidence of the road safety implications of hooning behaviours. While section 2.4 describes the available international research on this issue, it is limited to the involvement of illegal street racing in fatal crashes in the United States (e.g., Knight et al., 2004) and, therefore, may not reflect the involvement of the broader group of hooning behaviours, nor all types of crashes, within an Australian context. Further, it is important to note that there are differences between the types of illegal driving behaviours grouped together under the common heading of “hooning” in terms of their likely road safety implications. Second, vehicle impoundment is one of the most severe traffic sanctions in use in Australia as it involves the removal of a significant asset for increasing periods of time up to vehicle forfeiture, depending on whether the driver has been convicted of any other hooning offences within prescribed periods. Removal of vehicles affects not only the offender, but also their families or others who rely on the vehicle. If the offender does not own the vehicle (i.e., it is under some sort of finance, such as a lease or loan agreement), losing the vehicle permanently for a third hooning offence within the prescribed period may represent an ongoing financial problem, as the offender (and their family) would still be required to honour the loan, but would no longer have ownership and use of the vehicle. Vehicle impoundment programs may also result in costs to the state, in terms of police operational time, vehicle towing by third parties, and vehicle storage. While the legislation states that offenders must cover the costs of towing and storage before reclaiming the vehicle, prior to legislative amendment in 20071, this did not always occur in practice, and the state government then had to pursue the debt (Crang, 2006). Additionally, some offenders will opt not to reclaim the vehicle at the end of the impoundment period, particularly if the vehicle is worth less than the towing and
1 Prior to July 2007, Queensland Police Service was liable for towing and storage costs, and would attempt to recoup these from the offender. However, the legislation was amended so that the towing or storage company seeks payment directly from the offender. Hooning behaviours 7
storage costs. Accordingly, there is a need to evaluate the use of vehicle impoundment as a sanction for hooning behaviours to ensure that it is having the desired deterrent effect on driver behaviour and, thus, to provide support to justify its continued use. Further, while it was not possible to determine the extent of the cost to the community for vehicle impoundment laws for hooning in this research, these legislative changes and extension of the vehicle impoundment program in Queensland to other offence types was associated with improvements in data collection practices that may make such estimates possible in the future. These research needs are not mutually exclusive. For example, a better understanding of the road safety implications of hooning behaviours can be used to inform the development of public and offender education materials that can be used in conjunction with vehicle impoundment programs to change driver behaviour, and justify the use of such a severe penalty. Consequently, there is a need to conduct research addressing these gaps in knowledge regarding hooning behaviours and the use of vehicle impoundment programs to deal with this problem in Australia. Such research can improve understanding of the group of behaviours, and also inform road safety policy and practice. There are a number of ways of exploring these issues. First, researchers can consider whether hooning represents a road safety issue and, therefore, warrants the allocation of traffic policing resources rather than general policing, or no policing resources at all. Second, researchers can explore whether the use of traffic sanctions, such as vehicle impoundment and forfeiture programs, represent a cost-effective method of reducing hooning behaviour.
1.5 Theoretical framework for the research
Although it was not the purpose of this thesis to test or compare the utility of particular theories in explaining or predicting hooning behaviour, there are a number of benefits of theoretically driven approaches. Specifically, such approaches can aid the understanding of the underlying factors contributing to behaviour, and facilitate the design and evaluation of countermeasures (Grayson, 1997; Huguenin, 1997). This thesis adopted a multi-disciplinary approach to the exploration of hooning behaviours, drawing on criminological and psychosocial theories. The theoretical perspectives adopted were expanded deterrence theory (Stafford & Warr, 1993) and 8 Hooning behaviours
social learning theory (Akers, 1990). These theories were selected to facilitate the understanding of the legal and non-legal factors associated with the behaviours, and to guide the evaluation of the effectiveness of Queensland’s vehicle impoundment laws. As traffic law enforcement is underpinned by deterrence principles, where undesirable sanctions are used as punishments to deter drivers from breaching road rules, Stafford and Warr’s (1993) expanded deterrence model was utilised. Similar to classical deterrence models, this model focuses on the individual’s perceptions of the certainty, severity and swiftness of legal punishment for offending behaviour. However, it differs from other deterrence perspectives in terms of how general and specific deterrent effects are defined, as well as the inclusion of vicarious as well as direct personal experiences with punishment and punishment avoidance. While Stafford and Warr’s (1993) expanded model of deterrence appears to be an improvement upon classical models, deterrence models generally have been criticised for focusing only on legal factors, to the detriment of non-legal factors that also influence driving behaviour (e.g., Vingilis, 1990). Akers (1990) has argued that social learning theory incorporates deterrence principles, while also incorporating sociological and psychological factors. His theory posits that behaviour is developed and maintained by an individual observing models of the behaviour (imitation), associating with significant others that the person perceives approves (or does not disapprove) of the behaviour (differential association), perceiving more positive than negative consequences to occur (differential reinforcement), and holding positive attitudes and beliefs towards the behaviour (definitions) (Akers, 1990). There are also additional models relating to the individual that may contribute to the understanding of illegal street racing and associated hooning behaviours that are not incorporated in either of these models. These factors and the main theoretical framework, which incorporated two theoretical perspectives, for this thesis are discussed in more detail in section 2.7.
1.6 Research aims
Based on the limited body of empirical literature regarding illegal street racing and associated hooning behaviours described above (and in more detail in Chapter 2), the main aims of this program of research were: Hooning behaviours 9
RA1. To investigate the road safety implications of illegal street racing and associated (hooning) behaviours, in terms of the risks associated with the specific behaviours, and the drivers who engage in these behaviours; RA2. To assess the effectiveness of current approaches to dealing with the problem; and RA3. To inform policy and practice in the area of illegal street racing and associated (hooning) behaviours.
Three complementary studies involving multi-disciplinary (criminological, psychological and sociological) and multi-method (qualitative and quantitative) approaches were designed to address particular issues related to these research aims. The specific research questions examined by the research are outlined in section 2.8.1, following a review of the relevant literature.
1.7 Demarcation of scope
As this thesis was interested in hooning behaviours, and the effectiveness of legislative approaches, two populations of interest were identified for this research: the population of drivers who engage in these behaviours but have not necessarily been detected (see Studies 1a and 1b); and the population of drivers who have been detected and punished by police for engaging in these behaviours (see Studies 2a, 2b and 3). A third population that was beyond the scope of this study was drivers who would potentially engage in hooning behaviours but have been deterred from doing so. This population was not sampled in this research for a number of reasons. First, previous hooning research has sampled from the general population of drivers and then divided the sample into groups of drivers who do or do not engage in hooning behaviour, resulting in small sample sizes for the hooning samples and, therefore, low statistical power for analyses. As this research was primarily interested in the population of drivers who engage in these behaviours, it was important to target this population specifically via appropriate recruitment strategies to obtain an adequate sample size. Second, obtaining a sample of drivers who would potentially engage in the behaviours would be difficult in terms of articulating the selection criteria effectively and devising recruitment strategies. This thesis was concerned with the on-road behaviour of drivers who engage 10 Hooning behaviours
in hooning behaviours (both those who are caught and punished and those who are not). In this regard, only information regarding traffic offence and crash histories (self-reported and obtained from official data sources) were analysed in this research, rather than other (i.e., criminal) behaviour. Finally, although there were changes to the use of vehicle impoundment programs in Queensland during this program of research, such that it was expanded to be used as a penalty for other high-risk driving offences, this thesis is only concerned with the use of vehicle impoundment and forfeiture programs for hooning offences.
1.8 Outline of thesis
This thesis has been structured to reflect the three specific studies undertaken to address the research aims. In this regard, the chapters reflect the various studies, as opposed to the research aims. Studies 1 and 2 were each divided into two parts (a and b), and these studies have, therefore, been divided into two chapters each in this thesis. The studies and chapters were divided in this way because, in both cases, data from the first phase were analysed to inform the direction of the second phase of each of these respective studies, and it was, therefore, inappropriate to describe the results of the two phases together in one chapter. An additional reason for dividing the studies in this way was that there were differences in the sampling techniques and data collection methods between the phases. Chapter 2 reviews the available literature regarding illegal street racing and associated hooning behaviours, the effectiveness of vehicle impoundment programs, literature from other areas of road safety that may be relevant, and the theoretical perspectives incorporated into the theoretical framework of the thesis. The chapter concludes with the key research questions for this program of research that were developed based on identified gaps or research opportunities in the reviewed literature. Part of this chapter was presented at the Australasian College of Road Safety Conference on Infants, Children and Young People: Leal, Watson, Armstrong and King (2007) Enhancing road safety for young drivers: How Graduated Driver Licensing initiatives can complement “anti-hooning” legislation. Chapter 3 describes Study 1a, which involved semi-structured focus group discussions that aimed to provide a foundation for the program of research via Hooning behaviours 11
obtaining an in-depth understanding of hooning behaviours and involved drivers from their perspective. This understanding was also used to inform the development of a quantitative instrument for Study 1b. Part of this chapter was published in a peer-reviewed article in the proceedings of the 2009 Australasian Road Safety Research Policing and Education Conference: Leal, Watson, Armstrong and King (2009) “There’s no way in hell I’d pull up”: The deterrent and other effects of vehicle impoundment laws for hooning. Chapter 4 describes Study 1b, where a larger sample of drivers who self-reported engaging in hooning behaviours in Queensland completed an online survey developed based on the findings of Study 1a. Together, these studies explored all of the key research questions from the driver’s perspective, and were also used to identify further avenues of investigation in Study 2a. Chapters 5 and 6 describe Studies 2a and 2b respectively. These studies profiled a sample of drivers detected and punished for hooning within a 15-month period in Queensland (Study 2a, Chapter 5) and, second, compared these drivers in terms of their official licensing, traffic infringement and crash histories with a comparison group of similar Queensland drivers who did not have a hooning offence during this period (Study 2b, Chapter 6). An earlier version of Chapter 5 was published as a peer-reviewed article in the proceedings of the 2007 Australasian Road Safety Research Policing and Education Conference: Leal, Watson and King (2009) Hooning offenders and offences: Who and what are we dealing with? An earlier version of Chapter 6, using only offenders with an illegal street racing offence, was published as a peer-reviewed article in the proceedings of the 89th Annual Meeting of the Transportation Research Board and in Transportation Research Record: Leal, Watson, & Armstrong (2010) Risky driving or risky drivers? Exploring the driving and crash histories of illegal street racing offenders. Study 3, described in Chapter 7, analysed the post-impoundment driving behaviour of the Study 2b sample in order to address the second research aim regarding the effectiveness of Queensland’s anti-hooning legislation. Consistent with Study 2, this study involved the analysis of official driving records for the three years following the index hooning offence. The three year period was chosen to be consistent with the prescribed period for repeat hooning offences in Queensland’s hooning legislation. The final chapter of the thesis (Chapter 8) draws the results of the three 12 Hooning behaviours
studies together and discusses them in terms of the key research questions and research aims, as well as the implications of the research findings for policy and practice. Recommendations for future research are offered in light of the identified strengths and limitations of this program of research.
1.9 Chapter summary
This chapter has briefly summarised the limited empirical literature regarding illegal street racing and associated hooning behaviours, and vehicle impoundment and forfeiture programs, as all Australian states and territories have implemented laws that give police the power to impound the vehicles of drivers convicted of these offences for increasing periods with repeat offences within prescribed periods. This chapter also introduced the theoretical perspectives adopted in this program of research to better understand the factors associated with hooning behaviours, and to facilitate the evaluation of the effectiveness of current approaches to dealing with the problem (i.e., vehicle impoundment and forfeiture programs). While vehicle impoundment and forfeiture programs can be considered one of the most severe penalties applied to traffic offences, as they involve the temporary or permanent removal of an asset, it was noted that these laws have been implemented in the absence of the evidence of the crash risk of hooning behaviours. It was concluded that there is a need to better understand the on-road risks of these behaviours to inform policy development and traffic law enforcement practice. Further, while the effectiveness of vehicle impoundment (and to a lesser extent, vehicle forfeiture) programs has been demonstrated in North American jurisdictions where the sanctions have been applied to repeat drink driving and driving while suspended or disqualified offences, there is a need to establish the effectiveness of this sanction in dealing with hooning offences in an Australian context. The following chapter describes the literature that led to the research aims and research questions for this program of research. In addition, it describes the theoretical perspectives that underpinned the design of the three complementary studies conducted to address the research aims. The remaining chapters of this thesis describe these studies, with the aim of contributing to the limited body of knowledge regarding the road safety implications of hooning behaviours, and the effectiveness of vehicle impoundment and forfeiture programs in dealing with the problem. Hooning behaviours 13
CHAPTER 2: ILLEGAL STREET RACING AND ASSOCIATED “HOONING” BEHAVIOURS
2.1 Introduction
This chapter reviews the available literature regarding illegal street racing and associated hooning behaviours, and the effectiveness of vehicle impoundment and forfeiture programs. The purpose of this review was to determine the current state of knowledge in the area by exploring a number of key issues, including: who engages in illegal street racing and associated hooning behaviours?; what are the factors that contribute to these behaviours?; what are the road safety implications of these behaviours?; how effective are current approaches to dealing with the problem?; which theoretical perspectives can inform the design of an evaluation of a vehicle impoundment and forfeiture program targeting hooning behaviours?; and, what are the design options and considerations for an evaluation of Queensland’s vehicle impoundment and forfeiture laws for hooning? The review of the literature led to the identification of gaps in knowledge and, therefore, opportunities for further research, which were the foundation for the current program of research described in the remainder of this thesis.
2.1.1 Literature search parameters
In the initial stages of the literature review, searches were conducted to identify scientific papers written in English with citations in the Transport, ScienceDirect, and Google Scholar databases. No date restrictions were applied, but only sources for which the researcher was able to obtain the full-text version of the article were used. The types of publications included in the searches were reports, books, book chapters, journal articles and conference proceedings. A variety of search terms were used. As the term “hooning”, an Australian colloquial term for the group of behaviours under investigation in this thesis, yielded no results, variations on the names of these behaviours were used as search terms. The content of each article was checked by initially reading the abstract to ensure that the subject of the article was illegal driving behaviour. This check was 14 Hooning behaviours
particularly important when using a search term that included “racing”, given that people can participate in sanctioned racing events. Such events were beyond the scope of this thesis. When suitable articles were identified, any unique keywords applied by the authors were used in future searches. The reference lists of relevant articles were perused to identify additional sources. Finally, searches were conducted to identify additional sources that had cited articles identified as relevant to this review.
2.2 Who engages in illegal street racing and associated hooning behaviours?
The available evidence suggests that it is predominantly young (aged 16 to 25 years) males who are involved in the illegal street racing or hooning scene (Leigh, 1996; Peak & Glensor, 2004; Vaaranen & Wieloch, 2002; Warn et al., 2004); however, the number of females attending events is increasing (Armstrong & Steinhardt, 2006). It appears that these are transitory activities, as most people do not continue to participate for more than two or three years (Leigh, 1996). Leigh reports that drivers involved in the Sydney, Australia, street racing scene are predominantly Anglo-Saxon, and most are employed on a full-time basis as mechanics or in other trades, while others are involved in full-time education at high school or TAFE (Technical and Further Education) College (Leigh, 1996). This group shows higher participation in employment and education than their peers, and it is suggested that this tendency may be because street racing is an expensive enterprise. Some respondents had spent $10,000 to $25,000 on their vehicles, and had accumulated several thousand dollars in fines for traffic offences and vehicle defect notices (Leigh, 1996). This finding is in contrast to the Helsinki street racing scene, where “cruising club” boys were typically from working class families, rarely completed secondary school, and took low-paying factory and construction jobs to finance their interest in cars (Vaaranen, 2004). Leigh (1996) found few differences between participants and spectators at street racing events, stating that who actually competes at an event is simply a matter of chance. If spectators in his study did not already own a street racing car, most were in the process of preparing a race-ready vehicle (Leigh, 1996). Drivers involved in hooning have been described in the Australian media as Hooning behaviours 15 young males who drive high performance or “souped-up” cars, rev big engines, play loud music, and travel with groups of “testosterone-addled chums” (e.g., Altman, 2006, January 15; Johnson, 2007; Penberthy, 2004, November 29; Russell & Cooke, 2006, January 15). However, drivers who engage in hooning behaviours have yet to be profiled in a systematic way. Queensland research suggests that drivers involved in the illegal street racing or hooning scene are not a unified group, and can be divided in a number of ways. One such method is on the basis of vehicle choice, for example, a male “car enthusiast” from Brisbane noted that, “There are two types of groups, ‘go’ or ‘show’. Not many people can afford to have a car that is both spastically fast and good looking” (Armstrong & Steinhardt, 2006, p. 40). Each of these groups can be further divided into “car enthusiasts” and “hoons” (the more antisocial element) (Armstrong & Steinhardt, 2006), highlighting the historically arbitrary and culturally-bound nature of the term “hoon”. Thus, it appears that a number of sub-groups of drivers are commonly grouped together and labelled as “hoons”. This labelling has implications for the experience of the drivers themselves, the attitudes of the general public towards hooning behaviours, and the strategies employed by police to effectively detect and target these behaviours. As such, sub-groups warrant further investigation to ensure that “anti-hooning” legislation is targeting all drivers who engage in hooning behaviours and, thus, is having the desired effect of improving road safety. Further, the potential overlap between addressing the hooning problem and the broader young driver problem must be addressed, and is discussed in more detail in section 2.6.1 of this chapter.
2.3 Factors contributing to hooning behaviour
Hooning behaviours, for the purposes of this research, include a variety of different activities. As already noted, the available research (e.g., Armstrong & Steinhardt, 2006) also suggests that there are a number of distinct sub-groups of drivers who engage in hooning behaviours. Thus, it is likely that a number of different factors will contribute to the different behaviours. This section reviews the relevant literature regarding the personal, socio-cultural, and environmental factors associated with hooning behaviours. 16 Hooning behaviours
2.3.1 Person-related factors: young driver issues
Data gathered over a 21-year longitudinal study of a birth cohort of 941 New Zealand children investigated the relationship between attentional difficulties at age 13 and driving outcomes, including involvement in illegal street racing (Woodward, Fergusson, & Horwood, 2000). There was a strong significant association between the extent of adolescent attentional difficulties and illegal street racing. However, after adjusting for significant confounding factors (gender, distance driven, length of time held licence), the association was no longer significant (Woodward et al., 2000). Studies investigating adolescent risk taking while driving have identified sensation seeking and aggressiveness as factors contributing to risk taking (Jonah, 1997). In a study investigating both state (experiences and circumstances surrounding individual driving episodes) and trait (sensation seeking and aggressiveness) factors on Year 12 students’ driving behaviour, it was found that sensation seeking (r = 0.30) and trait aggressiveness (r = 0.32) were significantly correlated with racing another car (Arnett, Offer, & Fine, 1997). Participants kept a log of all of their driving episodes for 10 days and reported the circumstances of each episode immediately after it was over (including driving speed, whether passengers were present, and their emotional state) as a measure of state aggressiveness (Arnett et al., 1997). It was found that adolescents also tended to drive more recklessly when in an angry mood (Arnett et al., 1997). These findings suggest that the basis of adolescents’ risk-taking tendency lies in part in the traits of sensation seeking and aggressiveness (particularly for males, who report stronger tendencies than adolescent girls on both of these traits), but also their emotional state while driving (e.g., state aggressiveness) (Arnett et al., 1997). As it is mainly young drivers who engage in hooning, often in groups, it is worthwhile to review the published research on the increased crash risk of young drivers, and the risk taking behaviour or risky driving behaviour of young drivers (e.g., Arnett et al., 1997; Begg & Langley, 2001; Beirness et al., 2004; Deery & Fildes, 1999; Fergusson, Swain-Campbell, & Horwood, 2003; Harré, Brandt, & Dawe, 2000). Although hooning behaviours (if addressed) are usually only the subject of one or two items in these studies, such as likelihood of driving fast for the thrill of it and driving faster than other drivers (Begg & Langley, 2001), young driver and risky driving research is likely to be relevant to understanding hooning Hooning behaviours 17 behaviour. Second, hooning behaviours tend to occur in group settings (Crang, 2006), thus research assessing the effect of same-aged passengers on young driver crash involvement is also relevant.
2.3.1.1 Risky driving among young drivers
It has been suggested that risky driving amongst teenagers appears to be most associated with driving for recreational purposes, such as when out with friends on a Friday night (Preusser, Ferguson, & Williams, 1998). Further, young drivers are more likely than older drivers to drive “for fun” (Beirness et al., 2004), and according to one researcher, youths have always had a “profound need for speed” (Bender, 2003, as cited in Peak & Glensor, 2004). The group nature of hooning behaviours, and the illegal street racing aspect of hooning, suggests that risky driving research may be relevant. A longitudinal cohort study (N = 936) conducted in Dunedin, New Zealand found that males were more likely to “drive fast for the thrill of it” and “drive faster than other drivers” often or fairly often at age 21 years than at age 26 years (Begg & Langley, 2001). Females were more likely to “drive fast for the thrill of it” often or fairly often at age 21 years than at age 26 years (Begg & Langley, 2001). Risky driving (defined as engaging in risky behaviours often or fairly often) was a predominantly male activity; however, by 26 years of age, many had “matured out” of this behaviour (Begg & Langley, 2001). Among the females, there were few significant changes between ages 21 and 26 years and, at both ages, the prevalence of risky driving and thrill-seeking was relatively low (Begg & Langley, 2001). The findings of this research are similar to those of illegal street racing research, as participants are predominantly male and tend to “mature out” of the behaviour (Leigh, 1996; Peak & Glensor, 2004; Vaaranen & Wieloch, 2002; Warn et al., 2004). Similarly, Beirness et al. (2004) have argued that young drivers are at high risk of crash involvement not only because they are relatively new drivers and lack the experience required to help develop higher-order driving skills, but also because of other factors, such as a sense of invulnerability, susceptibility to peer pressure and a willingness to take risks. They challenge the assertion that the reason young people have such high crash rates is that they drive more, as they found that respondents aged 16 to 19 years and 20 to 24 years drove the least number of kilometres in an 18 Hooning behaviours
average month of any age group (300 and 590 kilometres, respectively). In comparison, the median distance travelled in a typical month for the older age groups was approximately 1000 kilometres (Beirness et al., 2004). Thus, when the amount of driving is taken into consideration, the risk of young driver involvement in fatal crashes increases relative to older drivers (Beirness et al., 2004). This finding suggests that it is not the amount of driving that is important, but the behaviour while driving. Beirness et al.’s (2004) research found that young drivers are more likely than older drivers to engage in a variety of high-risk driving behaviours (Beirness et al., 2004). For example: 38 percent of respondents aged 16 to 19 years and 33 percent of respondents aged 20 to 24 years reported taking a risk while driving “for fun” at least occasionally, while only 12 percent of respondents aged 45 to 54 years reported doing so; and 66 percent of respondents aged 16 to 19 years and 43 percent of respondents aged 20 to 24 years reported going driving “just for the fun of it” at least occasionally, while only around one-third of respondents aged 35 to 54 years reported doing so (Beirness et al., 2004). Younger drivers in their sample were also more likely than older drivers to have received a traffic ticket and to have been involved in a crash (Beirness et al., 2004). Research has also considered whether risky drivers select powerful cars; whether powerful cars encourage drivers to take more risks; or whether the relationship between driver risk taking and vehicle type is bi-directional (Horswill & Coster, 2002). If it is the drivers’ risk taking propensity that predicts their car choice, then it could be argued that individuals who take more risks when driving simply choose more powerful vehicles to facilitate their behaviour (Horswill & Coster, 2002). However, it is also possible that certain types of vehicles encourage or facilitate driving styles that may influence crash risk (Horswill & Coster, 2002). Horswill and Coster (2002) found that higher vehicle performance was associated with drivers selecting a higher intended travel speed. When they investigated the causal pathways of this association, they found that this relationship was bi- directional, as respondents who drove faster preferred to buy higher performance vehicles, and participants selected a significantly higher intended speed for a vehicle described as powerful compared with a less powerful vehicle (Horswill & Coster, 2002). This research may be relevant to illegal street racing and associated hooning behaviours, as involved drivers prefer powerful (e.g., turbo-charged) vehicles (Peak Hooning behaviours 19
& Glensor, 2004), or modify their current vehicles to increase power and performance (Leigh, 1996). It is unclear whether hooning behaviours can be considered an aspect of risk- taking that is more common among certain drivers (e.g., young males) as these studies suggest, or a distinct group of risky behaviours with unique characteristics and causes.
2.3.1.2 Peer-aged passenger carriage
Given that hooning tends to occur in group settings (Crang, 2006), the carriage of peer-aged passengers may further increase the crash risk of the hooning driver. Data obtained from the Fatality Analysis Reporting System (FARS database), maintained by the National Highway Traffic Safety Administration (NHTSA) in the United States for fatal crashes from 1990 through 1995 were used to analyse the effect of passenger presence on the fatal crash risk of teenage drivers. The results indicated that passenger presence was associated with proportionately more at-fault fatal crashes for young drivers (aged 24 years and under) (Preusser et al., 1998). However, there was no effect of passengers for drivers aged 25 to 29 years, and passengers were associated with fewer at-fault involvements for drivers aged 30 years and over. The relative risk of fatal crash involvement was particularly high for teenage drivers travelling, day or night, with two or more teenaged passengers (Preusser et al., 1998). A case-control study investigated the effects of passenger carriage for serious (hospitalisation and fatal) crashes in Auckland, New Zealand (Lam, Norton, Woodward, Connor, & Ameratunga, 2003). Interviews were conducted within 48 hours of the crash with case (crash-involved) drivers and control (non-crash involved) drivers. Proxy-interviews were conducted with family or friends for fatally-injured drivers. Passenger ages were defined in terms of the age of the driver, whether the same age or another age. When there was a mixture of same and other aged passengers, this instance was coded as “other” age (Lam et al., 2003). Older drivers (aged 25 years and over) were more likely than younger drivers (aged under 25 years) to be alone when they crashed (59% vs. 34%). Compared with the older drivers, younger drivers were more likely to: be male; crash at night; self- 20 Hooning behaviours
report alcohol consumption; report sleepiness prior to the crash; and drive less each week (Lam et al., 2003). Consequently, these potential confounding variables were included in the analyses. After adjusting for confounding variables, it was found that compared with unaccompanied drivers, the odds of car crash injury among younger drivers was: 2.39 times greater when driving with one passenger of the same age; 15.55 times greater when carrying two or more passengers of the same age; 3.49 times greater when carrying one passenger either younger or older than the driver; and 10.19 times greater when carrying two or more passengers either younger or older than the driver (Lam et al., 2003). In comparison, no increase in risk was observed for older drivers who carried passengers, regardless of passenger age. Thus, it was concluded that the carriage of two or more passengers, irrespective of the ages of passengers, significantly increases the risk of car crash injury among younger drivers (Lam et al., 2003). However, other research has found that, while adolescents drive faster when with friends than when with a parent, they also report driving just as fast when they are alone as when they are with friends (see Arnett et al., 1997). These researchers found that while the presence of a parent seems to inhibit adolescents’ reckless driving, the presence of friends does not appear to influence them to drive any more recklessly than they do when driving alone (Arnett et al., 1997). A number of key themes emerge from the literature discussed in this section. First, young drivers are more likely to drive for fun or recreational purposes with their peers than older drivers. This finding is of concern given the consistent evidence that passenger carriage is a risk factor in the crashes of young drivers. Second, young drivers are more likely to engage in risky driving behaviours than older drivers.
2.3.2 Socio-cultural factors
It has been argued that the car has been socially constructed as the epitome of masculinity, and that motor racing is the public assertion of this masculine power (Leigh, 1996). The response of many young men, it is argued, is to purchase a car, drive dangerously and be entertained by watching motor racing. However, some opt to participate in racing themselves and, unable to race legally, choose to compete on the street (Leigh, 1996). The “deviant” values of street racers may, thus, be traced Hooning behaviours 21 back to the values of the dominant culture. Their crime is a result of being blocked from participation in legal motor sport (i.e., it is one manifestation of the norms of a masculine, car-oriented culture; Leigh, 1996). Similarly, it was the affection felt for cars that was argued to unite the Helsinki “cruising club” boys (Vaaranen & Wieloch, 2002). Vaaranen (2004) found that the street racing boys felt socially and materially incompetent to face the challenges of the bigger world, thus they focused on their peers and after-hours lives on the streets and at the cruising club. They used their cultural performance to create night time counter experiences for their daytime experiences of lost opportunities, to define their masculine identity, and to function as a coping strategy to fight exclusion (Vaaranen, 2004). Joyriding research also argues that this pleasurable and thrilling form of risk-taking provides young males with a way of developing their masculine identity when legitimate avenues have been closed off (McDonagh, Wortley, & Homel, 2002). Thus joyriding, like illegal street racing, can be associated with social marginalisation. Peak and Glensor (2004) argued that illegal street racing provides an unsupervised activity and environment for people who are too young for bars or other adult-only activities, and affords participants a means of socialising with friends. It provides an opportunity to show off one’s vehicle and driving ability, and provides drivers, passengers, and onlookers with the exhilaration of speed (Peak & Glensor, 2004). However, this explanation may be more relevant to jurisdictions with a higher legal drinking age than legal driving age, as opposed to Australia where the minimum age one can drive unsupervised is 17 years (except in Victoria, where it is 18 years) and the legal drinking age is 18 years. Finnish research also argues that a need for excitement leads to street racers organising illegal races for large groups of participants (Vaaranen & Wieloch, 2002). Within this scene, the car-loving youths hang about in cars, drinking beer most weekend nights (Vaaranen & Wieloch, 2002). Alcohol consumption helps them make acquaintances among strangers and young women, since many of them have poor social skills, and will not attempt to talk to a girl when sober (Vaaranen & Wieloch, 2002). Along with attracting the attention of outsiders and the opposite sex, the researchers argued that illegal street racing forms an arena in which to test one’s driving skills with numerous spectators (Vaaranen & Wieloch, 2002). They found 22 Hooning behaviours
that the young men aspire to creating a reputation that stimulates sexual interest from women, and respect-based bonding with men. A reputation can be formed through success in illegal racing, and young women are attracted to those with a reputation, regardless of whether it is good or bad (Vaaranen & Wieloch, 2002). Surveys, focus groups and in-depth interviews with high school students (aged 17 and 18 years) from suburbs in the Greater Manchester area of the United Kingdom revealed that car use should be seen in the framework of sociability and networks, as experiences of extended sociability networks afforded by the car were particularly salient with these participants (Carrabine & Longhurst, 2002). The young people in the study who could not yet drive anticipated that the value of the car lay in the secure maintenance and management of the complex range of activities that make up their everyday lives (Carrabine & Longhurst, 2002). For those who could drive, the major benefit seen was the ability to socialise with friends without having to rely on others, while absence of a vehicle could lead to feelings of social exclusion (Carrabine & Longhurst, 2002). Similarly, among Finnish street racers, it appears that the car serves as the centre for many boys’ social activities, and their car culture functions to create a social community and provides an avenue for learning skills (Vaaranen & Wieloch, 2002). Given the social nature of hooning behaviours, the relationship between peer associations and lawbreaking is of interest. It has been argued that peer networks and associations are especially significant for adolescent delinquency, as most young offenders have co-offenders (Hochstetler, Copes, & DeLisi, 2002). There is anecdotal evidence from Queensland Police Service that this is the case for hooning in Queensland, as although specific data is not collected, it is common for drivers intercepted for a hooning offence to be carrying passengers (Crang, 2006). However, the mechanism by which delinquency is “socially transmitted” remains unclear. Hochstetler et al. (2002) examined the effects of peer behaviour, peer attitudes, and respondent attitudes on both solo and group criminal offending. Differentiating between solo and group offending allowed the researchers to assess whether findings for core theoretical variables were dependent upon the presence or absence of others (Hochstetler et al., 2002). The researchers found that both friends’ attitudes and behaviours were significant predictors of all three forms of criminal offending (group, solo and total; Hochstetler et al., 2002). They further suggested that the influence of a delinquent friend does not alter Hooning behaviours 23 a person’s thinking, even though they can have temporary and immediate effects on their actions (Hochstetler et al., 2002). Those who associate with offenders are obviously more likely to find themselves involved in a criminal event, and no learning or transference of attitudes is necessary if others are present to commit or encourage crime (Hochstetler et al., 2002). Joyriding research also places the crime in a social context (Dawes, 2000, 2001, 2002). Dawes argues that, for young joyriders, the peer group is central in providing the catalyst for their introduction and continuation to car theft and joyriding behaviour. Similar to the experiences of the Helsinki cruising club boys, it also serves as a means of young working class youth finding an identity in one area as a result of their exclusion from other areas, such as school and the job market (Dawes, 2000, 2001, 2002). Joyriding novices learn the skills of car stealing from experienced offenders, similar to a trade apprenticeship (McDonagh et al., 2002).
2.3.3 Environmental factors
Warn et al. (2004) identified interest in motor sport as a potential environmental predictor of participation in illegal street racing and other risky driving behaviours. The relationship between interest in motor sport, illegal street racing, and other risky driving behaviours in a sample of young drivers (aged 15 to 24 years) in Christchurch, New Zealand was investigated (Warn et al., 2004). The researchers argued that “Motor sport provides an environment that can shape an interest in cars and speeding and possibly could encourage spectators to act out risky behaviours when driving on public roads. A more extreme form of acting out would be to participate in illegal street racing” (Warn et al., 2004, p. 2). They suggest that spectators at motor sport events receive messages containing evaluative information on attitudes, norms, and beliefs about speeding and risk taking whilst driving. Further, the celebration of the winners in motor sport (the fastest drivers who demonstrate the best control over volitional risk taking) conveys a message about the social desirability of being able to drive faster and more capably than other drivers (Warn et al., 2004). In their study, involvement in motor sport was directly associated with risky driving, and also indirectly associated with risky driving through attitudes towards speeding. Sensation seeking, participation in motor sport, attitude to speeding, and 24 Hooning behaviours
risk perception predicted 45% of the total variance in illegal street racing behaviour (Warn et al., 2004). The authors state that this finding suggests that motor sport has a strong direct effect on involvement in illegal street racing, independent of any effect of sensation seeking propensity. They further argue that risky driving is a different type of problem to illegal street racing, as the antecedents of risky driving are attitudes and social norms (flowing from involvement in motor sport), whereas the antecedents of street racing are a ‘need for speed’ (measured by sensation seeking), and an opportunity to observe how to do it (attendance at motor sport events) (Warn et al., 2004). If their interpretation is correct, this view has important implications for the development of countermeasures to address illegal street racing.
2.4 What are the road safety implications of illegal street racing and associated hooning behaviours?
While illegal street racing and associated hooning behaviours can be considered a socially problematic group of behaviours (Warn et al., 2004), a number of specific potential harms caused by these behaviours have also been identified, including: road crashes; noise (from vehicles and crowds); vandalism and litter at hooning locations (including businesses where drivers commonly gather); loss of commercial revenue (if crowds obstruct or intimidate potential customers); and excessive wear and tear on public streets (painted street markings are commonly damaged by the burning rubber of vehicle tyres) (Peak & Glensor, 2004). The crash risk is not limited to drivers and passengers, as illegal street races encourage spectators to stand near possibly inexperienced drivers and poorly maintained vehicles, which is a potentially dangerous combination when standing only a few feet away from vehicles racing at highway speeds (Peak & Glensor, 2004). This occurrence is also problematic for spectators viewing burn outs and other displays involving vehicles losing traction with the road surface, as such vehicles are essentially out of control. Although it is assumed by police, the general public, and the media that illegal street racing and associated hooning behaviours pose a significant road safety risk, there is a need to support this claim with empirical evidence. There are a number of ways that the crash risk of illegal street racing and associated hooning behaviours could be quantified. Data are required regarding: the likelihood that Hooning behaviours 25 hooning contributes to crashing (i.e., the riskiness of the behaviour); the proportion of all crashes that involve hooning (i.e., the involvement of the behaviour in crashes); and, finally, the general driving behaviour of drivers who engage in hooning (i.e., the general riskiness of involved drivers).
2.4.1 The riskiness of hooning behaviour
Estimating the riskiness of hooning behaviour requires knowledge of the prevalence of the behaviour in terms of total incidents, and then the proportion of these incidents of hooning behaviour that result in a crash. While involved drivers are likely to accurately recall the number of crashes they have been involved in, it would be more difficult for them to accurately recall the total number of hooning incidents. In addition, there are a number of ways hooning incidents could be defined and measured. For example, is it the number of trips in which hooning occurred that are being summed, or the number of individual hooning acts (e.g., each skid or burn out) that is performed? Examining the road safety implications of hooning by estimating the involvement of the behaviour in crashes is more straight-forward.
2.4.2 The involvement of hooning in crashes
It is known that as the travel speed of a vehicle increases, so does the risk of crashing, as well as the risk of serious injury (Kloeden, McLean, Moore, & Ponte, 1997). While this notion suggests that there is an increased risk of crashing when engaging in hooning (particularly illegal street racing), as this driving behaviour involves high speeds, there is limited empirical literature to support this assertion. The major reason for this limited literature is the lack of dedicated coding and analysis of street racing data within most police agencies (Peak & Glensor, 2004). In an attempt to address this limitation, the FARS database added racing as a factor in 1998. To be included in the database, the crash must occur on a public roadway and result in at least one death to an occupant of a vehicle or non-motorist within 30 days of the crash. FARS data are obtained by reviewing documents including police accident reports, death certificates, state vehicle registration files, coroner / medical examiner reports, state driver licensing files, hospital medical reports, state highway department data, emergency medical service reports, vital 26 Hooning behaviours
statistics, and other state records in each state. Knight et al. (2004) examined FARS data for the years 1998 to 2001 to determine the involvement of street racing in fatal crashes. They found that a total of 315 (0.21%) fatal crashes involved street racing, resulting in 399 fatalities. In 74.9 percent of cases (299 fatalities), either the driver or passenger in the street racing vehicle was killed (Knight et al., 2004), meaning that one in four fatally injured persons could be considered innocent “victims” of street racing. Compared with all fatal crashes, street racing fatal crashes were more likely to occur on urban roadways and more likely to occur in the late evening and early morning hours. The days of the week that street racing fatal crashes occurred were similar to those for all fatal crashes. The researchers concluded that street racing involves risky driving behaviours and warrants further attention (Knight et al., 2004). They argued that urban roads often have increased traffic flow and fixed objects, such as street lights, that may add to the risk of a fatality during a street racing event (Knight et al., 2004). A limitation of this research is that the role of illegal street racing in non-fatal crashes was not examined. Further, the behaviours of interest in this program of research encompass a broader group of behaviours than illegal street racing alone (e.g., burn outs, donuts). Current data entry practices in Queensland, Australia, do not specifically identify illegal street racing or hooning as factors contributing to crashes, although it is possible to search for these terms in free text fields, such as “crash description”. Their inclusion in official datasets is, however, dependent upon police attendance at the crash, and the police officer having knowledge of the behaviour and recording this factor on the crash investigation form. Notwithstanding these issues, “hooning-related” crashes in Queensland were identified by searching the crash descriptions of all crashes involving drivers aged between 12 and 24 years old that occurred between 1999 and 2004 for words that indicated hooning, such as “hoon”, “racing”, “burn out” and “donut” (Armstrong & Steinhardt, 2006). A total of 169 “hooning-related” crashes were identified2. Most of these crashes (78%) occurred within 60 kilometres per hour and lower speed zones, as 60 percent of these crashes occurred on metropolitan roads. Most crashes (72%) occurred during the evenings or at night (between 5pm and 4am). The researchers argued that these trends suggest that hooning-related crashes are largely urban, night
2 A total of 59,014 crashes met the driver age requirements. However, not all crash descriptions were examined – only those that included the search terms. Hooning behaviours 27 time incidents occurring on suburban streets (Armstrong & Steinhardt, 2006), thus, similar to the findings of Knight et al. (2004). However, the researchers did not calculate a proportion of “hooning-related” crashes as their aim was to describe hooning-related crashes, and it was not possible to estimate such a proportion due to the limitations in the study design and data used. For example, they limited the search to young driver crashes only based on the literature regarding drivers typically involved in hooning, and also due to the large number of crash files that required analysis. To objectively measure the proportion of crashes that involve hooning, all crashes should be analysed. Further, as “hooning- related” is not specified as a factor contributing to crashes, researchers must rely on the attending police officer’s knowledge that hooning was involved (from witnessing the crash, or the reports of other witnesses) and reporting this information in the crash description. Finally, not all crashes will have data entered in the crash description field. Nothing being entered in this field may indicate that there were no factors other than those specified to report (i.e., the crash did not involve hooning); however, it is possible that hooning (or any number of other factors) was involved in the crash, but the reporting officer was not aware of it. It is also possible that a crash will have a description that does not include hooning, when hooning may have been involved, but the reporting police officer was unaware of it. Thus, attempts to quantify the proportion of all crashes that involve hooning using official data sources is likely to underestimate to the true involvement of the behaviours in crashes. There is also a need to be careful in how these estimates are described; that is, as a proportion of all crashes, or as a proportion of crashes that included a free text description. While the limited empirical research discussed above suggests that the involvement of hooning behaviours in crashes is relatively low, it is important to note the limitations of the data used. For example, unlike the FARS database in the United States, very few Australian jurisdictions specifically identify hooning as a factor contributing to road traffic crashes, so this information can only be obtained if the attending police officer was aware of the involvement of hooning and recorded this information on the crash form. Researchers must then read through qualitative crash reports for every crash in order to identify if and how hooning may have been involved in the crash, being mindful that not all police officers will record additional information about a crash and, thus, there are issues with using this method to 28 Hooning behaviours
estimate prevalence. The inclusion of hooning or illegal street racing as factors contributing to crashes on official forms should make it easier to identify relevant crashes in future. Further, not all crashes are included in mass crash databases, with only crashes that involve damage above a particular dollar value or are attended by a police officer or paramedic being eligible for inclusion in the Queensland Road Crash Information System. Given that hooning is illegal, there is likely to be far more motivation for drivers to refrain from reporting a crash to police or an insurance company than there are benefits for reporting the crash or admitting to an attending police officer that they were hooning at the time of the crash. Finally, witnesses to hooning offences and crashes are often reluctant to become involved (Folkman, 2005). Thus, it is possible that there are many hooning-related crashes that are not included in official data sources and any attempts to use such data to estimate the involvement of this behaviour in crashes are likely to result in underestimates. Moreover, it is likely that there are many low severity, single-vehicle crashes involving hooning that do not appear in official crash datasets at all.
2.4.3 The general riskiness of involved drivers
In addition to considering other areas of road safety that may be relevant to hooning, an alternative method of exploring the issue and determining whether it warrants special attention is to examine the general riskiness of drivers who engage in the behaviour. For example, Finnish research suggests that drivers who engage in illegal street racing have a history of crash involvement, as most of the “cruising club” boys observed in the study revealed that they had been involved in six or seven crashes; most of them minor crashes, although some were fatal (Vaaranen & Wieloch, 2002). The majority of these crashes occurred when the driver lost control at a high speed, and the car ran off the road (Vaaranen & Wieloch, 2002). This research also found that heavy alcohol use and careless risk-taking were common among street racers (Vaaranen & Wieloch, 2002). This finding suggests that, besides any risk associated with illegal street racing, there may be behaviours associated with it that may increase crash risk and / or severity that warrant further attention. Similarly, Knight et al. (2004) found that, compared to all drivers involved in fatal crashes, drivers involved in street racing crashes were more likely to be male teenagers who were involved in a crash previously and who have been convicted of Hooning behaviours 29 driving violations. Street racers were more likely to be impaired by alcohol at the time of the crash and to have had a previous licence suspension (Knight et al., 2004). However, Australian research suggests that there is virtually no involvement of alcohol or drugs among drivers in the Sydney illegal street racing scene, although alcohol and drug use among observers may be more prevalent (Leigh, 1996). Comparing the traffic and crash histories of drivers who engage in hooning with a comparison group of similar drivers who do not allows the risk of the drivers to be explored, to complement existing research exploring the risk associated with the behaviour. As discussed previously, the existing literature suggests that drivers who engage in hooning behaviour are predominantly young males (Leal, Watson, & King, 2007; Leigh, 1996; Peak & Glensor, 2004; Vaaranen & Wieloch, 2002; Warn et al., 2004), a group known to be over-represented in crashes. This finding means that comparing drivers who engage in hooning with a group of young males who do not allows researchers to explore whether the risk of hooning (if any) is significant over and above the young driver problem. This approach was adopted in Study 2b, reported in Chapter 6 of this thesis.
2.5 Current approaches to dealing with hooning
Section 1.3 briefly described the current approach of Australian jurisdictions to dealing with hooning, with a specific focus on the use of vehicle impoundment and forfeiture programs for these offences. This section describes these programs in more detail. In order to describe these programs, current hooning legislation for each state was sourced from the relevant publicly available government websites. Legislative documents were then searched for key information pertaining to: the prescribed hooning behaviours; maximum lengths of the applicable vehicle impoundment or forfeiture periods; and the prescribed period of time in which drivers must have subsequent offences in order to be treated as repeat offenders. Any errors or omissions as a result of this process are, therefore, the fault of the author. Table 2.1 outlines the descriptions of hooning behaviours that attract vehicle impoundment as a penalty by Australian state or territory. 30 Hooning behaviours
Table 2.1 Illegal driving behaviours and vehicle impoundment periods applied under anti-hooning legislation, by Australian state or territory Hooning-related behaviours Qld NSW Vic ACT Tas NT SA WA Racing and speed trials on roads Wilfully start / drive in a way that makes unnecessary noise or smoke Excessive speed Dangerous operation of a motor vehicle Careless driving of a motor vehicle Organising, promoting or urging others to engage in hooning Reckless driving Disqualified driving Failing to stop when directed by police Reckless entry into level crossing when train / tram is approaching Menacing driving Damaging surface of road or public place Disobey police instruction regarding noisy vehicle Graffiti (if vehicle used to travel to or from site) Driving under influence of alcohol or drugs Second or subs. unregistered, unlicensed, disqualified or uninsured offence Maximum length of vehicle impoundment period Qld NSW Vic ACT Tas NT SA WA First hooning offence within prescribed period 48 hrs 3 mo 48 hrs 3 mo 28 days 48 hrs 7 days 28 days Second hooning offence within prescribed period 3 mo Forfeit 3 mo Forfeit 3 mo 3-6 mo 3 mo 3 mo 6 mo / Third hooning offence within prescribed period Forfeit Forfeit Forfeit Forfeit Forfeit Forfeit 6 mo Forfeit 6 mo / Subsequent hooning offence within prescribed period Forfeit Forfeit Forfeit Forfeit Forfeit Forfeit Forfeit Forfeit Prescribed period for repeat offences 3 yrs 5 yrs 3 yrs 5 yrs 2 yrs 10 yrs 5 yrs Qld = Queensland; NSW = New South Wales; Vic = Victoria; ACT = Australian Capital Territory; Tas = Tasmania; NT = Northern Territory; SA = South Australia; WA = Western Australia. Hooning behaviours 31
The description of hooning-related behaviours in this table is not necessarily how the offence is described verbatim in each jurisdiction, as there were some slight differences. From the table, it can be seen that all jurisdictions impound the vehicles of drivers convicted of taking part in an illegal street race or speed trial, or driving in a way that causes unnecessary noise and smoke (e.g., burn outs, donuts, and other types of skids or manoeuvres that involve the vehicle losing traction with the road surface). However, the number and nature of “hooning-related” offences that also attract vehicle impoundment as a penalty differ between jurisdictions. When vehicle impoundment laws for hooning were first implemented, the penalty periods used in each state were fairly consistent, as states would model their legislative approaches on other states. In recent years, some jurisdictions have strengthened their hooning laws and, thus, have initial impoundment periods of more than 48 hours. These changes have occurred in the absence of objective evidence of the risk associated with hooning behaviours, or the relative effectiveness of different impoundment periods. However, Australian jurisdictions are similar in that their penalty structure involves increasing periods of vehicle impoundment leading to vehicle forfeiture for repeat hooning-related offences within a prescribed period. This prescribed period for drivers to be considered repeat offenders varies between two and 10 years across jurisdictions (Tasmania was not specified), meaning that vehicle forfeiture is more likely in states with longer prescribed periods, such as South Australia, particularly considering the larger number of offences considered hooning- related in that state.
2.5.1 The use of vehicle impoundment in Queensland
In response to a growing number of community complaints regarding street racing, “burn outs” and other hooning behaviours, and the potential for serious injury, legislation was introduced in Queensland on November 4, 2002 to target this group of behaviours (Folkman, 2005). The Police Powers and Responsibilities Act was amended to give police the power to immediately impound the vehicles of drivers charged with one of the prescribed hooning behaviours (i.e., dangerous operation of a motor vehicle, careless driving of a motor vehicle, racing and speed trials on roads, and wilfully causing unnecessary noise or smoke) for a period of 48 hours. The vehicle is towed to the holding yard of the attending towing company or 32 Hooning behaviours
to the nearest police station for storage. If it is the driver’s first offence of this type, no further action is taken on the vehicle. However, the vehicle can be impounded for a period of up to three months, or forfeited to the state, if the driver has been convicted of one or more hooning offences in the previous three years in Queensland. Forfeited vehicles become the property of the state, and can be sold at auction or donated with the permission of the Police Commissioner. In order to impound the vehicle for longer periods for repeat offending, police must apply to a court during the initial impoundment period for an impoundment or forfeiture order. To be considered “previous”, the conviction must have been upheld, and it must have occurred in a separate incident. For example, while it is possible for a person to be charged with several hooning behaviours on the one date as part of a single incident, this occurrence does not make the person eligible for a longer impoundment period or forfeiture unless they have hooning- related convictions prior to this incident (i.e., on an earlier date or time) and within the prescribed period. The use of vehicle impoundment programs in Queensland was extended in 2007 when it was applied as a penalty for a range of other high-risk driving offences. From the implementation of these legislative changes on July 1, 2007, hooning- related offences became known as “Type 1” offences, while Type 2 offences include driving an uninsured and unregistered vehicle, unlicensed driving, high-range drink driving (defined as > 150mg/100mL of blood or > 0.150g/210L breath), failing to provide a specimen as required, driving while suspended for failing to provide a specimen, and driving a defective vehicle when ordered to present vehicle for inspection or comply with a defect notice. People who evade police can also have their vehicle impounded for up to three months or forfeited in addition to other penalties for this offence. However, as noted in section 1.7, this thesis only examined hooning-related (Type 1) offences.
2.5.2 Purpose of vehicle sanctions
As one of the research aims of this thesis was to assess the effectiveness of current approaches to dealing with the problem, it is useful at this point to consider the purpose of vehicle sanctions, such as vehicle impoundment and forfeiture programs. This consideration facilitates the selection of an appropriate theoretical Hooning behaviours 33 framework for the evaluation of the effectiveness of these approaches. Traffic sanctions can be classified according to who, or what they directly target, even though all are ultimately directed at the driver. For example, some target the person directly (e.g., fines), others target the driver through driver’s licence sanctions (e.g., demerit points, suspension or disqualification), while some target the driver through a vehicle sanction (e.g., alcohol ignition interlocks and vehicle impoundment). Licence sanctions including suspension and disqualification are common in many jurisdictions for offences such as drink driving. There are four main objectives of legal sanctions, including licence sanctions: retribution, general deterrence, reform (through rehabilitation and/or specific deterrence) and incapacitation (Ross, 1992; Watson, 1998). For most offenders, licence sanctions, particularly long periods of suspension or disqualification, are a punishment and are, therefore, retributive. However, the general deterrent effect of licence sanctions can only exist if drivers are aware that it is a potential penalty. Where knowledge of the penalty is widespread among the driving population, and the penalty is perceived to be sufficiently severe, certain and swift, general deterrence would be expected, whereas only specific deterrence (an aspect of reform) would be expected when only convicted offenders are aware of the sanction. For example, Mirrlees-Black (1993) found that, while first time drink-driving offenders she interviewed often had not known that they could have their licence disqualified for their offence at the time they committed it, those who had experienced the sanction were far more aware of the penalties. The majority of offenders interviewed in her study claimed that having their licence disqualified had deterred them from future offending, and the sanction was most effective when it resulted in severe disruption to offenders’ lives (Mirrlees-Black, 1993). In terms of incapacitation, it is intended that licence suspension or disqualification will prevent the offender from driving. However, studies of suspended or disqualified offenders suggest that up to 75% continue to drive during the sanction period (e.g., Mirrlees-Black, 1993; Ross & Gonzales, 1988; Watson, 2003). While some researchers have suggested that there is sound evidence to suggest that suspended drivers may drive less and somewhat more carefully to avoid detection (e.g., Beirness, Simpson, & Mayhew, 1997; Mirrlees-Black, 1993; Voas & DeYoung, 2002), many offenders receive traffic citations and are involved in crashes during periods of licence suspension (Levy & Frank, 2000). Further, Watson (2004a) 34 Hooning behaviours
argued that although unlicensed drivers may reduce their driving exposure to avoid detection, this practice does not necessarily result in safer driving. His study found that unlicensed drivers were 2.90 times more likely than licensed drivers to be involved in a crash, and their crashes were significantly more severe. Given that drivers who have had their licence suspended or disqualified have been identified as dangerous drivers, their continued driving is concerning. Poor compliance with licence sanctions may be due, in part, to the difficulties in identifying these drivers. In the United States, for example, licence sanctions are difficult for police to enforce, as they cannot check a driver’s licence unless they have been stopped for another offence or at a traffic enforcement checkpoint (Voas, Tippetts, & Taylor, 1996, 1997). Additionally, most Australian states including Queensland do not have compulsory carriage of licence laws for all drivers and may, therefore, experience similar problems. Thus, disqualified drivers may perceive that the likelihood of being detected driving while disqualified is low, and continue to drive illegally. This perception was evident in self-report research with drivers whose licence was revoked for a drink driving offence (Ross & Gonzales, 1988). Further, Australian research into unlicensed driving found that 30.5% of the sample of 308 unlicensed drivers interviewed continued to drive between the time they were detected and then appeared in court (Watson, 2002). Further, 164 drivers (53.1% of the total sample) reported being stopped by police while driving unlicensed. Of these, 97 (59.1% of drivers stopped, 31.4% of total sample) did not have their licence checked on at least one occasion (Watson, 2002). The relatively low probability of apprehension in many jurisdictions as well as difficulty and cost of licence reinstatement also discourages the reinstatement of licences by offenders. Several studies have indicated that the reinstatement rate is as low as 50% or less (Voas & DeYoung, 2002). As a result, the full impact of the licence sanction is compromised and the long-term effectiveness of the system is partially eroded if those who do not reinstate their licences continue to drive. For this reason, it has been suggested that the penalty for driving while suspended or disqualified should be the removal of the vehicle (Beirness, Simpson, & Mayhew, 1997; Voas, 1992; Voas, Tippetts, & Taylor, 1998). The use of vehicle sanctions has become more widespread in recent years as a countermeasure designed to support licence sanctions and improve road safety. There are two main types of vehicle sanctions used in Australia and New Zealand: alcohol Hooning behaviours 35 ignition interlock devices; and some combination of vehicle immobilisation and impoundment, either for a specified period of time or permanently (i.e., vehicle forfeiture). Only the literature regarding vehicle impoundment and forfeiture programs will be reviewed further in this thesis, as these are the vehicle sanctions that have been applied for illegal street racing and associated hooning offences. Drink driving and the use of alcohol ignition interlocks as a sanction to address this problem are beyond the scope of this thesis.
2.5.3 Effectiveness of vehicle impoundment programs
Prior to the implementation of “anti-hooning” legislation, police presence at illegal street races in Sydney did appear to affect subsequent behaviour (Leigh, 1996). For example, attendance at street races in Sydney fluctuated according to the amount of police resources invested in controlling it (e.g., issuing vehicle defect notices). That is, if a large number of such notices were issued in a weekend, attendances at races over the following weeks was reduced (Leigh, 1996). There is some evidence that the availability of regular, legal, street racing events may reduce illegal street racing. Leigh (1996) reports that in Melbourne, where legal street meets were held weekly, the incidence of illegal street racing was far lower than in Sydney, where legal street meets were held monthly. In Queensland, since the introduction of this legislation in November, 2002 (and until the end of 2009), 5,470 vehicles were impounded for hooning offences. Of these, 5,288 were held for a period of 48 hours for a first offence. A small proportion of impoundments (n = 208, 3.8%) were held for up to three months for a second offence, while 19 vehicles were forfeited to the state for third (n = 17, 0.30%) or fourth (n = 2, 0.04%) offences (Queensland Police Service, unpublished data). While the Queensland Government has argued that the small percentage of repeat impoundment periods indicates that the legislation is successfully deterring hooning behaviours (Queensland Transport, 2006), the numbers of vehicles impounded for first offences has remained fairly stable (Queensland Police Service unpublished data), indicating that the general deterrent effect of the laws is weak. Evaluations of the Victorian and New Zealand vehicle impoundment programs are still in progress and results are yet to be made publicly available. Thus, the effectiveness of the implementation, procedures, and deterrent effects of vehicle impoundment 36 Hooning behaviours
legislation for hooning offences in an Australian context has not yet been established. Preliminary information regarding New Zealand’s program from the Land Transport Safety Authority (cited in Watson, 2004c) were promising. The vehicles of drivers whose licence was revoked, disqualified or suspended could be impounded for 28 days. Since the implementation of vehicle impoundment in May 1999, there was a decline in the involvement of disqualified and unlicensed drivers in crashes, and disqualified driving offences. However, as vehicle impoundment was implemented at the same time as mandatory licence carriage and photo licences, it was not possible to isolate the independent effect of the vehicle impoundment program. Nonetheless, there is published evidence from Canada and the United States that vehicle impoundment is an effective sanction for repeat drink drivers and drivers who continue to drive while suspended or disqualified (Beirness, Simpson, Mayhew, & Jonah, 1997; Voas et al., 1996, 1997, 1998).
2.5.3.1 Canada
Manitoba became the first province in Canada to introduce administrative licence suspension in November 1989. To combat the problem of driving while suspended, legislation was simultaneously implemented to give police the power to seize and impound for a period of 30 days (or 60 days for a repeat occurrence) the vehicle of any person found to be driving while suspended (DWS), disqualified, or otherwise prohibited from driving. While these were intended as drink driving countermeasures, they applied to all drivers disqualified from driving for any reason (Beirness, Simpson, & Mayhew, 1997). Beirness et al. (1997) evaluated the effectiveness of this program by comparing various outcome measures in Manitoba with a comparable control region, Saskatchewan, that did not have administrative licence suspension or vehicle seizure and impoundment as sanctions for these offences. A comparison of offences five years prior to and up to five years following the introduction of these laws revealed that these programs had a substantial impact on drinking and driving and DWS offences (Beirness, Simpson, & Mayhew, 1997). The authors argued that these effects were largely due to the impact these programs had on persons directly affected by them (i.e., a specific deterrent effect), as vehicle seizure and impoundment was associated with significant reductions in repeat DWS offences and Hooning behaviours 37 other traffic offences. These effects were not short-term temporary effects, rather the impact of these programs was maintained over a six year period (Beirness, Simpson, & Mayhew, 1997). In terms of a general deterrent effect, drinking driver fatalities in Manitoba decreased by 27%, while all fatalities during this period increased by nine percent (Beirness, Simpson, & Mayhew, 1997). While there was a similar significant reduction in drinking driver fatalities in Saskatchewan (the comparison area), this decrease occurred in conjunction with a nine percent decrease in all fatalities in this region. Thus, although drinking driver fatalities decreased in both the intervention and comparison areas, time series intervention analysis controlling for the overall trend in fatalities revealed that the effect of the intervention was significant (Beirness, Simpson, & Mayhew, 1997). Survival analysis revealed that there was also a substantial long-term specific deterrent impact of these programs. Up to four years later, persons convicted of DWS after the introduction of vehicle seizure and impoundment were significantly less likely to be reconvicted of the offence than drivers not subjected to vehicle seizure and impoundment (Beirness, Simpson, & Mayhew, 1997). The major limitation of this study for researchers and policy makers interested in vehicle seizure and impoundment is that it was not possible to disentangle the unique and combined general and specific deterrent effects of administrative licence suspension and vehicle seizure and impoundment, as both sanctions were introduced simultaneously. Thus, it is possible that the observed effect was the result of the separate as well as the combined influence of the two programs. Further, other programs likely to affect re-offence rates were also in place that may be responsible for some of the observed effects. However, the authors argued that given the sudden drop in outcome measures, it is likely that the vehicle seizure / impoundment and administrative licence suspension programs contributed to a significant reduction in re-offence rates, traffic violations, and crashes (Beirness, Simpson, & Mayhew, 1997).
2.5.3.2 United States
The remaining published evaluations of vehicle impoundment programs have been conducted in jurisdictions within the United States. For example, the first two 38 Hooning behaviours
years of the vehicle immobilisation and impoundment laws in Franklin County (Columbus), Ohio were evaluated by Voas et al. (1996, 1997). Variations in police enforcement and judicial sentencing policies meant that some offenders who were eligible for impoundment and immobilisation did not receive the sanction, allowing the recidivism rates of these offenders to be compared with individuals who did receive a vehicle sanction using survival analysis. Tracking of these two groups of offenders for up to two years demonstrated that the offenders who received the sanction had lower recidivism rates, both before and after they were able to reclaim the vehicles (Voas et al., 1996, 1997). Offenders were separated based on how many offences they had (one, two or three) and whether the offence was DWS or driving under the influence (DUI). First time DWS offenders could lose the vehicle for 30 days, or 60 days for a repeat offence. Second time DUI offenders could lose the vehicle for 90 days, or 180 days for a third offence. Beyond these offences, drivers could lose the vehicle permanently. During the period that the vehicle was impounded, significant differences in recidivism rates for DWS offences between those who experienced the sanction and those who did not were observed for first-time DWS offenders (0% vs. 3.6%) and second-time DUI offenders (0.8% vs. 3.6%). The significant effect sizes of 100% and 66% respectively reduced to 23% and 38% after the offender was eligible to reclaim the vehicle, and were no longer significant. However, once the offenders were eligible to reclaim the vehicle, a significant difference in DWS offence rates was observed for third-time DUI offenders (4.3% vs. 11.8%). For DUI offences during impoundment, significant differences in recidivism rates were observed for second-time DUI offenders (1.8% vs. 3.8%). While this effect reduced from 53% to 38% after the offender was eligible to reclaim the vehicle, it was still statistically significant. These results show that the differences in recidivism rates between groups were generally large, and there was evidence of a deterrent effect (or at least habituation to not having a vehicle) following the release of the vehicle (Voas et al., 1996, 1997). The authors evaluated a variation of the same law in Hamilton County (Cincinnati), Ohio, where vehicles were impounded for DWS or DUI offences, and obtained similar results (Voas et al., 1998). Compared with offenders who did not receive the sanction, survival analysis revealed that there was a 42.1% reduction in DWS offences during the period in which the vehicle was impounded, although this Hooning behaviours 39 effect size reduced to 25.2% post-sanction (up to two years after) (Voas et al., 1998). There was a 38.8% reduction in repeat DUI offences by multiple offenders while the vehicles were being held by the police, and this effect reduced to 24.6% after they were returned to the offenders (Voas et al., 1998). These results indicate that the effects of vehicle impoundment persist beyond the sanction period, albeit to a lesser extent. It is unclear whether the finding observed by Voas et al. (1996, 1997, 1998) that the effect of impoundment persists beyond the impoundment period itself reflects a deterrent (i.e., the cost and inconvenience of the penalty was so painful that the offender was motivated to avoid being detected again), or an incapacitation effect. Incapacitation could result from vehicle impoundment because some offenders who experienced long impoundment periods may not have reclaimed their cars, or because drivers whose offence resulted in the impoundment of an employer’s or spouse’s vehicle may have been denied access to the vehicle after it was released (Voas et al., 1996, 1997, 1998). While the application of vehicle impoundment to some but not all offenders created a comparison group for analyses, the authors note that a major limitation of the two studies was that the inability to assign the vehicle penalty at random to eligible offenders may have influenced the results. They state that the combination of administrative and personal factors that determine whether the offender was in the sanction versus no sanction group meant that there were some pre-existing differences between the groups (Voas et al., 1996, 1997, 1998). While the Cox regression technique used in these studies allows the use of covariates in the analyses, the researchers did not have a great deal of demographic data available to use as potential covariates (Voas et al., 1996, 1997, 1998). However, demographic data and prior driving history measures were available for use as covariates in published evaluations of California’s vehicle impoundment program, which represents the most extensive current use of vehicle sanctions in the United States. Law enforcement officers can immediately impound vehicles of drivers who do not have a valid licence for 30 days. DeYoung (1997, 1998, 1999, 2000) has examined both the specific and general deterrent effects of this program. Demographic and prior driving history measures used as covariates in the statistical analyses were collected from the Department of Motor Vehicles driver record database and the US Census. The covariates included subject-specific 40 Hooning behaviours
variables, such as age and prior driving history, as well as aggregate-level measures categorised by ZIP code, such as crash and conviction rates. Data on traffic convictions and crashes occurring one year subsequent to the triggering DWS or driving while unlicensed (DWU) incident were also gathered from the Department of Motor Vehicles database and used to measure the effects of impoundment (DeYoung, 1997, 1999). The use of these covariates provided added confidence to the results, as it was possible to control for the pre-existing differences between groups that are problematic when random allocation to groups is not possible. Thus, it is possible to be more confident that any observed differences in re-offence rates between the groups were due to the impoundment program and not other factors (Voas & DeYoung, 2002). Specific deterrent effects were observed in the year following the impoundment period, as drivers whose vehicles were impounded had 23.8% fewer subsequent convictions for DWS or DWU relative to similar drivers whose vehicles were not impounded. They also had 18.1% fewer traffic convictions, and had been involved in 24.7% fewer crashes (DeYoung, 1997, 1999). These differences were even larger for offenders with previous convictions whose vehicles were impounded, as in the year following the impoundment period, repeat offenders had 34.2% fewer subsequent convictions for DWS or DWU than similar drivers whose vehicles were not impounded. They also had 22.3% fewer traffic convictions and were involved in 37.6% fewer crashes (DeYoung, 1997, 1999). In terms of a general deterrent effect, DeYoung (1998, 2000) found that there was a 13.6% reduction in the crash rate of suspended or revoked drivers in California when the vehicle impoundment law was implemented. However, this initial effect reduced fairly quickly. Approximately 78% of the effect had disappeared after four months, and it had almost completely vanished (99.3%) after one year. The comparison group also showed an 8.3% reduction during the same period. While this reduction is smaller than that observed for the suspended / revoked drivers, it is of the same general magnitude, as the difference between the two reductions was only marginally significant (p = .10), suggesting that the law had relatively little general deterrent impact (DeYoung, 1998, 2000). DeYoung (1998, 2000) points out that because the drop in crashes for suspended / revoked drivers was larger than the corresponding drop for control drivers, it appears that there was some general deterrent effect of the laws. However, Hooning behaviours 41 he cautions that since more than three-quarters of the effect had dissipated after about four months, the initial effect is of little practical significance.
2.5.4 Effectiveness of vehicle forfeiture programs
In their review of vehicle impoundment and forfeiture laws, Voas and DeYoung (2002) concluded that the available literature suggests that vehicle impoundment laws are associated with reductions in both traffic offences and highway crashes among suspended drivers that are both statistically significant and practically important. A question that naturally arises is whether or not progression to vehicle forfeiture has an incremental effect beyond impoundment (Peck & Voas, 2002). It has been argued that the evidence regarding the effectiveness of forfeiture laws is much less clear, because while jurisdictions actively enforce impoundment laws, few enforce forfeiture laws (Peck & Voas, 2002). Of the five major reasons given by police agencies for not enforcing the forfeiture statute, two appeared to be the most significant: lack of district attorney support and poor cost-benefit potential (i.e., the cost of enforcement and prosecution exceeds the value of the vehicle) (Peck & Voas, 2002). Further, the vehicles of many first-time offenders are voluntarily forfeited, as they are not collected at the end of the impoundment period, often because the cost of reclaiming the vehicle by paying towing and storage costs exceeds the value of the vehicle itself. This means that many offenders in the impoundment group are not truly independent of those in the forfeiture group. Finally, the sample of drivers who have experienced vehicle forfeiture is small, making evaluations of such programs difficult due to inadequate statistical power (Peck & Voas, 2002). Incidentally, however, the threat of vehicle forfeiture may be an important component of the specific deterrent effect achieved by vehicle impoundment programs. A vehicle forfeiture program implemented in New York City in February 1999 aimed to target drivers charged with driving while intoxicated (even for the first time), as first time drink driving offenders are responsible for 87% of driving while intoxicated fatalities (Safir, Grasso, & Messner, 2000). The penalty is based on the premise that the vehicle is property that is the instrument of a crime (Safir et al., 2000). Early results indicated that vehicle confiscation may have been effective, as alcohol-related crashes decreased by 14.4% in the first 10 months of the program, 42 Hooning behaviours
and alcohol-related fatalities decreased by 32.2%. These reductions are particularly important when compared with overall trends during this period, where increases were observed for all fatalities (18.2%) and all crashes (6.5%) (Safir et al., 2000). Alcohol-impaired driving arrests (of drivers with a Blood Alcohol Content of 0.10% or more) also declined by 22% (Safir et al., 2000). However, as no further evaluation of the program has been published, there is no evidence for the long-term effectiveness of vehicle forfeiture programs.
2.5.5 Summary
Published evaluations of vehicle impoundment programs reviewed in this section indicate that these programs have been generally successful in reducing re- offences and unsafe driving by offenders (Beirness, Simpson, & Mayhew, 1997; DeYoung, 1997, 1999; Sweedler & Stewart, 2000; Voas, Fell, McKnight, & Sweedler, 2004; Voas et al., 1996, 1997, 1998). These results suggest that vehicle sanctions are promising countermeasures for reducing DUI and DWS recidivism. There is also some evidence to suggest that vehicle impoundment may reduce the occurrence of crashes (Beirness, Simpson, & Mayhew, 1997; Levy & Frank, 2000), and that these effects persist (to a lesser extent) after the vehicle is returned to the offender (Beirness, Simpson, & Mayhew, 1997; DeYoung, 1997, 1999; Sweedler & Stewart, 2000; Voas et al., 1998). This finding may suggest that vehicle impoundment programs are more effective than alcohol ignition interlock programs in dealing with drink driving offenders, where some evaluations have found that the effects do not persist once the interlock has been removed from the vehicle (e.g., Popkin, 1994; Tippetts & Voas, 1997). Thus, any effects associated with interlocks appear to be the result of incapacitation rather than reform through specific deterrence (Watson, 1998). However, further research regarding the effectiveness of vehicle forfeiture programs is required.
2.6 Evaluation issues
To date, all studies of vehicle impoundment programs have been quasi- experimental in nature, reflecting the difficulty of randomly assigning offenders to different punitive sanctions. The findings of quasi-experimental designs are more Hooning behaviours 43 vulnerable to rival alternative hypotheses than those from experimental designs. Nonetheless, quasi-experiments can provide fairly convincing findings if potential biases are explored, statistical or design controls used, and studies replicated using different methods and measures (Voas & DeYoung, 2002). Most researchers have employed statistical or design controls to minimise differences among non- equivalent groups, and all studies reviewed found reductions in recidivism with similar substantial effect sizes (Voas & DeYoung, 2002). Overall, large sample sizes (allowing sufficient statistical power) and replication among the stronger studies add credibility to the collective findings that vehicle impoundment and / or immobilisation are associated with declines in crashes and traffic offences that are both statistically and practically significant (Voas & DeYoung, 2002). One problem more difficult to overcome is that road safety countermeasures are rarely implemented in isolation. Study outcomes may be affected by the concurrent implementation of other countermeasures that address either the same issue or other road safety problems, or by other changes in traffic enforcement practices. For example, a driver may experience other sanctions in addition to vehicle impoundment for the one offence, such as fines and licence suspension, making it difficult to isolate the unique effects of vehicle impoundment from other sanctions, and to determine which aspects of the road safety program are effective or the most influential in terms of changing driver behaviour. Similarly, other initiatives that are unrelated to vehicle impoundment may impact the target group and their behaviour. As the available research suggests that drivers likely to engage in hooning behaviour are young, initiatives addressing young and novice drivers may have an indirect effect of reducing hooning behaviours that can occur among groups of young drivers, due to the overlap in targeted drivers and the increased likelihood that the hooning driver will come into contact with police.
2.6.1 Young drivers and Graduated Driver Licensing systems
Novice drivers (i.e., those drivers of licensing age, but under the age of 25 years) are over-represented in crashes. While young drivers comprise around one tenth of drivers on the road in OECD countries, they are involved in approximately one quarter of crashes (Organisation for Economic Co-operation and Development, 44 Hooning behaviours
2006). In Queensland, novice drivers3 were more likely to be at fault for their crashes compared to open licence holders, and the most common contributing circumstances for crashes where the driver or rider was a provisional licence holder included: inexperience / lack of expertise (40.2%); undue care and attention (16.1%); over prescribed concentration of alcohol (3.4%); and excessive speed for the circumstances (2.3%) (Queensland Parliamentary Travelsafe Committee, 2003). While errors in the early stages of acquiring a new skill as complex as driving are to be expected, the risk taking literature discussed previously in this chapter highlights that this type of recklessness is more common among young drivers. Graduated Driver Licensing programs cannot directly address deliberate risk taking on the part of the new driver, rather “a fundamental purpose of graduated licensing is to provide new drivers with the opportunity to gain driving experience under conditions that minimize the exposure to risk” (Simpson, 2003, p. 27). Graduated Driver Licensing programs impose a number of restrictions on the novice driver that are gradually and systematically removed as they gain on-road unsupervised driving experience, and these programs usually impose penalties on the novice driver at a lower threshold than what applies to open (or full) licence holders (Simpson, 2003). Many Australian jurisdictions have strengthened their existing Driver Licensing programs in recent years. While there are many similarities across jurisdictions, this thesis is primarily concerned with the new Graduated Licensing System in Queensland that commenced on July 1, 2007. Described in more detail in Appendix A.1, key changes include, but are not limited to: reducing the minimum age a Learner licence can be obtained from 16.5 to 16 years; increasing the minimum length of the Learner licence from 6 to 12 months; requiring drivers to display L and P plates; varied mobile phone restrictions for driver and passengers according to licence level; the requirement that Learners keep a log book recording a minimum of 100 hours driving experience; the division of the Provisional licence phase into two phases (P1 and P2) with varied restrictions relating to peer-aged passengers, mobile phone use and the power of vehicles (late night driving restrictions can also be imposed if all four demerit points on licence are lost); and the introduction of a Hazard Perception Test (HPT) to graduate from the P1 to the P2 licence.
3 87.1% of Provisional licence holders in Queensland in 2002 were aged less than 25 years. Hooning behaviours 45
2.6.1.1 Is hooning part of the broader “young driver problem”?
It has been argued within the current chapter that while there is growing community concern about hooning behaviours, there is limited empirical evidence of the road safety implications of these behaviours. Further, drivers likely to engage in hooning behaviours are young males, a group known to be at-risk of involvement in a road traffic crash. Thus, it is unclear whether the risk (if any) associated with hooning behaviours is due to the behaviour/s per se, or the drivers likely to engage in the behaviours. In addition to this similarity between the hooning and young driver populations, similarities also exist between the countermeasures employed to address hooning and young driver issues. With regards to hooning offences, vehicle impoundment serves to punish the offender by seizing an object of value. However, it can also be considered a method of exposure control, as the sanction constrains the driver’s ability to re-offend during the impoundment period. It is also presumed that the risk of detection and punishment serves as a deterrent for future hooning behaviour. Graduated Driver Licensing initiatives can also be considered a means of exposure control, as they are primarily designed to minimise risk. For example, peer-aged passenger restrictions and mobile phone use restrictions are designed to minimise distraction for the driver. It was noted previously that hooning tends to occur in a group setting, thus there is a need to explore the prevalence of peer-aged passengers in hooning offences and hooning-related crashes. It is equally important to consider whether changes to Graduated Driver Licensing in Queensland and other jurisdictions have flow-on effects to hooning behaviours. Similarly, it remains to be seen whether restrictions on mobile phone use will affect hooning behaviour. In addition to using mobile phones to arrange hooning activities, many mobile phones allow the user to record video footage. Drivers or passengers may film hooning behaviours to upload to internet sites, such as YouTube or MySpace. Further, video call functions may also allow “on-the-spot” live commentary to spectators or friends. High powered vehicle restrictions have also been included in Queensland’s new licensing system as research suggests that drivers take more risks, such as speeding and reckless driving, when in high powered vehicles (e.g., Horswill & Coster, 2002; Leigh, 1996; Peak & Glensor, 2004). These restrictions are also relevant to hooning, and Study 2a explored the types of vehicles used in hooning 46 Hooning behaviours
offences in Queensland; however, the level of detail in the data analysed in this study did not permit an analysis of the proportion of vehicles used in hooning offences which are no longer permitted to be driven by novice drivers under the new system, such as the Subaru WRX, and V8 and turbo-charged vehicles. Finally, late night driving restrictions have been included in the new licensing system as the fatal crash risk for young drivers is approximately three times greater at night than during the day. Similarly, the “hooning-related” crashes described by Armstrong and Steinhardt (2006) tended to occur late at night. Thus, it is clear that hooning and young driver behaviour in general are related road safety issues. Analysis of the nature of hooning offenders, offences and crashes in Study 2b explored this relationship. This evidence suggests that police services and transport agencies may be able to maximise the road safety benefits of their policy and enforcement initiatives, such as Graduated Driver Licensing schemes, as a well-enforced program with high rates of compliance may have a flow- on effect of reducing hooning behaviours. While this effect is advantageous for police services and transport agencies, the overlap in target populations highlights the importance of accounting for these complementary effects in evaluations of the effectiveness of “anti-hooning” legislation and Graduated Driver Licensing programs.
2.6.2 Data available for use in evaluations
Data collection and storage practices relating to hooning in Queensland, and differences in the length of the impoundment periods, mean that published evaluations of vehicle impoundment programs described in this chapter cannot be easily replicated in order to assess the effectiveness of Queensland’s anti-hooning legislation. For example, published evaluations of vehicle impoundment programs have typically compared the during- and post-sanction driving behaviour of drivers who experienced the sanction with a comparable group that did not, when there is no such group in Queensland. Further, impoundment periods in published evaluations start at 30 days, compared with only 48 hours for a first hooning offence in Queensland. As it is unlikely that a driver would have an offence within this period, there is little use in analysing the during-sanction behaviour of Queensland hooning offenders relative to North American evaluations. Further, the initial 48 hour Hooning behaviours 47 impoundment period is applied administratively to all offenders, meaning there is not a comparison group of drivers who did not receive the sanction available. However, it is possible to sample a group of drivers who were detected and charged with a hooning offence prior to the legislation being implemented, but this approach would face additional problems, such as difficulty identifying these drivers due to the lack of dedicated codes in the police database, and no grouping of hooning offences prior to the implementation of the legislation, as well as a potential history bias between the vehicle impoundment and comparison groups. The lack of dedicated codes in relevant databases for hooning offences is a particularly problematic issue as not all of the prescribed hooning behaviours are unique to hooning. For example, dangerous operation of a motor vehicle and careless driving of a motor vehicle offences are also applied to traffic incidents that do not involve hooning. Similarly, there is no specific reference to hooning behaviours on the standard form used by Queensland Police to record the factors contributing to crashes. This omission makes it difficult to determine the extent to which hooning is a factor in road traffic crashes. While introducing unique codes for hooning offences and crashes will not solve the problem of a lack of baseline levels of offending and crashes prior to the introduction of vehicle impoundment as a penalty for hooning- related offences, it will facilitate ongoing monitoring of the legislation and more timely extraction of hooning-related statistics. The introduction of separate hooning “prescribed offence” codes occurred after the Study 2 and 3 datasets were extracted. Additional data collection practices may also address some of the issues noted in published evaluations of vehicle impoundment programs. For example, noting the date the vehicle was collected at the end of the impoundment period (if at all) in a vehicle impoundment database would assist in determining the true end point of the during-impoundment period and beginning of the post-sanction period. This occurrence would address the issue of impoundment turning into voluntary forfeiture raised by Peck and Voas (2002). Such a database could also be used to record additional information provided by the offender, such as whether they had access to another vehicle during the impoundment period. If similar databases were employed across jurisdictions, this would facilitate pooling of data for larger scale evaluations. However, the problem of differences in descriptions of offence types between jurisdictions, and differences in laws relating to privacy and research, may limit the utility of this practice. Finally, the vehicle impoundment database could be linked to 48 Hooning behaviours
other official databases holding crash and offence information to facilitate efficient access to the driver traffic profiles for use in evaluations.
2.6.3 Evaluation design issues
Vehicle impoundment is applied as a sanction to a number of different offence types in Australian jurisdictions and New Zealand, including: hooning- related offences; repeat drink driving; and driving while suspended, disqualified or unregistered. While it is also applied for a number of offences in the United States and Canada, predominantly repeat drink driving and DWS offences, most of the suspensions have been imposed as a penalty for previous drink driving offences (Sweedler & Stewart, 2000) and are, therefore, more closely related to each other than the offences for which vehicle impoundment is imposed in Australia and New Zealand. However, published evaluations of vehicle impoundment programs have analysed the effectiveness of the program separately for the different offence types. As hooning in an Australian context encompasses several driving behaviours that may involve distinct groups of drivers and have different road safety implications, an evaluation of vehicle impoundment as applied to hooning offences should also ideally separate drivers by offence type. A further limitation of published evaluations of vehicle impoundment programs is that they have been based solely on official data sources, such as offence and crash data. Researchers and policy makers make assumptions about what deterrent effect a road safety countermeasure is having based on official data, which is particularly problematic for a sanction such as vehicle impoundment that can have significant social and economic consequences for the offenders and their families in addition to traditional deterrent effects of being punished. It is not possible to fully understand how a program is perceived by targeted drivers, and the effectiveness of different aspects of the legislation and enforcement, without incorporating a qualitative, self-report methodology informed by theory into the evaluation to complement official data sources. This practice is fundamentally necessary to assess the perceptions of the target group, which underpins the desired deterrent effects. Ideally, the qualitative research phase should be partially informed by analysis of official data, as this type of research provides the opportunity to gain a better understanding of the trends observed in official data and any general and specific Hooning behaviours 49 deterrent effects of vehicle impoundment programs. This qualitative research should be conducted with samples from the general community (i.e., drivers with previous offences who did not experience vehicle impoundment), and drivers who have had a vehicle impounded to fully understand the impact of the legislation. Finally, most jurisdictions use increasing impoundment periods for repeat hooning offences within prescribed periods. Although statistically complex, an important avenue for future research is to better understand both the individual and cumulative deterrent effects of increasing impoundment periods.
2.7 Relevant theoretical perspectives
It was noted in section 1.5 that there are a number of benefits of theoretically driven approaches as opposed to purely descriptive, data-driven approaches, particularly in terms of understanding the underlying factors contributing to behaviour, and designing and evaluating targeted countermeasures (Grayson, 1997; Huguenin, 1997). While it was not the purpose of this program of research to test a particular theoretical model, or develop a model that can explain and predict hooning behaviour, a number of theoretical perspectives were identified as being potentially useful in understanding hooning behaviour and the results of Studies 2 and 3. Thus, the purpose of adopting a theoretical framework incorporating these perspectives was to guide the program of research, rather than test the theories. This section describes the selection of the theoretical perspectives for this research, and how they are relevant for illegal street racing and associated hooning behaviour research. At the outset, it is acknowledged that much of the illegal street racing and associated (hooning) behaviour literature to date has been descriptive in nature, examining the issue from a sociological perspective. While this research is informative, these behaviours are now illegal in all Australian jurisdictions and, thus, should also be analysed from a criminological perspective (i.e., the construction of hooning as an illegal behaviour should be considered). Also, given the likely role of person-related factors, such as sensation seeking or propensity for risk taking, there is a need to utilise more psychologically-oriented perspectives. Given the variety of behaviours that constitute hooning behaviours for the purposes of this program of research, and the potential number of factors contributing to the behaviours, it is unlikely that one theoretical perspective will be 50 Hooning behaviours
all encompassing. As such, this program of research adopted a multidisciplinary approach to the utilisation of theoretical perspectives to understand the group of behaviours. As hooning is an illegal behaviour, and one purpose of legislating behaviour is to deter offending, the application of deterrence theory to understanding hooning was explored. However, as the inherently social nature of the group of behaviours is, arguably, not adequately accounted for by a criminological perspective, the application of a psychological / sociological perspective, social learning theory, was also considered.
2.7.1 Deterrence models
A major aim of road rules and, in turn, traffic law enforcement, is deterrence. According to deterrence principles, if the consequences of violating traffic laws are seen as negative or unpleasant, drivers will adhere to road rules in order to avoid this punishment (known as general deterrence). Further, drivers who have experienced punishment for violating road rules will change their behaviour in order to avoid experiencing punishment again (known as specific deterrence). Some penalties also serve to constrain future offending behaviour, such as alcohol ignition interlocks for drink driving, and vehicle impoundment to increase compliance with licence suspension or disqualification. Deterrence theory has traditionally been used as the basis for road safety countermeasures, such as random breath testing and speed camera programs in Australia (Cameron, Cavallo, & Gilbert, 1992; Homel, 1988; Watson, 2003).
2.7.1.1 Classical deterrence theory
In its classical form, deterrence theory posits that individuals evaluate legal threats according to the perceived risk of punishment, which is determined by a combination of the perceived risk of being apprehended and the perceived certainty, severity, and swiftness of legal sanctions. Thus, it is expected that drivers will refrain from engaging in particular behaviours if they perceive the risk of being apprehended by police to be high, believe there is a high certainty that they would receive a punishment when detected, and that the punishment would be severe and delivered in Hooning behaviours 51 a timely manner (Vingilis, 1990). According to the classical deterrence model of hooning presented in Figure 2.1, adapted from Watson (2004c), an individual’s previous experience being punished for hooning, exposure to hooning and other police enforcement, and his/her knowledge of the enforcement and penalties associated with hooning influence perceptions about the likelihood they will be punished for engaging in the behaviour. These perceptions about the perceived likelihood of detection, and perceptions regarding the certainty severity and swiftness of punishment, in turn, influence the decision to engage in hooning behaviour or not. If someone is aware of the police enforcement practices and relevant penalties, and has been punished in the past, he/she should have a high perceived risk of punishment and, therefore, be less likely to engage in hooning behaviour than someone who has less knowledge or experience with penalties, and consequently has a lower perceived risk of punishment.
Past punishment experience (for hooning and other similar offences) Perceived risk of punishment for Exposure to hooning Decision to enforcement Perceived risk of engage in (of hooning activities and detection hooning other police operations) Perceived certainty, behaviour severity and swiftness of sanctions Knowledge of enforcement practices and sanctions (from media and other sources)
Figure 2.1. Classical deterrence model of hooning behaviour
There are two types of deterrence identified in the literature: general and specific. General deterrence refers to the effects of legal punishment on the general public (i.e., potential offenders), while specific deterrence pertains to the effects of legal punishment on those who have experienced it (i.e., punished offenders) 52 Hooning behaviours
(Piquero & Paternoster, 1998; Stafford & Warr, 1993). These are important distinctions, as it is not necessary for an individual to experience a punishment in order to be deterred from engaging in the target behaviour (specific deterrence), as the mere threat of a penalty (general deterrence) can have a much wider impact on community behaviour.
2.7.1.2 Expanded deterrence theory
Classical deterrence theory has been criticised for perpetuating the notion that the two forms of deterrence occur among distinct populations (offenders and non- offenders), and for failing to account for indirect (vicarious) experiences. For example, Stafford and Warr (1993) argue that the conventional distinction between general and specific deterrence is incorrect, and that one individual can experience both general and specific deterrence. Rather than viewing general and specific deterrence as influencing distinct and separate populations, they see general and specific deterrence as opposite ends of a continuum affecting one population (Stafford & Warr, 1993). They postulate that it is possible for both general and specific deterrence to operate for an individual at any given time, and propose that the distinction between the two types of deterrence be limited to contrasting kinds of experience with legal punishment (Stafford & Warr, 1993). If deterrence is based on the fear of legal punishment, then general deterrence refers to the deterrent effect of indirect experience with punishment and punishment avoidance and specific deterrence refers to the deterrent effect of direct experience with punishment and punishment avoidance (Stafford & Warr, 1993). In most populations (i.e., the general public or punished offenders), people are likely to be exposed to a mixture of direct and indirect experience with punishment and punishment avoidance (Stafford & Warr, 1993). Classical deterrence theory has also been criticised for neglecting the effect that punishment avoidance is likely to have on future behaviour (Stafford & Warr, 1993). Punishment avoidance is likely to affect the chances of committing crimes again by influencing (i.e., reducing) perceptions of certainty and severity of punishment (Stafford & Warr, 1993). Stafford and Warr (1993, p. 125) argue that:
“punishment avoidance does more to encourage crime than punishment does to discourage it. Offenders whose experience is limited largely to avoiding Hooning behaviours 53
punishment may come to believe that they are immune from punishment, even in the face of occasional evidence to the contrary”.
Deterrence researchers often presume that offenders only consider their own personal experience when evaluating the certainty and severity of punishment (Stafford & Warr, 1993). However, Stafford and Warr argue that the assumption is problematic for delinquent behaviour, as delinquency is generally a group phenomenon. This argument is particularly relevant to hooning-related driving behaviours, given that these tend to occur in groups, as there may be large groups of spectators, groups of vehicles, and groups within vehicles (Crang, 2006). Thus, these individuals are likely to have collective experiences with companions, meaning that their experiential base is likely to be much larger than their personal experience alone (Stafford & Warr, 1993). It has also been suggested that the immediate presence of others may alter perceptions of certainty and severity, as the presence of others may produce a heightened sense of anonymity or invulnerability among offenders, which may translate into perceptions of low certainty and severity (Stafford & Warr, 1993). Figure 2.2 illustrates a model of hooning behaviour based on expanded deterrence theory.
Personal experience with punishment & punishment avoidance, Perceived Decision Specific personal exposure to risk of to engage enforcement, Deterrence punishment in hooning personal knowledge of enforcement for self behaviour practices and sanctions
Vicarious experience with punishment & punishment avoidance, Perceived
General vicarious exposure to risk of Deterrence enforcement, punishment vicarious knowledge for others of enforcement practices and sanctions
Figure 2.2. Expanded deterrence model of hooning behaviour 54 Hooning behaviours
The model outlines the process of an individual’s knowledge of the enforcement exposure and experience with punishment and punishment avoidance of others influencing their perceptions of risk for themselves, and contributing to their decision to engage in hooning. Stafford and Warr’s (1993) expanded deterrence theory has been applied to a number of areas of road safety research. For example, Piquero and Paternoster (1998) applied the theory to drinking and driving, as this is a relatively common crime and people are likely to have had extensive experience violating drink driving laws, and therefore experience with punishment and punishment avoidance. Consistent with Stafford and Warr’s (1993) theory, they found that deterrence appeared to involve a mixture of both general and specific deterrence mechanisms (Piquero & Paternoster, 1998). Second, it was found that experiences, both personal and vicarious, have mixed effects on behaviour. Some experiences strengthen the expectation that those who drink and drive will be detected, while others reduce the credibility of the law, leading to the belief that they can drink and drive with impunity (Piquero & Paternoster, 1998). It was also found that the model applied equally well to both men and women (Piquero & Paternoster, 1998). Australian drink driving research using a sample of recidivist offenders also found support for the punishment avoidance component of the theory; however, vicarious experiences were not associated with further drink driving behaviour (Freeman & Watson, 2006). Similar results were found in Australian research on unlicensed driving (Watson, 2004c), speeding (Fleiter & Watson, 2006) and hooning (Gee Kee, Steinhardt, & Palk, 2007). However, despite Stafford and Warr’s (1993) expanded theory accounting for a broader range of influences on behaviour, deterrence theory in general has been criticised for its narrow focus on sanctions and for ignoring factors such as the social implications of behaviour (e.g., peer approval), and the intrinsic rewards associated with a behaviour (e.g., feelings of exhilaration when racing) (Fleiter & Watson, 2006; Vingilis, 1990; Watson, 2004c; Zaal, 1994).
2.7.2 Social learning theory
Akers’ social learning theory was developed with a particular emphasis on explaining deviant behaviour, and draws on both sociological and psychological theoretical concepts (Akers, 1977). The sociological influence was drawn from Hooning behaviours 55
Sutherland’s differential association theory, which suggests the primary reason a person engages in deviant or illegal behaviour is because favourable attitudes towards the behaviour exceed unfavourable ones, and that these attitudes are primarily gained from a close group of intimate associates, such as friends and family (Akers, 1998). Akers and Burgess added the psychological learning principles of operant conditioning to this concept (i.e., differential reinforcement through rewards and punishment) to create a broader social learning theory (Akers, 1994). As such, social learning theory can be viewed as:
a behavioral approach to socialization which includes individuals’ responses to rewards and punishments in the current situation, the learned patterns of responses they bring to that situation, and the anticipated consequences of actions taken now and in the future in the initiation, continuation and cessation of those actions. (Akers, 1990).
Social learning theory emphasises the direct and indirect exposure an individual has to the behaviours, attitudes, and norms of associates. The theory posits that the individuals and groups with whom one associates provide the major social contexts in which learning mechanisms operate. Thus, deviance and conformity are learned in the same way, with a balance of influence stemming from the way behaviour is punished and rewarded (Akers, 1990). There are four main components of social learning theory: differential association, imitation, differential reinforcement, and definitions. According to the theory, social behaviour is acquired both through direct conditioning and through imitation or modelling of others’ behaviour. Behaviour is strengthened through reward (positive reinforcement) and avoidance of punishment (negative reinforcement) or weakened by aversive stimuli (positive punishment) and loss of reward (negative punishment). Whether deviant or conforming behaviour is acquired and persists depends on past and present rewards or punishments for the behaviour and the rewards or punishment attached to alternative behaviour – differential reinforcement. Individuals learn in interaction with significant groups in their lives evaluative definitions (norms, attitudes, orientations) of the behaviour as good or bad. The most important of these groups with which one is in differential association are the peer groups and the family but they may also include schools, churches, and other groups (Akers, Krohn, Lanza-Kaduce, & Radosevich, 1979). The theory proposes a process which orders and specifies the relationships 56 Hooning behaviours
among these variables. Differential association, which refers to interaction and identity with different groups, occurs first. These groups provide the social environments in which exposure to definitions, imitation of models, and social reinforcement for the behaviour take place. The definitions are learned through imitation and social reinforcement of them by members of the groups with whom one associates. Once learned, these definitions serve as discriminative stimuli for engaging in the behaviour. These definitions, in conjunction with imitation of behaviour and the anticipated balance of reinforcement, produce the initial behaviour. After the initial performance of the behaviour, imitation becomes less important while the effects of the definitions continue (themselves affected by the experience of engaging in the behaviour). It is at this point that the actual consequences (social and non-social reinforcers and punishers) of the specific behaviour come into play to determine the probability that the behaviour will be continued and at what level (Akers et al., 1979). Figure 2.3 illustrates a social learning theory model of hooning behaviour based on Watson (2004c).
Imitation Overall exposure to people (models) who engage in hooning or not
Differential Differential
association reinforcement Decision to Driving behaviour of Anticipated balance of engage in significant others rewards and punishments hooning Attitudes of significant for hooning behaviour behaviour others towards hooning and alternatives
Definitions Personal attitudes towards hooning behaviour and alternatives
Figure 2.3. Social learning model of hooning behaviour
While this perspective has been successfully used to investigate a wide range of deviant or non-conforming behaviours, it has not been as widely utilised in road Hooning behaviours 57 safety research. However, there is a evidence that it is useful in explaining a variety of driving behaviours, including drink driving (DiBlasio, 1988), and a number of Centre for Accident Research and Road Safety – Queensland research projects examining unlicensed driving (Watson, 2004c), speeding (Fleiter, 2004; Fleiter & Watson, 2006), drug driving (Armstrong, Wills, & Watson, 2005) and hooning (Gee Kee, 2006). While the most important single predictor appears to be differential association (e.g., DiBlasio, 1988; Watson, 2004c), the remaining social learning theory variables have also been shown to be significant predictors of deviant road user behaviour. For example, definitions and imitation add significantly to the prediction of riding with a drunk driver, self-reported speeding, and intention to drive unlicensed (DiBlasio, 1988; Fleiter & Watson, 2006; Watson, 2004c). DiBlasio (1988) found that differential association was the most important variable in predicting an adolescent’s decision to ride with a drinking driver. Using a measure of both parental and peer association, results showed that peer influence on this decision increased with the age of adolescents, such that younger adolescents were influenced more by parents, while older adolescents were influenced more by their peers. More recently, in a study of unlicensed drivers, differential association was found to be the main social influence on those who drive without a licence (Watson, 2004c). Results indicated that differential association was the most important predictor of frequency of unlicensed driving, continued driving after licence disqualification, and future intentions to drive unlicensed, and was particularly relevant to the more deviant offenders in the sample. As such, there is evidence to suggest that the differential association component of social learning theory is particularly applicable to road safety research. In relation to deviant group behaviour, it is recognised by Akers and Lee (1996) that a complex reciprocal process takes place. Groups may be drawn together by a shared thread or threads of attitudes and behaviour, but may also begin to influence each other in refining these attributes (Akers & Lee, 1996). Given the group nature of hooning behaviours (Crang, 2006), it is important to consider how friends’ attitudes and behaviours influence group as well as individual offending. This issue was addressed in a study of adolescent criminal offending undertaken by Hochstetler et al. (2002). As noted earlier, it was found that both friends’ attitudes and behaviours were significant determinants of all three forms of criminal offending (group, solo, and total), and that nearly all of the effects of 58 Hooning behaviours
attitudes and behaviours remained significant predictors of offending when controlling for respondent attitudes. This was true for group and solo crime, which suggests that the effects of friends’ attitudes and behaviours did not operate solely through respondents’ attitudes. The researchers argued that significant results for friends’ attitudes and behaviours for lone offenders lends support to differential association theory as originally formulated (Hochstetler et al., 2002).
2.7.3 Application of theoretical frameworks to hooning behaviour
As hooning behaviours are treated as traffic offences in all Australian, and some international, jurisdictions, it follows that deterrence perspectives are important to understand the behaviours and the effects of countermeasures designed to address hooning. However, this section has argued that the limited literature suggests that the plethora of non-legal factors associated with behaviour, including hooning, warrants the consideration of other perspectives. For example, Akers’ social learning theory has been successfully applied to a number of areas of road safety. Akers (1990) argues that neither deterrence nor rational choice theory is a general or complete model of criminal behaviour, and that a strength of social learning theory is that the central concepts and propositions in each theory – fear of legal punishment in deterrence theory and the reward / cost balance (or expected utility function) in rational choice theory – are subsumable under the more general differential reinforcement formula in social learning theory. He further argues that differential reinforcement refers to the overall balance of rewards and punishment for behaviour, and encompasses a full range of behavioural inhibitors and facilitators: rewards/costs; past, present and future anticipated reinforcers and punishers; formal and informal sanctions; legal and extra-legal penalties; direct and indirect punishment; and positive and negative reinforcement, whether or not rationally calculated (Akers, 1990). Thus, it may be that when applied to hooning behaviours, deterrence theory (both in its classical and reconceptualised form) will not explain significant variability in hooning behaviour over and above that already explained by Akers’ social learning theory. This was the case in a recent study utilising a university student sample to investigate the relative utility of deterrence theory and social learning in predicting hooning behaviours (Gee Kee, 2006; Gee Kee et al., 2007). Hooning behaviours 59
However, Gee Kee’s work measured hooning as a group of behaviours rather than dividing the construct into the various activities considered hooning in Australia. Further, the survey tool was very brief, with many constructs measured by only one item, and the sampling population was not limited to drivers who engage in hooning behaviour, resulting in only a small group of drivers in the “hooning” sub-sample relative to the “non-hooning” sub-sample.
2.8 Chapter summary
The literature reviewed in this chapter has demonstrated that there is growing community concern about hooning behaviours. While governments in all Australian states and territories, and New Zealand, have responded by implementing “anti- hooning” legislation, there is limited empirical evidence of the road safety implications of these behaviours. Further, there is evidence to suggest that drivers likely to engage in hooning behaviours are young males, a group known to be at-risk of involvement in road crashes. Thus, it is unclear whether the risk (if any) associated with hooning behaviours is due to the behaviours per se, or the drivers likely to engage in the behaviours. However, the limited available evidence about hooning suggests that there are a number of sub-groups of drivers within the larger population of drivers generally labelled as “hoons”, of which only some are arguably deviant. This notion has not been investigated by any large-scale research to date. Second, the effectiveness of “anti-hooning” legislation as a sanction to manage hooning behaviours has not yet been established. While there is a growing body of evidence that vehicle impoundment is an effective sanction to reduce recidivism among drink driving offenders and drivers who continue to drive while suspended or disqualified in the United States and Canada, it is unclear whether the sanction is effective in the Australian context, or for hooning offenders. While it is difficult to accurately quantify the amount of police resources devoted to enforcing this legislation, it appears that it is considerable. Queensland’s Traffic Response Group, colloquially referred to as the “Hoon Squad”, conduct regular hooning enforcement operations, and there are also regular multi-agency operations conducted with the Queensland Department of Transport and Main Roads to enforce hooning and vehicle safety laws. There is a need to assess whether the use of these resources is warranted from a road safety perspective. 60 Hooning behaviours
2.8.1 Research aims and key research questions
The purpose of this program of research was to contribute to the limited body of empirical knowledge about hooning behaviours by addressing the following research aims:
RA1. To investigate the road safety implications of illegal street racing and associated (hooning) behaviours, in terms of the risks associated with the specific behaviours, and the drivers who engage in the behaviours; RA2. To assess the effectiveness of current approaches to dealing with the problem; and RA3. To inform policy and practice in the area of illegal street racing and associated hooning behaviour.
A number of research questions were developed to contribute to these research aims. The first two research questions were designed to provide a foundation for the program of research, and better understand the hooning problem. That is, these research questions aimed to contribute to the literature by determining whether the broader group of behaviours collectively labelled as hooning in Australia is similar to the behaviour of illegal street racing as reported in the available literature (described in sections 2.2 and 2.3). These research questions were as follows:
RQ1. Who engages in hooning in an Australian context?; and RQ2. What are the legal, social and psychological factors that contribute to hooning behaviours?
The first research aim of the thesis was refined into research question 3:
RQ3. What are the road safety implications of hooning behaviours?
To further explore the first research aim, the issue of whether illegal street racing and associated hooning behaviours may be considered part of a broader group of risky driving behaviours (as discussed in section 2.3.1.1) was explored in research question 4:
RQ4. Do drivers who engage in hooning also engage in other risky driving behaviours?
Finally, the second research aim was refined into research question 5: Hooning behaviours 61
RQ5. How effective are vehicle impoundment and forfeiture programs at reducing hooning behaviour?
The results relating to all of the research questions (and, therefore, the first two research aims) were designed to address the third research aim of this thesis, that is, to inform policy and practice in the area. These key research questions were addressed in a program of research involving three complementary studies that are described in chapters 3 through 7 of this thesis. The results of all three studies are drawn together to discuss the status of each of the research questions and research aims in the final chapter of the thesis.
62 Hooning behaviours
Hooning behaviours 63
CHAPTER 3: STUDY 1A – FACTORS CONTRIBUTING TO ILLEGAL STREET RACING AND ASSOCIATED “HOONING” BEHAVIOURS (QUALITATIVE PHASE)
3.1 Introduction
This study was designed to provide a foundation for the program of research. It contributed to all three research aims, from the perspective of drivers who self- report engaging in hooning behaviours in Queensland. A qualitative, exploratory approach was used in this study in order to obtain an in-depth understanding of hooning behaviour and attitudes towards Queensland’s vehicle impoundment and forfeiture laws for hooning from the drivers’ perspective. The approach used in this study could also be described as purpose-driven, as the results were used to inform the development of the quantitative survey instrument for use in a larger study (Study 1b) exploring the same issues. Thus, the research utilised qualitative methods to complement subsequent quantitative approaches, a strategy that has been recommended (see Morgan, 1998b). Obtaining a better understanding of hooning behaviours and driver attitudes towards Queensland’s anti-hooning legislation was important for Studies 2 and 3, as qualitative data can provide depth to official statistics, and aid interpretation of results. A qualitative study with drivers who engage in hooning behaviours also has the unique benefit of identifying avenues of investigation with the official data to be collected in these later studies which, taken together, can inform policy development and law enforcement practices. Further, official data alone can rarely provide sufficient insight into the motivations for behaviour, or provide an accurate assessment of the true extent to which someone participates in a particular behaviour (i.e., it is possible for a person to engage in an illegal behaviour regularly, but only be detected and, therefore, appear in official data sources a few times, or perhaps not at all). While there are limitations in the use of self-report data, it can provide important information that cannot be obtained from offence and crash data alone. Second, discussions in Study 1a were used to ascertain the best method of addressing the issues of interest and operationalising the theoretical constructs in 64 Hooning behaviours
Study 1b. This approach ensured that the language used in the questionnaire was understood and commonly used by the target population, and that the questions and response options developed for the quantitative phase would allow participants to provide information that was as thorough and accurate as possible.
3.1.1 Study aims
This study explored all of the research questions of this program of research:
RQ1. Who engages in hooning in an Australian context?; RQ2. What are the legal, social and psychological factors that contribute to hooning behaviours?; RQ3. What are the road safety implications of hooning behaviours?; RQ4. Do drivers who engage in hooning also engage in other risky driving behaviours; and RQ5. How effective are vehicle impoundment and forfeiture programs at reducing hooning behaviour?
Given the qualitative nature of Study 1a, specific hypotheses were not used to guide the research. Rather, the research questions acted as themes underpinning the inquiry.
3.2 Method
3.2.1 Sampling population
The population of interest for this study was drivers who engage in hooning behaviours, as listed in Queensland’s anti-hooning legislation (i.e., Police Powers and Responsibilities Act 2002), including: dangerous operation of a motor vehicle; careless driving of a motor vehicle; racing and speed trials on roads; and wilfully starting a vehicle, or driving a vehicle, in a way that makes unnecessary noise or smoke. To be eligible for participation in this study, the person was required to drive in Queensland and report engaging in at least one of the prescribed hooning behaviours in the previous month. The first criterion was driving in Queensland as opposed to residing or holding a Queensland licence as anyone driving on Queensland public roads, with or without a licence, is subject to Queensland’s road Hooning behaviours 65 rules. The second criterion was defined in terms of the legislation to be consistent with Studies 2 and 3, and to be clear to potential participants about the behaviours under investigation. A time limit of one month was set to facilitate recall and also to ensure that participants had recently engaged in these behaviours, as opposed to having engaged in one or more of the behaviours at some point in the past but no longer doing so. This approach meant that the participants were eligible for punishment under the current anti-hooning laws, and they were, therefore, at-risk of having a vehicle impounded. However, it was not necessary for participants to have been detected and punished under these laws which would have artificially constrained the sample. Rather, they only needed to engage in one or more of the behaviours that could result in these laws being applied. In previous hooning research conducted in Queensland (Gee Kee, 2006; Thake, 2009), the target group included all drivers, irrespective of whether they had previously engaged in any hooning-related behaviours or not. While using that approach in this research could have resulted in the inclusion of people who could be considered to have been successfully deterred by Queensland’s vehicle impoundment and forfeiture laws for hooning, it was not used in this study for a number of reasons. First, the previous research studies obtained very small samples of drivers who engage in hooning, resulting in inadequate statistical power for between-groups analyses. Further, although the time limit of one month meant that people in the sample had recently engaged in hooning, there should still be variability in frequency of behaviour, the types of hooning behaviour participants engage in, and their intentions to do so in future. Finally, the current program of research was primarily interested in the driving behaviour and attitudes of drivers who engage in hooning behaviour, rather than between-groups comparisons of drivers who do and do not engage in the target behaviours. This approach was adopted as research to date has been inhibited by small samples of “hooning” drivers, and it was this target group that was of most interest in the current program of research.
3.2.2 Recruitment method
A sample of 20 to 25 drivers who reported engaging in hooning behaviours in Queensland was desired for this study, as it was expected that this sample size would provide an adequate range of views and approach theoretical saturation (the point at 66 Hooning behaviours
which the collecting of additional data and conducting of further focus group discussions is considered unlikely to yield any new or different information; see Morgan, 1998a). Several months prior to data collection for this study, some media outlets published a story about the research. As some drivers who met the selection criteria for Study 1 had contacted the researcher volunteering to participate in response to these stories, the initial recruitment method was via a media release. The media release included information about the overall program of research, with a focus on this phase of Study 1 and the type of drivers required (see Appendix B.1). As previous contacts had read stories published in free local weekly newspapers, media releases were targeted towards these publications by including the area the newspaper was circulated in. For example, the release sent to the Gold Coast newspaper said “Gold Coast drivers are required…” while the release sent to North Queensland said “North Queensland drivers are required…” and so on. This approach was utilised so as to increase the likelihood of the newspapers publishing a story about the research. This media release resulted in 20 radio interviews and 11 interviews with print journalists within one week of its distribution. Some information about the project was also included in news bulletins of radio stations and newspapers that did not contact the researcher directly for an interview, but had information on the research from the media release or online transcripts of interviews with other media outlets. A media monitoring service revealed that there were more than 50 stories about the research in radio broadcasts and articles in newspapers. Although most clippings were from Queensland, there were a small number of clippings from other Australian states and one international newspaper. Although it was not possible to calculate a response rate using this recruitment strategy, the extent of media coverage suggests that the call for participants had the potential to reach a broad audience. The researcher responded to all enquiries about participating in the research and provided potential participants with further information about what was involved, and confirmed whether they met the selection criteria and whether they were still interested in participating. Participant contact details were obtained so a project information sheet and consent form (Appendix B.2) about the research could be provided, and so that the participants could be contacted at a later date to arrange attendance at one of four focus groups conducted across Queensland. Snowballing was also used as a sampling technique, as drivers who contacted the researcher were Hooning behaviours 67 encouraged to forward information about the research to friends or family members who also met the selection criteria, and who may be interested in participating. After approximately two weeks, there were no new contacts, and the dates and locations for the four focus groups were arranged and participants contacted. The focus groups were conducted over six weeks between August and October 2007. To preserve the anonymity of participants, they were not required to identify themselves when contacting the researcher or when they attended the focus groups, and were specifically discouraged from using their own or other attendee’s names (if known). Thus, it was not possible to identify the number of participants who were recruited directly as a result of personally hearing or reading about the research and those who were recruited via snowballing.
3.2.3 Participants
A total of 22 drivers (18 males, 4 females) participated in the four focus groups conducted in this study. Most participants were under 25 years old (median age = 22 years; range 19 – 45 years), with only four participants aged 25 years or over. Three groups with five participants each were conducted in South East Queensland (n = 15), while one group was conducted in a regional location (n = 7). Participants were reimbursed AU$20 cash for their time and travel costs.
3.2.4 Design and measures
As discussed in section 3.1, Study 1a was a purpose-driven qualitative study that aimed to elicit an in-depth understanding of hooning behaviour that could provide insight to inform the development and operationalisation of study variables for the quantitative survey instrument in Study 1b. Thus, the variables of interest were related to the components of Stafford and Warr’s (1993) expanded deterrence theory, Akers’ (1990) social learning theory, and thrill or sensation seeking (Arnett et al., 1997; Jonah, 1997; Warn et al., 2004). Questions were also designed to explore the influence of others, and drivers’ attitudes towards Queensland’s vehicle impoundment laws as applied to hooning offences, as well as perceptions of the population of drivers that engage in hooning behaviours so as to complement Studies 2 and 3. Table 3.1 outlines the initial prompt questions used in the focus groups. 68 Hooning behaviours
Table 3.1 Focus group variables of interest and initial questions
Variable Prompt question/s Are there different groups of drivers who engage in street racing and associated hooning behaviours? Involved drivers How / why do they differ?
Have you or your friends ever been caught hooning? Have you or your friends ever avoided being caught hooning? How? How likely is it that you will be caught hooning? Reconceptualised deterrence theory If caught, how severe is the punishment? (asked separately for 48 hours, 3 months & forfeiture periods) How likely is it that your friends will be caught hooning? If caught, how severe is the punishment they would receive?
What do your family and friends think about hooning behaviours? Do you have any friends who engage in hooning behaviours? Social learning theory On balance, do you think more good or bad things result from hooning? Do you approve or disapprove of hooning?
Do you usually engage in hooning alone, or with a group? What is it about that group that makes you want to engage in the behaviours? Influence of others Do you ever do things while with the group that you wouldn’t do on your own? How important is it for you to continue to be a member of this group? Thrill-seeking Do you get a thrill out of hooning? What do you think of Queensland’s ‘anti-hooning’ legislation? What do you think others think of it? Queensland’s vehicle impoundment laws What do you think about the way police handle the legislation? as applied to hooning offences What could be done differently? Has the police response made you change your behaviour in any way? How? Do you think others have changed their behaviour? How? Hooning behaviours 69
Prior to commencing the focus group, participants completed a brief demographic survey (Appendix B.3), to allow description of the sample, and some level of descriptive comparison between the sample of this study and those obtained for later studies in the program of research.
3.2.5 Procedure
Clearance to conduct research with human participants was obtained from the Queensland University of Technology Human Research Ethics Committee (reference number 0700000589) prior to participant recruitment. The research project risk assessment was approved by the School of Psychology and Counselling Workplace Health and Safety Officer (project number 110). Participants were recruited as described in section 3.2.2. The focus group discussions were conducted in neutral locations at local universities and Tertiary and Further Education (TAFE) colleges. Refreshments were available prior to focus groups while waiting for all participants to arrive. Once all participants had arrived, the researcher invited everyone to be seated and distributed project information sheets and consent forms. Although people who had contacted the researcher about participating in the research had been sent these documents, they were provided again to ensure that consent to participate was informed, and particularly so that participants who had come along as a result of snowballing could review the information. Participants were given the opportunity to ask any questions before signing and returning the consent forms to the researcher. All groups were facilitated by the researcher, with a research officer taking brief notes to assist in assigning comments to participants during transcription. All participants consented to the focus groups being audio recorded, and were asked not to mention the names of any person (present or not) to protect their anonymity and that of their acquaintances. Each participant was given a name tag with a letter of the alphabet, which was used as an identification code on the demographic survey and focus group transcripts, and allowed the participants to refer to each other without using names. The discussions were semi-structured around the prompt questions outlined in Table 3.1, to allow for a natural progression to the groups’ conversations. As one of the aims of this study was to obtain an understanding of hooning behaviours from the 70 Hooning behaviours
perspective of involved drivers, and understand the lived experiences and meanings ascribed to such experiences by individuals in relation to hooning, the theoretical approach could be described as phenomenological. Where necessary, the facilitator asked additional questions to clarify understanding of participant statements, or to bring the group back on topic. Generally, the role of the facilitator was to encourage all participants to share their opinion about the topic being discussed, without imparting judgement. However, member checking was conducted throughout to ensure that the researcher was interpreting the participants’ comments correctly, giving participants the opportunity to challenge, agree or extend upon comments if needed. At the conclusion of the focus group, participants were given the opportunity to make final comments before the audio recorder was switched off. All participants received an envelope containing AU$20 cash and a business card for the researcher, and were thanked for their time and openness. The brief demographic surveys were entered into a Statistics Package for the Social Sciences (SPSS) data file for analysis. Audio files from each focus group were transcribed verbatim, and checked for accuracy by the researcher and a research officer. However, references to individuals by name or specific locations were not transcribed to protect the anonymity of participants. Using the notes taken by the research officer at each focus group, the researcher assigned a participant identification code to each of the comments. All copies of the audio files were deleted (i.e., from the recorder and the researcher’s computer), and a single copy of the transcription was saved in a password-protected networked drive that is backed- up several times per day, and accessible only to the researcher. The analysis conducted on this information was descriptive in nature, and involved thematic analysis, where the researcher listened to audio recordings while reading the transcripts, and assigned themes to participant statements consistent with the components of the theoretical perspectives addressed in the prompt questions. Comments that did not fit with the theoretical perspectives were described as “other issues”, and those relating to the vehicle impoundment legislation were analysed in consultation with other research team members. The summary analyses were checked by other research team members to ensure validity of descriptions. It was not the purpose of this study to test specific hypotheses or draw conclusions, rather it was to pose open-ended questions to drivers who engage in hooning behaviours to better understand the behaviour and vehicle impoundment laws from their Hooning behaviours 71 perspective, and provide insight into issues that should be explored in the quantitative phase, and the appropriate vernacular to use in that phase.
3.3 Results
3.3.1 Sample characteristics
In addition to the gender and age of participants reported in section 3.2.3, the brief demographic survey allowed the sample to be described in terms of their self- reported education and employment status, and driving history. Table 3.2 outlines the highest level of education attained by participants, employment status, and usual occupations coded into Australian Bureau of Statistics Major Groups (Australian Bureau of Statistics, 1997). An additional “not working” group was also created to include students, retirees and the unemployed. Consistent with the sample of hooning offenders in Study 2, the most common major occupation group was tradespersons.
Table 3.2 Participants’ level of education, employment status and usual occupation (N = 22)
n % Highest level of education Secondary school 6 27.3% TAFE or Technical College (incl. Trade Apprenticeship) 10 45.5% University – Undergraduate 6 27.3% Current employment status Full-time worker 13 59.1% Part-time worker 2 9.1% Casual worker 3 13.6% Student 2 9.1% Student and full-time worker 1 4.5% Student and part-time worker 1 4.5% Usual occupation by ABS Major Groups Tradespersons and related workers 11 50.0% Intermediate clerical, sales and service workers 3 13.6% Professionals 3 13.6% Labourers and related workers 2 9.1% Not working (students) 2 9.1% Intermediate production and transport workers 1 4.5% 72 Hooning behaviours
Information relating to a number of driving variables was also collected. In terms of current licence status, most participants (n = 13) held an Open Driver’s Licence, while six held a Provisional licence, two held a P14 licence, and one held a Learner’s permit. The median number of years participants had held at least a Provisional licence (and could therefore drive unsupervised) was three years (range = 0 – 28 years). Almost two thirds of the sample (n = 14, 63.6%) had been involved in a crash as a driver. Of these, seven were involved in one crash (53.6%), two participants had been involved in two crashes (15.4%), one participant each had been involved in three, four, five and seven crashes (7.7% each), and one crash-involved participant did not answer this question. Three of the crash-involved participants (21.4%) indicated hooning had contributed to one of their crashes (they reported being involved in one, two and four crashes in total respectively). Participants were also asked if they had ever been “booked” (the colloquial term for being detected and punished) for a number of traffic offences. As can be seen in Table 3.3, almost all participants had been previously booked for at least one speeding offence, and approximately half had been booked for vehicle defects. Four participants had been booked for a hooning offence prior to participating in the study, although the participants who had been booked three and five times indicated that these offences had occurred prior to the vehicle impoundment legislation.
Table 3.3 Self-reported offence by type for focus group participants (N = 22) Have you even been booked by Police for … Yes No Speeding 20 (90.9%) 2 (9.1%) Drink driving 4 (18.2%) 18 (81.8%) Unlicensed driving 6 (27.3%) 16 (72.7%) Vehicle defects a 11 (52.4%) 10 (47.6%) Hooning 4 (18.2%) 18 (81.8%) How many times? 0 18 1 2 3 1 5 1 a One participant did not answer this question, thus N = 21
4 In July 2007, Queensland introduced two classes of Provisional licences to their age-related Graduated Driver Licensing System: P1 (for 12 months) and P2 (for 24 months) licences. Hooning behaviours 73
The remainder of section 3.3 describes the focus group discussions. Participants have been assigned a number based on the order in which they have been quoted in this chapter. For example, P#1 is the first participant quoted. Following this code is the gender (M or F) and age in years of the participant. When a series of quotes involves a discussion between participants, this occurrence is either indicated in the preceding sentence, or by grouping the quotes together in the one paragraph.
3.3.2 Involved drivers
Participants in the focus group discussions unanimously agreed that people who engage in hooning behaviours are not all the same, and should be considered as such by the general community, researchers, or police. A number of ways of describing the differences between people who engage in hooning behaviours were discussed, including age of the driver, ownership status and type of vehicle, and the skill and ability of the driver. These issues were often intertwined. The most common factor discussed in all groups was the age of the driver, and this was often linked to the other factors:
“Because half of them are in Mum’s Camry, lifting the guards up and stuff, trying to do a skid. And then there’s the other half that actually got half an interest and have their own gear and it’s fairly decent stuff” (P#1, M, age not specified).
“It’s age. In terms of the legislation, though, the old snoozers with their hot rods, who are over the noise level, who cruise around, have fun, definitely race, do not attract the police attention. Compared to young guys doing exactly the same thing with cars which are far more legal, far more within the guidelines. The term hoon is a label. In our current dialogue, it’s been attributed to young people and poor people. If you are driving a Ferrari, racing, spinning wheels, showing off, the term is not used” (P#2, M45).
“You have got the young fellows who literally are just jumping into simple, six cylinder cars, go out for a bit of a bash. And then you have got the old school, over 40, who literally might go out and just cruise sort of thing in old school fast cars. An old man does a burn out, wicked skid down the street. He’s a legend. The young fellow in a Skyline or WRX does a skid down the street, he’s a wanker” (P#3, M30).
The location in which people engage in hooning behaviours was also 74 Hooning behaviours
considered important, and was used to differentiate between drivers who were seeking public attention and showing off, and those who participate in these behaviours as a serious sport:
“There’s two types of hoons. There’s people that do it in the quiet streets, no one around, nothing to hit or damage if you lose it. And there’s people that do it in stupid areas with people everywhere” (P#4, M19).
“You see a lot of the first timers out and they’ll do stupid things in stupid places, whereas the other crowd probably do stupid things but in places where it’s not as…” (P#1, M, age not specified) “… a threat to other people” (P#5, F22) “Yeah that’s right” (P#1, M, age not specified) “Go outta town” (P#5, F22).
“You have sensible hoons and you have dickhead hoons and there is a huge variation. You’ve got 50 – 60 year old blokes that are hoons but they’re sensible. They don’t go doing stupid things at stupid times. But I would say generally it’s the imported Japanese cars that are the worst offenders with young drivers for purely the dickhead things – burn outs while in close proximity to people and property” (P#6, M37).
“You get the old fellas who won’t do anything around town, they’ll go out to a racetrack or they’ll go out somewhere private and do it” (P#7, M20).
“There’s the show-off factor, and there’s the serious factor, it’s a sport as well” (P#5, F22).
“Some people drive like idiots and some people have a hobby” (P#8, F22).
3.3.3 Expanded deterrence theory
Participants discussed their experiences with punishment and punishment avoidance, and their perceptions of the likelihood they would be caught for a hooning offence and the severity of the different impoundment periods. They also discussed whether the experiences of their friends would be similar to their own. As each focus group consisted of two to six members of the same friendship group, it was generally agreed that the experiences of their friends were similar. However, they suggested that people from other groups may be more likely to be caught based on where they engage in hooning behaviours, and police targeting the vehicles of drivers known to be involved in hooning. Hooning behaviours 75
3.3.3.1 Experience with punishment and punishment avoidance
In terms of indirect experience with vehicle impoundment, all of the participants knew someone who had received this penalty, or had witnessed it being applied to someone. Four participants reported being charged for at least one hooning offence prior to participating in the study, where two participants reported being charged once, one participant reported receiving three hooning offences, and the other reported five. However, only the participants with one hooning offence reported having experienced vehicle impoundment, as the hooning offences of the other participants occurred prior to the implementation of the legislation. Participants discussed many ways that they and their friends had avoided being punished for a hooning offence. In the following exchange, two participants discussed the use of technology to avoid detection:
“There are mobile phones and police scanners” (P#5, F22).
“We’ve heard of cops coming on the scanner and everyone’s just taken off” (P#8, F22).
When asked about how they or their friends had managed to avoid detection, a common strategy discussed was being selective about the location and time:
“Doing it at a place where we are allowed to do it. And we don’t do it in peak hour, we don’t do it in an hour when it’s going to bother someone and we wouldn’t do it in an area that’s going to bother someone” (P#5, F22).
“Not drawing attention to yourself. Doing it in a less populated area” (P#9, F23).
One participant described a very thorough process of determining the level of police activity prior to going out:
“It’s getting a lot more organised these days, so you can get away with it. Even before I bring my car out, I make a phone call or I even take another vehicle out and you go for a safety lap. Less than 10 and it’s not too bad, less than five, you are great, you are out. Police cars that is. This is basically just to take it for a drive, not to go racing. I don’t think anyone ever sends a text message to organise a race. But you get a lot of phone calls – it’s a lot easier way to organise stuff. Mainly it’s just a phone call to see how many police are out. That’s basically what I’m doing” (P#10, M, age not specified). 76 Hooning behaviours
Participants also discussed strategies they or their friends use to avoid punishment once detected by police, including fleeing:
“By running” (P#1, M, age not specified).
“Take off. And don’t muck about. If you are going, you absolutely go” (P#2, M45).
Other strategies were used to take advantage of provisions in the legislation, or providing false information to the police to avoid the application of the relevant vehicle impoundment period:
“People hoon in other people’s cars and when they get police footage or footage of any sort doesn’t necessarily mean it’s the owner of the car” (P#5, F22).
“My car is not under my name as well. Just put it under somebody else’s name. I have never registered a car under my name, put it that way” (P#11, M23).
“Give someone else’s name, address and date of birth” (P#3, M30).
Finally, one participant suggested that the choice and value of the vehicle could minimise the effect of experiencing punishment:
“Then you buy an old snotter, particularly to hoon in. I mean, leave it or set fire to it when you are pulled over. Then you don’t have to worry about it. ‘See you later, I’ll buy another one next pay’” (P#2, M45).
3.3.3.2 Perceived likelihood of detection
Perceptions of likelihood of detection varied from very unlikely to every time they drive, and appeared to be linked to a number of factors. For instance, many participants noted that who you associate with can influence how likely you are to be targeted by police:
“I’ve probably got an 80% chance [of getting caught]. But I think it depends on who you associate with because if you associate with people that are well known hoons obviously you’re going to get targeted more” (P#9, F23).
However, the following exchange that occurred during the same focus group highlights how engaging in hooning behaviours with others can also be protective: Hooning behaviours 77
“If you’re in a group you’re safer. If you go out by yourself for a hoon through town you’re 50% chance of getting caught” (P#8, F22).
“But on that level if there is only one skid pulled and they’re [the police] not there to witness it and you’re there with a big bunch of associated hoons, they can’t really fine anyone in particular” (P#5, F22).
Participants discussed how being “smart” about where they choose to engage in hooning behaviours and “organised” in alerting others to potential police presence affected the chances of being caught:
“It depends on how smart you are I guess” (P#1, M, age not specified).
“I think it’s just very dependent on the area you are in, what you are doing, what you are driving, as to whether or not you are going to get done” (P#12, M29).
“I think if you’re racing up any main street where there’s traffic you will get caught. I am 25 and I haven’t been caught for street racing. It’s just time and place and organisation. I think it’s stupid to go up a main street” (P#13, M25).
“With CB radios and texting, everyone scatters now, so the chance of you getting caught is pretty slim” (P#14, M22).
“If it’s an organised event, usually, you won’t get caught, depending on who shows up” (P#10, M, age not specified).
One participant also discussed how once you had been caught for two hooning offences, the likelihood of being caught for a third offence and losing your vehicle permanently increased:
“Well the problem I see with that one is that once you’ve lost your car twice the police know your vehicle and they’ll be looking for you and keeping an eye on you so yeah, you wouldn’t have to step out of line very far at all to lose it” (P#6, M37).
In summary, participants generally felt that the likelihood of being caught depended upon the individual driver involved and the circumstances:
“It depends who you are, what you are driving and how old you are” (P#2, M45). 78 Hooning behaviours
3.3.3.3 Perceptions of sanction severity
Participants’ perceptions of the severity of the penalty depended on the length of the impoundment period and the circumstances of the offence. Generally, the perceived severity of the initial 48 hour impoundment period was not high:
“I don’t think it’s too bad” (P#8, F22).
“I think the 48 hour period is a good starting point, shows that they’re serious” (P#5, F22).
“It would depend how heavy the offence was too, whether you would be too upset about it. If you genuinely felt you deserved it then I guess I would be okay with it if I was doing something stupid like putting other people’s life in danger” (P#15, M19).
However, some participants did seem to perceive even the 48 hour period as quite severe:
“It’s severe, I tell you now, because I don’t want it” (P#4, M19).
One participant was very concerned about who had access to his vehicle during the impoundment period, and indicated that he would prefer for his vehicle to be immobilised in his garage so he could be certain it would remain in good condition:
“Where is your car in the 48 hours? If they grab your young one or something like that, or grabbed the missus and stored them for 48 hours, what are you going to do? Some people treat their car like their missus. It’s the same thing mate. I’m sleeping in that [the car]. My missus ain’t worth that much” (P#3, M30).
Another participant perceived any length of vehicle impoundment to be overly severe for a hooning offence, describing the penalty as follows:
“Two or three spins of a wheel, and that’s it, you walk, you lose your assets. To me, that’s just appalling. It’s legislatively enforced unlawful behaviour” (P#2, M45).
The three month impoundment period for a second hooning offence within three years was perceived as being far more severe: Hooning behaviours 79
“That’s pretty severe” (P#10, M, age not specified).
“Three months is a bit tough” (P#8, F22).
“The second offence is way severe. You’ll just be like ‘Oh crap!’” (P#5, F22).
“For the second offence I think three months would be a long time. It’s a bit harsh I’d say” (P#16, M20).
Participants discussed how losing their vehicle for three months had the potential to cause significant disruption to their daily lives, possibly leading to job loss:
“If that’s your only mode of transport to get to and from work, to get anywhere that you need to go, you could end up losing your job or God only knows what else” (P#12, M29).
“Three months is devastating. It could ruin you. You risk losing your job. Won’t be able to get to work. Three months is pretty bad” (P#13, M25).
“I would find that an extreme inconvenience and I would be very sad. It would make me think twice about doing it again, that’s for sure” (P#7, M20).
Some participants discussed the possibility that the three month impoundment period could actually make the problem worse if drivers tried to evade police:
“Three months is a decent stint isn’t it? Could create people running. For three months, losing your car, it’s going to cause so much more problems. It’s going to push everybody more underground” (P#14, M22).
“Probably make me run, knowing what my car is capable of. Assuming they don’t have my number plates yet” (P#13, M25).
One participant discussed how the wealth of the individual related to how the penalty would affect them:
“It only affects you if you have your life tied up in the car. Then it really affects you. So that’s a major effect. But if you don’t, then it’s of no consequence. So if it is a cheap car or if you are wealthy and you have the ability to say, ‘Oh well, let’s pull something else out of the garage’, you know, it’s no issue” (P#2, M45).
When discussing their perceptions of the severity of vehicle forfeiture, 80 Hooning behaviours
participants unanimously agreed that this penalty was extremely severe:
“It would be like taking away your legs, wouldn’t it?” (P#7, M20).
“I think it’ll make a lot of people unhappy. Any property that you knew you worked on, done anything to put together. Especially if it’s something you have dreamt about, finally grabbed and the next minute someone in a blue uniform decides to come along with a tow truck and take it away – that would be very hard” (P#3, M30).
There was also further discussion of willingness to flee from police in order to avoid losing their vehicles:
“You wouldn’t pull up. If you were on your third [strike] and you got pulled up for a hooning offence there is no way in hell I would pull up” (P#1, M, age not specified).
“I won’t pull up” (P#17, M, age not specified).
“I think if people think they are going to get their car taken away from them for good, they [the police] are going to find a lot of people, they are going to keep on running. They are not going to stop the third time. It’s going to lead to deaths and so forth. They really need to take that into account” (P#11, M23).
While it is possible that these comments were not a true indication of future behaviour but rather reflected an element of bravado, many participants qualified their statements with considered justifications for fleeing from police:
“I think it gives people more reason to run as well. I mean, myself, having spent a lot of money on my car, if I ever do get to that point where I am going to lose my car, third time, third strike, I am going to lose it forever. Say I spent about $40,000 on my car – is it a $40,000 fine for having a race down the highway? To me, that’s worth running. I mean, you have given me $40,000 to run from the cops. That’s good enough reason for me to run and kill myself or the people chasing me or someone else on the road. Whereas if I knew it was the same as the first time I got done, $300, lose my licence, something like that, you’d stop. Stop. It’s not worth dying over. Forty grand might be, for a lot of young people” (P#13, M25).
3.3.4 Social learning theory
The next series of issues discussed by participants related to the components Hooning behaviours 81 of social learning theory: differential association; imitation; differential reinforcement; and definitions. However, as there had been lengthy discussions regarding friends and acquaintances and their behaviour, and all focus groups contained members of friendship groups, the imitation question “Do you have any friends who engage in hooning behaviours?” was not asked.
3.3.4.1 Differential association
Based on previous research that found that the influence of family and friends differs (e.g., Fleiter, Watson, Lennon, & Lewis, 2006), the attitudes and beliefs of significant others was explored separately for family and then friends. Participants generally discussed this aspect in terms of approval, and reported that their family, particularly their mothers, would disapprove of hooning:
“Disapprove. She [my mother] would flip out” (P#7, M20).
“My mother definitely disapproves of it but has realised there’s nothing she can do about it” (P#18, M22). “Mothers are mothers” (P#2, M45).
“I wouldn’t tell them I went out and raced somebody” (P#8, F22). “Yeah I don’t think a lot of the people who do hooning actions go home and tell their parents” (P#5, F22).
Many participants reported that while their parents (particularly fathers) may have engaged in similar driving behaviours when they were young, they may still disapprove of hooning, depending upon the situation:
“My old man tries to tell me that it’s wrong and that, but he’s a hypocrite because he used to do it too” (P#1, M, age not specified).
“My father… he approves more than disapproves, but at the same time he doesn’t really say out loud. He was the same as me when he was younger. He’s told me plenty of stories with him and his mates going out, doing all the same kind of stuff that I’ve done” (P#18, M22).
“Dad’s into cars as well so he’d do little bits [of hooning] and I know lots of stories of him when he was younger doing things so it wouldn’t worry him so much. But in the wrong situation he would definitely disapprove, like around people and main streets” (P#16, M20). “Yeah my Dad would categorise it. He’d be like ‘If you do it out here it’s alright but if you do it here I’ll give you the biggest backhand you’ve ever seen’” (P#7, M20). 82 Hooning behaviours
Friends were described as generally approving of hooning behaviours, even encouraging it, mainly because participants had developed a circle of friends who shared their interest in cars:
“Most friends approve only because they’re friends by association” (P#10, M, age not specified).
“Definitely approve – I am in the same circle” (P#18, M22).
“They all approve” (P#17, M, age not specified).
“Oh for sure, peer pressure. They’re like ‘Go on – race him!’” (P#7, M20).
“They encourage us to go fast. It’s just our culture, that all of our friends are used to. It’s just the way we’ve grown up and what we do every day” (P#8, F22).
However, some participants mentioned having friends who disapproved of hooning, and the importance of respecting their wishes when travelling together:
“I’ve got some friends that will not be associated with it and they’ll be like ‘If you’re going out here I don’t want to come’. They’ll be happy to come for a cruise… but once the shops close and everyone goes home to bed and that’s when all the hooning starts they’ll go ‘Nah, drop me off’. I think in our sort of environment and society most people are happy to let someone out of their car. It doesn’t make you any less cool or any less of a hoon to get out of a car and say ‘Nah I don’t want to be in it purely because I don’t feel like dying right now’” (P#5, F22).
Finally, participants also discussed how the approval of their family and friends would also be contingent upon the type of hooning behaviour they were engaging in:
“Definitely a race would be frowned upon a lot more than a burn out” (P#7, M20).
“My mum wouldn’t approve of me going very fast” (P#8, F22).
“My parents wouldn’t approve of me racing because we have a legit area here to do it” (P#5, F22).
3.3.4.2 Differential reinforcement
Due to time constraints, participants were not directly asked what positive Hooning behaviours 83 and negative consequences of hooning behaviours might be, just on balance whether they thought more good or bad consequences would arise from hooning. However, examples of consequences were also offered in response to this question. Most participants indicated that there were far more negative consequences for hooning than positive:
“Good ones: You get a bit of a rush; a bit of an ego up, if you keep winning. Bad ones, you know, for people who do stupid things: kill people; kill yourself; damage property; lose your vehicle. You know, there’s so many more negatives to it” (P#10, M, age not specified).
One participant even stated:
“Nothing really good comes out of it” (P#13, M25).
The most commonly mentioned negative consequences related to damaging the vehicle, such as the following exchange:
“Definitely more bad things that could happen” (P#7, M20).
“Yeah, like you can break your diff, that’s bad” (P#6, M37).
“Yeah, it’s not just the police after you, it’s damaging your car as well. Don’t wanna be pushing your car home” (P#7, M20).
“Or like smashing your car into a telegraph pole or something like that. It’s just going to suck” (P#19, M20).
“Yeah, when you stack your car into the tree and you’re like ‘Oh geez, that was a good burn out’. You’d be kicking your car going ‘Ahh – Why is it all broken?’” (P#7, M20).
“If parts break then it’s bad” (P#11, M23).
Other negative consequences discussed included harm to themselves and others:
“None of the good stuff could even compare to killing somebody. Like none of it is worth it” (P#16, M20).
“A lot of people have died in the last year or so” (P#8, F22).
The economic and occupational ramifications of losing their vehicle if caught hooning were mentioned in the following exchange: 84 Hooning behaviours
“Lose your job, lose your vehicle” (P#10, M, age not specified).
“Money” (P#13, M25).
“That’s what makes it even more exciting” (P#14, M22).
Positive consequences of hooning were generally related to the thrill or adrenaline rush experienced when performing a driving manoeuvre, either because of the skill involved, or the illegality of their behaviour, as discussed in the following exchange:
“Adrenalin rush” (P#15, M19).
“See, if they made it all legal, we really wouldn’t do it, you know what I mean? Like, you would lose your rush. The rush is a lot of the big thing. You are going out and you are doing something wrong” (P#14, M22).
“I get a lot more rush in the street” (P#4, M19).
“I like a rush, nothing more than driving from here to there, and having a really nice exotic car pull up beside me with no one else on the road. And give ‘em the nod – he’s got a good car, you’ve got a nice car and you both go for it. That’s where the rush comes from. But other than that, nothing else comes good of it” (P#13, M25).
Another positive consequence was the praise (or even perceived praise) of others who witnessed your driving:
“… you slide your car out sideways and everyone is just there looking and watching ya. You sort of get a head swell from things like that” (P#6, M37).
3.3.4.3 Definitions
When discussing their personal attitudes towards hooning behaviours, all participants agreed there was “a time and a place” for hooning behaviours, and approved of engaging in hooning behaviours when they had minimised risk. Most comments, after some version of this initial statement, related to justifying their involvement by describing situations in which they did not approve of hooning:
“I wouldn’t do it in town and I wouldn’t do it in front of the general public” (P#8, F22). Hooning behaviours 85
It’s not like we’re going into our school zones and like arcing it up. I’ve seen people hooning in the wet with three kids in the back. That is not on. The day that I have a kid, the kid will not be in the car when I do anything silly, will not be in anyone’s car, will not be near anyone’s car when they’re doing something silly because we’re responsible for ourselves and a child is not old enough to step up and say ‘Let me out of the car while we’re doing this’” (P#5, F22).
That’s what it comes down to – time and place. You are a hoon if you do stupid things when people are around, your family, there are things to lose. If you are organised, you are not a hoon. You have actually organised an enthusiast event” (P#10, M, age not specified).
“I approve of burn outs out in the bush, and even drifting around the bush to a certain extent, as long as it’s not blind corners and stuff like that. Yeah, I’d approve if there are no passengers in the car, just doing it yourself you’re only going to hurt yourself, and then go to a place where it’s only you” (P#7, M20).
Finally, the following exchange is an example of how participants compared risk to themselves and others, and used potential harm to other road users to define when hooning was acceptable:
“It’s like when everyone talks about racing up and down the highway it’s like ‘Yeah, that’s all great, I’m glad you had fun, But the family in the station wagon you hit wasn’t expecting you’” (P#19, M20).
“Yeah with six kids in the back” (P#7, M20).
“And the baby and everything. It’s going to be a different story for them” (P#19, M20).
3.3.5 Influence of others
As noted in Table 3.1, participants were asked questions relating to the influence of others on their decisions to engage in hooning behaviours. Responses to the first question about the likelihood of engaging in hooning behaviours when alone or in a group were very mixed, with some participants indicating they were likely to engage in hooning behaviours both alone and when with a group, and others indicating that hooning was more likely to occur in groups:
“I would definitely do it with other people more” (P#8, F22). 86 Hooning behaviours
“We go in groups. Like this guy said ‘I’ll teach you how to do a skid’. We were all sitting there watching and it was sort of like a lesson and everybody was cheering and it was good for him because his self esteem went through the roof because we were like ‘Yay! Hooray for you!’ (P#5, F22).
“I’d say more with a group of mates. As much as I hate to admit, you do show off sometimes” (P#15, M19).
“I wouldn’t jump in my car and go out looking for a race. You would meet up with a few people first and then you would organise to go out. No, I wouldn’t do things on my own. Always need someone to start the race” (P#10, M, age not specified).
One of the reasons offered for preferring to engage in hooning alone was to avoid embarrassment:
“You go out by yourself and have a practice before you do it in front of anyone else so you don’t look like a stooge if you mess it up” (P#1, M, age not specified).
Further, some participants expressed concerned about the possibility of harming others, and so would try new or risky things alone:
“Well when there are people with me I’m probably more of a stick in the mud because yeah I don’t like to take... I do take responsibility for who is in my vehicle with me and I just couldn’t... wouldn’t want to know that I had hurt my mates because I was being a dickhead. You know I couldn’t do that so I like to think that yeah, I, in a vehicle by myself, can do all sorts of things but I think when you’ve got a person on the back of the back or in the car then their safety is more important” (P#6, M37).
“I’d say if I was by myself I push a bit harder. Because I’m the only one I’ve got to focus on, there is no group to be aware of or other vehicles as a distraction” (P#20, M24). “Not going to hurt anyone” (P#1, M, age not specified).
However some participants had interesting perspectives on the role of friends in reducing risk:
“If something happens, you end up skidding down the hill or something, at least someone sees you go down there. Whereas if you’re driving by yourself, you do that and might be there for another five hours. So I might go a little bit more out there when people are around me. If you are by yourself, then no one is there to save you if something happens” (P#11, M23). Hooning behaviours 87
“Someone to tell you when enough is enough” (P#13, M25).
A number of factors about the group they associated with that encouraged them to engage in hooning behaviours were discussed, including competition, testosterone, adrenaline, peer pressure, and boredom or entertainment:
“You can do it by yourself but it gets boring. It’s more fun when there are people there to have a play with them” (P#1, M, age not specified).
“It’s probably a testosterone thing. It’s all fun and games until the cops show up” (P#2, M45).
“It’s the fact of being better than your mates. There’s always a pecking order – you are the man to beat. It’s an ego thing, really” (P#10, M, age not specified).
Participants agreed that continuing to be part of the group of friends with whom they engaged in hooning behaviours was important to them, although most indicated that they were confident that they would continue to be friends regardless of whether they continued to race or perform skids. One participant also described how a common interest in cars can facilitate establishing new friendships:
“Some people join the car forums when they move to a new town and that is their only way to make friends. Once you’re out of school you’re out of that easy environment to make friends. We all have a common interest, and it’s a starting point to have a conversation with someone” (P#5, F22).
3.3.6 Thrill-seeking
Participants had mentioned the thrill and adrenaline rush they experienced when engaging in hooning behaviours in response to previous questions (i.e., as an example of a non-social reward in the differential reinforcement component of social learning theory), but reinforced that this thrill and enjoyment was the main reason they participated when asked if they get a thrill out of hooning:
“It’s because we enjoy it. It’s the same reason someone watches the footy, it’s because they enjoy it. It’s even enjoying to watch it, it’s enjoyable to hear about it, it’s enjoyable to be a part of it” (P#5, F22).
“It’s a mad adrenaline rush” (P#8, F22).
“That’s the only reason you do it” (P#13, M25). 88 Hooning behaviours
Differences in the rush associated with the different types of hooning behaviours and associated car-centred activities were also discussed in the following exchange:
“Burn outs has got its crowd, drifting has got its crowd, and racing has got its crowd. Different rushes. I get more of a rush if I am going out for a slide, and I don’t hit a gutter and total my car, and I drive home. That’s the rush that you get. You know, to pull something off is cool, too. But racing, you get the rush from winning. Even spectators get a rush, though” (P#10, M, age not specified).
“It’s building the cars as well. We love to build them. That’s why we put our money into them, build them and modify them. Take them out and see the end product of what you have built” (P#13, M25).
3.3.7 Queensland’s vehicle impoundment laws for hooning offences
Participants discussed their overall opinion of the legislation, and how they perceived other people felt about it. To address research question 5 regarding the effectiveness of vehicle impoundment laws for hooning, they were asked how they or others had changed their behaviour in response to its implementation, and their general views on how it was being managed and any alternatives they saw that could reduce hooning behaviour. Not surprisingly, participants were not positive when giving their overall opinion of the legislation:
“It’s shit” (P#4, M19).
“Stupidity” (P#10, M, age not specified).
“Queensland Government suck, that’s all” (P#3, M30).
“It’s immoral” (P#2, M45).
When asked about what they perceived other people thought, they indicated that others were either very pleased about hoons or hooning being targeted, or that they had no opinion about the legislation at all as it did not affect them:
“The elderly, the media, the government – they love it. That’s what I think. The Police love it. Anyone that owns a modified vehicle thinks it’s stupid” (P#10, M, age not specified). Hooning behaviours 89
“I think older people are rejoicing about it” (P#7, M20).
“There is a shift to the political right, though, the sort of John Laws types, who are laughing at this legislation” (P#2, M45).
“Other people, it doesn’t concern them. If they think it’s going to get hoons off the streets, then of course they would agree with it. If I thought it was going to get hoons off the streets, I would agree with it” (P#13, M25). “It doesn’t get them off the streets” (P#10, M, age not specified). “It’s not going to get the right people off the streets” (P#13, M25) “Still got 17 year olds out there with Mum and Dad’s car” (P#4, M19).
Participants discussed that some people may still be unaware of the legislation, and only knew about it if they or someone they knew had been penalised, as in the following exchange:
“You only get told about it when you get busted. It’s like a rare disease – you wouldn’t know about it unless one of yours friends had it” (P#8, F22).
“Yeah I don’t think many people do know about it. They would have a general knowledge of what is and isn’t illegal but the finer points? I don’t think they know jack. Unless someone you know has had it happen to them, you don’t really know” (P#5, F22).
However, once someone was punished, word spread quickly throughout the network:
“When the impounding law first came in I think that was a bit exciting because when the first car was seen on a trailer everyone in the town knew about it… everyone knows everything in this town anyway” (P#5, F22).
They suggested that information, such as a pamphlet regarding rules and regulations associated with vehicle modifications and hooning behaviours, should be provided at licensing to better inform young drivers of the consequences of hooning:
“There should be more about it in the learning booklets and stuff. Rather than just saying ‘You need to give way to the right’ and this and that, they need to have more included in that education. So when you sit to take your Leaner’s [test], it [the consequences of hooning] is a known. They need to have what the consequences actually are included in those booklets or even information nights, where you aren’t going to be scared to go there, drive your car there.” (P#13, M25).
Another suggestion discussed was for the legislation to have graded penalties 90 Hooning behaviours
based on where the hooning behaviour occurred and the associated level of risk:
“There’s tougher penalties for people speeding in a school zone. Should there be tougher penalties for people hooning in suburbia or main roads? As opposed to out the back of the middle of nowhere where there’s less risk? There’s no families and things like that, and they’ve obviously gone out of the way, they’ve made an effort to take it off the main streets. They can hurt no one but themselves” (P#13, M25).
Participants in one of the focus groups unanimously agreed that in their experience the legislation was being applied inconsistently, and they shared anecdotes of different outcomes depending upon which police officer they encountered. They also spoke of friends who had received different penalties for what they saw as the same offence. They spoke about how these inconsistencies lead to feelings of resentment:
“If you get caught you’d probably have greater resentment against the cops” (P#20, M24).
“Just resenting the police more. Yeah the police state we’re living in, it’s just getting too much” (P#6, M37).
“I think they need to be more consistent and not more lenient with a certain sex than others. If they’re going to take a hard approach they need to take a hard approach with everyone, regardless of whether it’s a 40 year old woman with her shopping in the back, or a 17 year old kid who just got his licence and is in his Mum and Dad’s Camry” (P#9, F23).
“It just needs to be fair and consistent” (P#8, F22).
One group also discussed how if you were to think about vehicle forfeiture in terms of monetary value like a fine (i.e., the value of the vehicle), there were gross inconsistencies in penalties depending upon the person’s vehicle:
“How can someone get a $500 fine and I get a $40,000 fine? And committed the same crime as me? That’s not fair” (P#13, M25).
Most participants indicated that the legislation had not resulted in substantial changes in their behaviour, other than changes made to decrease the likelihood of attracting police attention:
“I don’t think the laws have changed anything” (P#8, F22). Hooning behaviours 91
“I’m more careful where I do it now” (P#21, M, age not specified).
“You just get smarter” (P#13, M25). “Just go to different areas now – that’s all it is. We just changed the spot” (P#14, M22). “Just taking it to different areas, more organisation, and basically getting rid of the younger followers. All the hangers-on that want to watch you race” (P#13, M25).
“You’ve just gotta be smarter about it. They haven’t changed the actual activity, we’ve just gotten smarter about it” (P#1, M, age not specified).
“I’ve changed my car to look more standard and I haven’t gotten any problems from them [the police] because the last thing I want is to be pulled up by them. The less likely my car is to be picked out of a crowd just on pure looks, the better. Just to keep me away from them and all this legislation” (P#20, M24).
“It has worked in some ways. Like, you used to be able to go out. You would have 50 or 60 cars out almost every night of the week, especially on school holidays and stuff, even if they weren’t modified. These days, people are too scared to bring their cars out” (P#10, M, age not specified).
“I never really did it in the main streets anyway, what’s made me go further out is that they keep building more and more houses so you have to keep going further and further” (P#7, M20).
However, some indicated that with the threat of losing their vehicles, the legislation may have had a negative impact on road safety:
“I think the taking of the cars after the third strike is absolutely ridiculous and they are going to lose lives over it” (P#2, M45).
“If they start crushing cars like in the States, you’re going to see a lot more accidents, a lot more deaths. No one is going to stop, whether they’ve got your plates or not. No one is going to stop” (P#4, M19).
3.3.8 Other issues
When asked if they had any final comments they had not had the opportunity to make throughout the discussion, one participant commented on the visibility of youth and the community response to hooning:
“With young people, I don’t now but this is the theory I’ve got: You look at past generations, you know our parents and grandparents, and they’ve had worldwide conflicts. Young fellas had to jump in fighter planes and stuff like 92 Hooning behaviours
that and they relied on that sort of wild streak in people to do their job. There was World War II, Vietnam, Korea. Our generation doesn’t have such a heavy demand on us, and we’re now more in the public eye with this sort of behaviour and taking the risks and the chances that way” (P#20, M24).
Another talked about the notion that hooning behaviours are not new, and that previous generations of young people have engaged in similar behaviours. He suggested that the hooning laws reflect the views of the Baby Boomer generation:
“This law has been applied to the future of Australia in terms of this generation. I just think it’s totally inappropriate. What I don’t understand is that we’ve had a continual decline in our road toll, in terms of the proportion of our population, since 1973. So I don’t understand why we need it, you know. I think it’s this generation, this Baby Boomer generation, were quite happy to kill each other and everybody else on the road in the 70s, when our road toll was proportionately 10 times what it is now. But now they’re worried that they might be impinged upon in some way by this behaviour, which they themselves – it was integral to their youth. That’s the only thing I put it down to” (P#2, M45).
Others talked about hooning as part of the car culture, and an area for them to excel:
“It’s ingrained in our culture. We are brought up with that at school. You have to be the fastest; you have to be the best at something. With our sporting stars, you have to be the fastest runner or something. It’s the same with us – who has the fastest car” (P#14, M22).
Participants also discussed their perceptions of risk associated with hooning behaviours compared to other traffic offences:
“A lot of accidents are caused by drinking. Someone speeding or drunk is a lot worse than what we’re doing. I reckon if you saw the statistics maybe, I reckon crashes from speeding and crashing from drink driving or under the influence of other drugs, it might be a lot higher [than hooning]. So who’s really the worst one on the road?” (P#14, M22).
3.4 Discussion
The overall aims of Study 1a were to obtain a better understanding of hooning from the drivers’ perspective; which would provide a foundation for the Hooning behaviours 93 program of research by identifying avenues of investigation and inform the interpretation of data collected in Studies 2 and 3, and inform the development of the questionnaire for Study 1b.
3.4.1 Status of research questions
As it was not the purpose of this study to test specific hypotheses, and the sample size was small, it is acknowledged that the discussion of the status of research questions in this section is tentative. The first research question regarding who engages in hooning was not directly addressed, although on the basis of the participants who volunteered to participate in this study, it does appear that consistent with the research described in section 2.2, it is primarily young males who engage in hooning. Other than the female participants at the focus groups, there was little mention of women, and the majority of comments related to young people. Further, the results of this study suggest that drivers who engage in hooning behaviour do not represent a homogenous group, as a number of potential sub-groups of drivers were discussed. This finding is consistent with previous hooning research conducted in Queensland (Armstrong & Steinhardt, 2006). The heterogeneity of the “involved” driver is important for researchers, law enforcement and policy makers, as it is possible that these groups have differing motivations for engaging in the behaviour, and may also respond differently to interventions designed to prevent hooning or punish offenders. A better understanding of these distinct groups in future research specifically examining this issue can inform the development of a number of targeted interventions and enhance their effectiveness. Regarding the second research question, a number of factors contributing to hooning behaviour were identified, with thrill and enjoyment representing the main reason participants continue to engage in hooning behaviour despite the risks of severe penalties, and risks to their safety and that of others. It was interesting that participants discussed a large number of potential negative consequences that could arise from hooning, but very few positive rewards, specifically thrill or enjoyment, and the competition. This finding suggests that people assign different weights to the potential consequences of hooning, although how these weights are derived remains unclear. It is possible that they are a complex function of the perceived likelihood of 94 Hooning behaviours
the outcome occurring, previous experience with that outcome, and their attitudes towards that particular outcome. For example, while crashing or even killing someone was unanimously agreed to be the worst possible outcome of hooning, and considered possible, it may also be considered rare and unlikely to occur, as opposed to thrill and enjoyment, which participants reported always experiencing. The third research question regarding the road safety implications was addressed by a question about hooning contributing to crashes on the brief demographic survey. One fifth of the participants who had been involved in at least one crash as a driver indicated that one of their crashes involved hooning. These crashes did not come up in the focus group discussions. Rather, references to vehicle damage as a result of hooning were generally hypothetical. Participant responses to the brief demographic and driving history survey, and focus group discussions suggest that drivers who engage in hooning behaviours also engage in other risky driving behaviours (RQ4). Participants openly discussed their experiences with police, and many mentioned speeding offences and drink driving convictions. This finding may suggest that drivers who engage in hooning can be considered generally risky drivers, with hooning representing only one group of potentially dangerous driving behaviour they engage in. It may also suggest that drivers who engage in hooning are not likely to comply with traffic laws. Recent research exploring the relationship between personality and hooning behaviours that involve loss of traction with the road surface (e.g., burn outs) found that drivers who self-reported engaging in these behaviours scored significantly lower on the agreeableness factor than drivers who did not report hooning (Thake, 2009). Finally, participant responses to questions related to the fifth research question suggest that drivers who engage in hooning, not surprisingly, do not support Queensland’s vehicle impoundment and forfeiture laws for hooning and think they are an overreaction, and open to misuse by police. In terms of the effects these laws have had on their own behaviour, and their perceptions of the effects on others’ behaviour, comments indicated that the main change in behaviour had been to push the behaviour underground, rather than reducing or eliminating it. Thus from the perspective of these participants, the effect of the legislation has been one of displacement rather than a deterrent. Participant responses to questions relating to these research questions are discussed in more detail in sections 3.4.2 and 3.4.3. Hooning behaviours 95
3.4.2 Implications for Study 1b
3.4.2.1 Sampling issues
The desired sample size for this study was 20 to 25 drivers who drive in Queensland and engage in hooning behaviours as defined by Queensland legislation. Calling for participants via a media release and snowballing resulted in an adequate sample of 22 participants, and after four focus groups it was determined that saturation (Morgan, 1998a) was reached. Some people who contacted the researcher declined to participate in focus groups, but asked to be contacted when data were being collected for the quantitative phase of the study. However, as 250 – 300 drivers were required for the quantitative phase, and the recruitment method yielded only 22 focus group participants, using this method to recruit participants for the quantitative phase was unlikely to be successful, and alternative recruitment methods were required for Study 1b. One of the people who contacted the researcher via email in response to a media story about the research included a link to an online community forum, where the research was discussed before and after the focus group had occurred in that area. Prior to the focus group occurring, there was detailed discussion about the possibility that this study was really a covert police operation, and that anyone who attended was “an idiot” as the Police would “just round everybody up”. However, after the focus group, a participant posted a lengthy message about their positive experience the evening before, dispelling those concerns. This occurrence suggested that the concern of police prosecution resulting from participation in the research should be dealt with in the project information sheet and / or call for participants in the quantitative phase of this study.
3.4.2.2 Question wording
The most significant issue with regards to wording of the questions in this study was that the use of the term “Queensland’s anti-hooning legislation” resulted in responses relating to excessive speeding and vehicle defect offences, in addition to the hooning behaviours of interest in this research. The researcher clarified the scope of the questions in focus groups, but participant responses highlighted the importance 96 Hooning behaviours
of being clear and specific in the wording of questions in the quantitative phase of the research. A common response to many of the questions in the focus groups was “it depends”. As noted in section 3.3, participants had markedly different views and opinions on issues depending on the situational context, and repeatedly emphasised the importance of distinctions between various scenarios. This finding suggests that general questions, as used in this study, would not be appropriate in the quantitative phase, and the contexts discussed during focus groups should be incorporated into context-specific versions of questions. In terms of the behaviours considered hooning under Queensland legislation, participants often differentiated between racing and doing “burn outs and stuff”. Time trials, grouped with illegal street racing in the legislation, were rarely discussed. This finding may suggest that time trials are a rare activity among this group compared with the other prescribed hooning behaviours, or that the attention of drivers who regularly perform time trials was not attracted by the media coverage generated by the release. Many of the responses to the question designed to address the differential association component of social learning theory were answered in terms of the participants’ perceptions of their family and friends’ approval of their own behaviour, rather than their perceptions of their general attitudes and beliefs about hooning behaviour. Thus, there was some blurring between this construct and the differential reinforcement component of the theory, where perceived approval or disapproval are types of social rewards or punishments. Therefore, there is a need to be clear in the wording of questions in Study 1b about whether the question relates to the behaviour in general, or the respondent’s behaviour.
3.4.2.3 Relationships among variables of interest
An important consideration is the possibility of significant correlations between variables of interest, and how these will affect the structure and interpretation of statistical analyses in Study 1b. In addition to the potential overlap between responses to the differential association and differential reinforcement questions discussed in section 3.4.2.2, there may also be some overlap in responses to the social learning and influence of others questions. For example, preference for Hooning behaviours 97 engaging in hooning behaviours as part of a group may reflect the influence of others and / or an example of a social reward (differential reinforcement). Further, as the thrill associated with hooning can be considered a non-social reward, it is not clear whether the general trait of sensation seeking (i.e., not specifically limited to the thrill associated with hooning) will explain any additional variance over and above that already explained by the non-social rewards in the differential reinforcement component of social learning theory. Checking for multicollinearity is not only an important statistical assumption of multiple regression analyses, but is also imperative for understanding the various rewards and punishments that facilitate the initiation and maintenance of hooning behaviours.
3.4.2.4 Explanatory utility of study variables
Although only preliminary due to the small sample size, the results of this phase of Study 1 have informed the development of hypotheses for the quantitative phase. For example, according to classical deterrence theory, participant responses suggest that they should be unlikely to engage in hooning behaviours, as they perceived that the likelihood of being detected was high, and that if detected the penalty was severe (particularly for second and third offences). However, participants discussed engaging in hooning behaviours frequently and intended to continue doing so. It is important to note that there were marked differences in perceptions of severity for the different impoundment periods, where participants perceived the 3 month and vehicle forfeiture penalties to be far more severe than the initial 48 hour impoundment period applied for a first hooning offence. Perhaps the model is a poor fit for explaining first-time hooning behaviour, as the penalty for this initial offence does not reach a sufficient threshold of severity to effectively deter hooning behaviour and it, therefore, has limited general deterrent effect. However, as participants did perceive the impoundment periods for second and third offences to be extremely severe, it is possible that the classical model would be a better fit for understanding the hooning behaviour of these “repeat” offenders. Further, perhaps the 48 hour impoundment period does have a specific deterrent effect, as drivers who have experienced it become eligible for the more severe 3 month period and any associated general deterrent effect of this penalty. Looking to the expanded model of deterrence, the group had far more 98 Hooning behaviours
experience avoiding punishment than experiencing it directly or indirectly; thus, it is possible that the experience of punishment avoidance is having a disproportionate effect on their hooning behaviour, highlighting the utility of Stafford and Warr’s (1993) model. Thus, it may be that the expanded deterrence variables, as a group, predict a significant amount of variability in hooning behaviour in the quantitative phase of this study, and of these variables, it is likely that punishment avoidance will be the most important component, explaining the most variance in hooning behaviour. Similarly, responses to some of the social learning theory variables were also counterintuitive. While it was expected that participants would have a number of friends who engage in hooning behaviours (imitation), some of their responses to other aspects of the theory were not consistent with the model, and again suggest that some components must be more important in explaining variance in hooning behaviours than others. For example, participants indicated that their family (particularly their mothers) did not approve of hooning, but reported that their friends generally supported the behaviour (differential association and / or differential reinforcement). It may be that friends are a more important influence on their driving behaviour than their parents, which is consistent with previous speeding research (Fleiter et al., 2006), and may also reflect a developmental issue related to age. In terms of differential reinforcement, participants reported several negative consequences of hooning behaviour, but could only suggest thrill and enjoyment as positive outcomes. For this component of social learning theory to be a significant predictor of hooning behaviour, the thrill and enjoyment associated with hooning must be a stronger influence than the many potential negative consequences. This tendency may be due to experiencing these positive outcomes each time they engage in the behaviour, as opposed to the negative consequences that may have only been experienced rarely, vicariously, or never. Finally, participants’ personal attitudes towards hooning behaviour were not completely positive. Most described their own behaviour as acceptable, and described how they ensured the safety of themselves and others, but went on to describe a number of contexts in which hooning by others was unacceptable. Hooning behaviours 99
3.4.3 Implications for Studies 2 and 3
A number of issues arose during focus group discussions that can be explored further in official offence and crash data in Studies 2 and 3 of this program of research. For example, the apparent importance of punishment avoidance in understanding hooning behaviour may be relevant in Study 3 when interpreting the post-impoundment driving behaviour of the offender sample. Any reduction (or absence) in offending may be due to an effective specific deterrent effect of the sanction. However, based on participants’ comments regarding punishment avoidance and how they have changed their driving in response to the legislation in this study, this finding may actually be indicative of a change or relocation of behaviour (displacement) to avoid detection, rather than a true reduction or elimination of hooning behaviour (deterrence).
3.4.4 Strengths and limitations
The major strength of this study was the use of a qualitative methodology. While the results of a study with a small sample size of 22 drivers may not be generalisable to the population of drivers who engage in hooning behaviours, the qualitative approach elicited rich information that resulted in an in-depth understanding of hooning behaviour from the drivers’ perspective. Further, the focus group discussions allowed the research to veer into unforseen areas in response to participants’ comments which is not possible in quantitative research. To the best of the author’s knowledge, this study is the first of its kind, and has resulted in a rich body of information about a variety of issues relating to vehicle impoundment legislation as applied to hooning offences that may have practical implications for government agencies responsible for managing this type of legislation. Second, this study was strengthened by the use of a multidisciplinary approach to exploring hooning behaviours. Participant responses in this study have informed the operationalisation of the quantitative instrument for Study 1b, and prompted additional avenues of investigation in Studies 2 and 3. Third, the results of this study can be used to complement the quantitative analyses of the program of research and give added meaning to those results. Participants in this study spoke openly about their experiences and driving 100 Hooning behaviours
activities, including illegal activities, which may suggest that they have been open and honest in their responses and confidence can be placed in these data. Further, the type of data required in this study cannot be obtained from official or objective sources. In addition to the small sample size, it is not clear whether another limitation of this study was the inability to determine the representativeness of the sample. This possibility was unable to be assessed, as there are no data about the population of drivers who engage in hooning behaviours. However, the age and gender characteristics of the sample in this study are similar to those of the offenders reported in Studies 2 and 3, although other key variables that would be useful to compare in order to assess representativeness (e.g., motivations, attitudes, personality) were not available. Further, it is unknown whether drivers detected and punished for hooning offences are representative of all drivers who engage in these behaviours. Finally, the selection criteria used in this study and (Study 1b described in the following chapter) may have introduced a bias in that only people who had engaged in hooning recently were recruited. In other words, only people who were not sufficiently deterred by the laws were involved in the study. While previous research (Gee Kee, 2006; Thake, 2009) has recruited more broadly and then compared the responses of drivers who do engage in hooning (i.e., not deterred) with those of drivers who do not engage in hooning (i.e., because they either have no interest, or have been sufficiently deterred), that was not the purpose of this research. While the sample in this study and Study 1b may be biased towards drivers who are not deterred from engaging in hooning behaviours, it was this target group of individuals that were of most interest in this research. Further, although all participants reported engaging in hooning recently, there was still variability in the frequency of their behaviour, and intentions regarding future behaviour that allow for the research aims and key research questions to be explored.
3.5 Chapter summary
Study 1a involved focus group discussions with a sample of 22 people who drive in Queensland and engage in behaviours considered hooning under Queensland’s “anti-hooning” legislation. In order to obtain an in-depth Hooning behaviours 101 understanding of hooning from the drivers’ perspective, and inform the development of a quantitative measure for Study 1b with a larger sample from the same population, participants were asked about drivers who engage in hooning behaviours, as well as their opinion of the vehicle impoundment legislation applied to hooning offences. Questions based on expanded deterrence theory, social learning theory, the influence of others and thrill-seeking were also discussed. The discussions highlighted the complexity of hooning behaviours, and the importance of reflecting this complexity in the wording of questions and selection of variables of interest in Study 1b. In addition to informing the quantitative survey instrument, the discussion of expanded deterrence theory variables had particular practical relevance for police, as participants commented on their perceptions of the severity of vehicle impoundment laws, but also how they and their friends have been able to avoid police detection and continue engaging in hooning. In summary, this study provided important insights into hooning behaviours from the drivers’ perspective, and informed a quantitative survey instrument for use in a larger scale study (Study 1b), reported in the following chapter. 102 Hooning behaviours
Hooning behaviours 103
CHAPTER 4: STUDY 1B – FACTORS CONTRIBUTING TO ILLEGAL STREET RACING AND ASSOCIATED “HOONING” BEHAVIOURS (QUANTITATIVE PHASE)
4.1 Introduction
Study 1b extended upon Study 1a by using the focus group findings to inform the development and question wording of a quantitative instrument designed to measure the components of the theoretical perspectives of interest. This chapter describes the development and administration of the quantitative instrument used in Study 1b and the related results. The instrument was designed to address specific hypotheses related to the key research questions of the thesis from the perspective of drivers who engage in hooning on Queensland roads. Study 1b examined all of the key research questions of this program of research.
4.1.1 Hypotheses
Study 1b hypotheses were formulated based upon the review of the relevant literature and participant comments in Study 1a. As such the theoretical framework from which this study was approached included expanded deterrence theory, social learning theory, and driver thrill-seeking perspectives. This section outlines the specific hypotheses addressed in this study by the key research question to which the hypothesis relates.
4.1.1.1 RQ1: Who engages in hooning in an Australian context?
Using a small sample of 22 drivers, Study 1a suggested that drivers involved in hooning behaviours are similar to those involved in illegal street racing in other countries (a sub-set of hooning behaviours in Australia), according to the literature reviewed in section 2.2. It was therefore predicted in this study that:
H1: Drivers involved in hooning will be predominantly young males working in trade professions. 104 Hooning behaviours
4.1.1.2 RQ2: What are the legal, social and psychological factors that contribute to hooning behaviour?
A number of psychological, social and legal factors that potentially contribute to hooning behaviour were discussed in Study 1a. Further, the existing literature reviewed in section 2.3 supported the association of these factors with hooning, or illegal street racing. Based on these findings, it was predicted that:
H2: Scores on expanded deterrence theory variables will be associated with more frequent hooning behaviour and intentions to engage in hooning behaviour in the future; such that scores for punishment experience, perceived likelihood of detection and perceptions of the certainty, severity and swiftness of punishment will be negatively related to hooning behaviour, while punishment avoidance scores will be positively related to hooning behaviour; H3: High scores on the additional5 social learning theory variables6 will be positively associated with more frequent hooning behaviour and intentions to engage in hooning behaviour in the future; and H4: A greater propensity for driver thrill-seeking will be positively associated with more frequent hooning behaviour and intentions to engage in hooning behaviour in the future.
As some of the variance in hooning behaviour these variables explain is likely to be shared, the unique associations between these variables and hooning behaviours were also of interest. These associations were explored using multiple regression analyses. The two key perspectives in the theoretical framework of this research were expanded deterrence theory and social learning theory. As social learning theory incorporates deterrence principles (Akers et al., 1979), expanded deterrence variables were entered first, followed by the remaining social learning variables to test the following hypotheses:
H5: Deterrence theory variables will predict significant variability in hooning behaviour; and
5 As noted in section 2.7.3, Akers argues that deterrence theory can be subsumed within social learning theory. In keeping with this conception, the social learning theory variables were operationalised to be additional to the deterrence variables. 6 Social learning theory variables were scored so that higher scores indicated greater support for hooning behaviours. For example: high differential associations scores indicate that the person perceives that significant others have favourable attitudes towards hooning; high imitation scores indicate that the person has many friends who engage in hooning often; high differential reinforcement scores indicate that the person perceives that more rewards are likely to result from hooning that punishments; and high definitions scores indicate that the person holds positive attitudes towards hooning. Hooning behaviours 105
H6: The additional social learning theory variables will predict significant variability in hooning behaviour over and above expanded deterrence variables.
As Akers (1990) has argued that psychological factors such as driver thrill- seeking are accounted for in his model as an example of a non-social reward, driver thrill-seeking scores were entered last into the analyses, to test the prediction that:
H7: Driver thrill-seeking scores will not predict significant variability in hooning behaviour over and above deterrence theory and additional social learning theory variables.
4.1.1.3 RQ3: What are the road safety implications of hooning behaviours?
To explore the road safety implications of hooning behaviours, this study aimed to explore the risk associated with hooning behaviours per se, and the drivers who engage in hooning behaviours. Thus, participants were asked about crashes where hooning contributed to the crash, and their crash involvement generally. Assuming there are road safety implications associated with both hooning behaviours and drivers who engage in these behaviours, it was predicted that:
H8: There will be a positive relationship between hooning behaviours and involvement in hooning-related crashes.
4.1.1.4 RQ4: Do drivers who engage in hooning also engage in other risky driving behaviours?
In addition to the main dependent variable of hooning behaviour, participants were also asked about their involvement in other illegal driving behaviours to explore the fourth key research question in this program of research. It was discussed in section 2.3.1.1 that it is possible that illegal street racing is associated with risky driving behaviour in general, as items in risky driving measures have included racing other vehicles. If this is true, given that illegal street racing is a sub-set of hooning behaviours, it then follows that:
H9: There will be positive relationships between hooning behaviours and other illegal driving behaviours; and H10: There will be a positive relationship between hooning behaviours and involvement in crashes generally. 106 Hooning behaviours
4.1.1.5 RQ5: How effective are vehicle impoundment and forfeiture programs at reducing hooning behaviour?
If Queensland’s vehicle impoundment and forfeiture laws for hooning are effective, they should serve as a deterrent for future hooning behaviour. Thus, it was predicted that:
H11: Queensland’s vehicle impoundment and forfeiture laws for hooning will be perceived as certain and severe; and H12: Drivers who engage in hooning behaviour will report reducing their hooning behaviour in response to Queensland’s vehicle impoundment and forfeiture laws for hooning.
4.2 Method
4.2.1 Sampling population
Consistent with Study 1a, the population of interest for this study was drivers who engage in hooning behaviours, as listed in Queensland’s anti-hooning legislation (i.e., Police Powers and Responsibilities Act 2002); that is: dangerous operation of a motor vehicle; careless driving of a motor vehicle; racing and speed trials on roads; and wilfully starting a vehicle, or driving a vehicle, in a way that makes unnecessary noise or smoke. To be eligible for participation in this study, the person was required to drive in Queensland and report engaging in at least one of the prescribed hooning behaviours in the previous month. However, consistent with Study 1a, it was not necessary for participants to have been penalised under these laws; they only needed to engage in one or more of the behaviours that could result in these laws being applied.
4.2.2 Recruitment method
A sample of 250 to 300 drivers who reported engaging in hooning behaviours in Queensland was desired for this study to provide adequate statistical power for the required analyses7. As discussed in section 3.4.2.1, while a media release facilitated
7 According to Green’s recommendations (as cited in Field, 2005), to have sufficient statistical power for the regression analyses, a sample of 50 + (8*24 variables) was required (i.e., N 242). Hooning behaviours 107 the recruitment of the small sample desired for Study 1a, this method was considered unlikely to yield an adequate sample for Study 1b. Alternative recruitment methods were identified, including face-to-face recruitment at locations where drivers who engage in hooning behaviours tend to gather in large groups, and the use of an online survey. In both cases it was planned to use snowballing as an additional recruitment technique, where participants would be encouraged to pass on details about the research to others who met the selection criteria and may also be interested in participating. The face-to-face recruitment method did not prove successful during the pilot stage, with only eight drivers completing the questionnaire in one evening, and no drivers during four other attempts at locations across South East Queensland. Focus group participants had suggested that the hooning scene was changing, and that large group gatherings were becoming less frequent, as these gatherings were more likely to attract the attention of police and transport agencies. This was directly observed during one evening of attempted questionnaire piloting, where the research team witnessed a group of police officers conducting licence checks, random breath tests, and vehicle inspections at the proposed data collection location. There were also problems with the selection criteria during piloting, where some of the eight pilot participants indicated verbally that they met the criteria, but later inspection of their questionnaires revealed that their responses did not fit the criteria and, therefore, were not eligible for inclusion in the study. This recruitment method was ultimately abandoned, and the questionnaire was developed as an online survey, with the selection criteria questions at the beginning of the survey. Respondents who did not answer in a way that satisfied the criteria received a message that said “Unfortunately you do not meet the selection criteria for this study and are not required to complete this survey. Thank you for your time”. Only those that responded in a way that did meet the selection criteria were able to continue to further questions. With the permission of forum moderators, advertisements about the research, including a link to the online survey, were posted on Queensland regional forums of car-related websites mentioned by focus group participants in Study 1a. Similar information was also emailed directly to anyone who had previously contacted the researcher and expressed an interest in participating. In addition to the snowballing request, participants were asked to suggest other potential means of recruitment (i.e., 108 Hooning behaviours
other online forums) and advertisements about the research were also placed there. As this recruitment method resulted in the successful recruitment of an adequate sample within approximately six weeks, no other recruitment methods were employed.
4.2.3 Participants
A total of 370 drivers satisfied the selection criteria and commenced the online survey. However, after multi-staged data cleaning (described in detail in section 4.3.1), the sample of participants used in analyses consisted of 290 drivers, of which 259 were male (89.3%) and 31 were female (10.7%). While this over- represents females relative to the sample of hooning offenders in Study 2a (reported in the next chapter, females = 2.6% of sample), the age of participants in this study was similar to the hooning offender sample, as most were under 25 years old (median age = 22 years; range 17 – 55 years), with approximately one third of participants (32.9%) aged 25 years or over. As this was a rather lengthy survey (some participants reported that completion took more than 30 minutes), participants were given a small thank you gift of two movie ticket vouchers valued from AU$18 – 32, depending on the individual’s normal admission price. These vouchers would be worth approximately $18 to students or concession card holders who normally pay $9 per movie ticket, but closer to $32 if the participant was not eligible for any discounts and normally pays the full admission price of $16 per ticket.
4.2.4 Design and measures
The variables of interest in this study were informed by the review of relevant literature (described in Chapter 2) and the focus groups conducted in Study 1a. For ease of reference, Appendix C.1 includes a table that outlines each of the variables in Study 1b and the items in the survey designed to measure it, while Appendix C.2 includes a printed version of the online survey. Hooning behaviours 109
4.2.4.1 Demographic characteristics
The demographic characteristics measured in this study included gender, age, education (completed and in progress), employment (status, usual occupation, and need to drive for work), and some driving questions (licence type, years driving unsupervised and hours of driving per week). Consistent with other studies in the program of research, responses to the usual occupation question were later recoded according to the Australian Standard Classification of Occupations (Australian Bureau of Statistics, 1997), with an additional “not working” group created to include students, retirees, and the unemployed. The demographic characteristic questions were the first group of questions after the selection criteria. While some research design experts suggest that it is more appropriate to leave demographic questions to the end of surveys to avoid confronting participants and increase openness (e.g., Christensen, 2007; Mitchell & Jolley, 2001), they were included earlier in this survey for a number of reasons. First, it was believed that these questions would be very easy for participants to answer, and would allow them to familiarise themselves with the online survey tool and methods of responding. Further, as the bulk of the survey items related to their experiences with or attitudes towards a series of illegal behaviours, it was also believed that demographic questions would be considered less confronting than the remainder of the survey. Finally, it was of utmost importance to be able to describe the sample in order to consider representativeness. Given the length of the survey, and expectation that some participants would not complete all of the questions, demographic characteristics and the more important study variables were placed earlier in the survey.
4.2.4.2 Main dependent variables
The main dependent variables in this study were the frequency of current hooning behaviour (operationalised as behaviour in the previous month), intentions regarding future hooning behaviour (operationalised as likelihood of engaging in hooning behaviour in the following month), and crash involvement as a driver and passenger in the previous three years. As noted previously, the questions relating to current (or last month) frequency of hooning behaviour were used as selection 110 Hooning behaviours
criteria for this study, with the time period limited to one month to facilitate recall. Future intentions regarding hooning behaviour were measured on a Likert scale from 1 (very unlikely) to 7 (very likely) to use in prediction models. While intentions to engage in behaviour are not a perfect predictor of actual future behaviour, they do provide insight into preparedness to engage in behaviour in the future. It was noted in section 2.7.4 that asking participants about hooning generally is problematic given the number and heterogeneity of driving behaviours grouped together under the common label of hooning in Queensland. Thus, the questions relating to current hooning behaviour and intentions regarding future hooning behaviour were asked separately for: driving behaviour such as burn outs, donuts, fish tails, drifting, or skids (referred to as noise and smoke-related hooning behaviours in this chapter); taking part in an illegal street race (including time trials); being part of a rolling road block while others raced; and racing while others held back traffic in a rolling road block. This separation of the hooning behaviours was consistent with Queensland legislation. While anecdotal evidence from police (Crang, 2006) and participant feedback in the focus group discussions in Study 1a suggests that the use of rolling road blocks to facilitate illegal street racing is becoming less frequent in Queensland, the behaviours were separated in this way to explore their prevalence. In addition to asking about the number of previous crashes participants had been involved in as a driver or passenger, participants were asked about crashes that involved the two main groups of hooning behaviours (described as things like burn outs and illegal street racing). These questions categorised severity of crashes as incidents involving injury to at least one person, no injury but at least one vehicle required towing, or no injury but at least one vehicle was damaged and did not require towing. Participants were also asked about whether the crash (or most recent crash if they had been involved in more than one) in each category was reported, in an attempt to describe the presumed under-reporting of crashes, particularly those involving hooning behaviour. The time period was limited to three years to facilitate recall, and to be consistent with other driving history (offence) questions.
4.2.4.3 Driving history and vehicle type
Participants responded to a number of driving history questions concerning a Hooning behaviours 111 variety of traffic offence types in the previous three years, and the frequency of a series of risky or illegal driving behaviours in the previous month to complement the responses regarding hooning behaviour in the same time period. Questions about the vehicle driven most often, and the vehicle/s used for hooning behaviours (if different from that driven most often) were also asked. However some of the websites used to recruit participants were dedicated to particular vehicle makes and models (e.g., www.[make][model].com). As a result of this sampling technique, the make of vehicles of drivers in the sample was biased towards the makes and models these sites related to and it was, therefore, not appropriate to analyse these data any further than describing the proportion of the sample that have access to multiple vehicles, and use of different vehicles for different driving activities. This was of interest as a participant in Study 1a talked about using a generic looking vehicle to go for a drive and see how many police were patrolling before returning home and going out in the vehicle they used for racing. Other Study 1a participants also discussed how the effect of vehicle impoundment was eliminated, or at least minimised, if you had ready access to other vehicles.
4.2.4.4 Expanded deterrence theory
As noted in section 2.7.1, expanded deterrence theory has previously been applied to a study of hooning behaviour (Gee Kee et al., 2007), where each component of the theory was generally addressed by only one item, and referred to hooning behaviours generally. However, based on participant comments in the focus groups conducted for Study 1a, and the hypotheses of this study, questions relating to the components of expanded deterrence theory were divided in a number of ways to better measure the complex group of behaviours hooning represents. Participants were asked to respond to each question for both illegal street racing / speed trials and behaviours involving unnecessary noise and smoke such as burn outs. Further, questions regarding perceptions of the severity of punishment (Qs 43 – 45 and 49 – 51) were asked separately for each of the impoundment periods used in Queensland, and in terms of perceived severity and the difference experiencing the penalty would make to their daily life. When asking about perceived likelihood of detection (Qs 40, 46, and 99 – 100), survey items included the various contexts raised by focus groups participants, who had indicated that the 112 Hooning behaviours
likelihood of detection varied depending upon the location. It was difficult to operationalise a single measure of punishment avoidance for this study, as it is not clear in the deterrence literature whether punishment avoidance relates to the frequency of the behaviour that goes undetected (i.e., punishment is avoided by avoiding detection), the frequency a person is able to avoid punishment once detected, or a combination of both of these scenarios. Other research has been able to measure punishment avoidance in terms of the individual’s experience being stopped by police for another purpose and avoiding (secondary) detection, for example being stopped for a random breath test but not having their licence checked while driving unlicensed (Watson, 2004c), or not being required to provide a sample for a drug test when stopped while driving after using drugs (Watling, Palk, Freeman, & Davey, 2010). Hooning offences are not as covert as these types of offences, so it is not appropriate to measure punishment avoidance in terms of the extent to which an individual has avoided secondary detection. Measuring punishment avoidance for hooning as the frequency of behaviour less the number of times they have been caught is essentially measuring the frequency of the behaviour in this sample. Therefore, two measures of punishment avoidance were derived for these analyses. First an ordinal8 variable “avoidance” was created, where participants received a score of: 1 if they were caught for at least one hooning offence and were punished (i.e., they were not able to avoid punishment on at least one occasion); 2 if they were not caught for any hooning offences (i.e., avoided punishment by avoiding detection); or 3 if they were caught for a hooning offence but the vehicle was not impounded (i.e., they were detected but still avoided punishment). As such, higher scores on this variable indicate higher punishment avoidance. A second measure used was the scale score for the use of punishment avoidance strategies, as higher scores indicate that participants have been able to use these strategies to avoid punishment more often. Additional items (Qs 70 – 73) were created relating to strategies used to avoid punishment based on focus group participant comments, but also had a free response “other” item where participants could indicate other ways
8 This variable was considered ordinal rather than categorical as the extent to which the person had avoided punishment increased with each level, but was also assumed to have interval qualities. This measure also allowed a more sensitive measure than a dichotomous scale, which would have had low statistical power for analyses given so few people in the sample had experienced vehicle impoundment. Hooning behaviours 113 they or their friends had successfully avoided punishment since the vehicle impoundment laws for hooning were implemented. Finally, included with the expanded deterrence theory questions were items designed to further explore issues that arose during the focus group discussions. For example, participants were asked about their intentions to flee from police to avoid punishment (Qs 43c, 44c, 45c, 49c, 50c, and 51c). There have been occasions in Australia when members of the public or politicians have called (via the media) for penalties for hooning offences to be increased to follow the lead of North American jurisdictions that crush the vehicles of offenders and make them watch (e.g., AAP, 2010; The Motor Report, 2010). These calls are often in response to a crash believed to be hooning-related, or an offence that is deemed to have had the potential to have resulted in a crash (e.g., an illegal street race involving extremely high speeds). People quoted in these stories argue that the message that hooning is dangerous is not getting through to potential offenders, and that the only way to “make them think twice” is to increase the severity of the penalties (AAP, 2010). Some jurisdictions (e.g., NSW) already destroy forfeited vehicles in crash tests, while others may destroy those that are not fit for sale. To explore this issue, participants were asked a series of questions about crushing cars (Q52a – c). First, they rated the severity of this penalty for a third hooning offence. Second, they were asked to directly compare crushing cars to vehicle forfeiture on a scale from 1 (forfeiture is far worse) to 7 (crushing is far worse), with 4 labelled ‘much the same’. Finally, they were asked to rate how likely it was that they would flee from police in order to avoid having their vehicle crushed. Similar to previous speeding research (Fleiter, 2004), participants were also asked how long the initial impoundment period would need to be in order to prevent them from engaging in the two main groups of hooning behaviours (Q53a – b).
4.2.4.5 Social learning theory
Items designed to measure the components of social learning theory were developed based on the focus group discussions in Study 1a and previous road safety and other illegal behaviour research that had utilised this theory (Akers, 1990; Akers, 1994, 1998; Akers et al., 1979; Armstrong et al., 2005; DiBlasio, 1988; Fleiter, 2004, 2010; Fleiter & Watson, 2006; Gee Kee, 2006; Watson, 2004c). All questions were 114 Hooning behaviours
asked separately for the two main groups of hooning behaviours as distinguished in Queensland’s legislation. Behavioural (Qs 14 – 15) and normative (Qs 80 – 82) aspects of differential association were explored. Imitation was measured by their agreement with a number of statements about the reasons why they started engaging in the two types of hooning behaviours (Qs 16 – 17, excluding c). Differential reinforcement items were developed to measure perceptions regarding: social rewards (Qs 83 – 84, 87 – 88, 91 – 92), punishment (Qs 85 – 86, 89 – 90, 123 – 124) and absence of punishment (Qs 74 – 79); non-social (intrinsic) rewards (Qs 121 – 122) and punishments (Qs 125 – 126 excluding e and g); instrumental punishments (Qs 125 – 126 e and g); and finally their perceptions of the overall balance of rewards and punishments likely to result from hooning (Qs 127 – 129). Definitions items included those designed to measure personal attitudes relating to hooning in specific contexts (Qs 115 – 118), comparing hooning to other high-risk driving behaviours (Qs 38 – 39), and a series of statements about hooning that were favourable (Qs 103 – 106, 113 – 114), neutral (Qs 93 – 94, 97 – 98, 107 – 110) or negative in nature (Qs 95 – 96, 101 – 102, 111 – 112, 119 – 120). This approach is consistent with Akers’ (1990) suggestions, and previous applications of this theory to road safety issues (Fleiter et al., 2006; Watson, 2004c).
4.2.4.6 Driver thrill-seeking
The main positive outcome of hooning behaviours, and often sole reason identified by Study 1a participants for engaging in the behaviour despite the greater number of potential negative consequences, was the thrill obtained from the experience. Rather than using a general measure of thrill- or sensation-seeking, a measure specific to driving was sought. Stradling et al. (1999, as cited in Stradling, Meadows, & Beatty, 2004) used an eight-item driver thrill-seeking scale based on the work of Matthews et al. (1997), where each item was scored from 1 (strongly disagree) to 11 (strongly agree). Example items from the scale include “I get a real thrill out of driving fast” and “I like to raise my adrenaline levels while driving”. The scale has acceptable internal consistency (Cronbach's alpha = .91, Stradling et al., 1999, as cited in Stradling et al., 2004), and has been successfully applied to other road safety research (Fleiter, 2004, 2010; Tunnicliff, 2006; Watson, Tunnicliff, White, Schonfeld, & Wishart, 2007). This scale was included as items 62 – 69. Hooning behaviours 115
4.2.4.7 Other items
Items measuring other variables were included (and appear in Appendix C.2), however as they did not form part of study hypotheses, they are not described in this chapter.
4.2.5 Procedure
Prior to participant recruitment, clearance to conduct research with human participants was obtained from the Queensland University of Technology Human Research Ethics Committee (reference number 0700000589). The research project risk assessment was approved by the School of Psychology and Counselling Workplace Health and Safety Officer (project number 110). As discussed in section 4.2.4, items were developed or sought to measure each of the variables of interest in the study, and were arranged in a pen-and-paper questionnaire format. The initial face-to-face recruitment strategy was trialled during the piloting phase and did not prove successful. Revisions to items were made based on feedback from the eight pilot participants. The survey was then produced in an online format, which allowed the selection criteria to be checked and participants prevented from continuing with the survey if their responses indicated that they were not eligible. The online version of the survey was piloted by the researcher’s colleagues and acquaintances, with a focus on the readability and user-friendliness of the survey tool, and checking whether the appropriate error messages were presented when response rules were violated (e.g., when participants did not meet the selection criteria, or entered letters in a field that should only include numerals). Recruitment invitations were first sent via direct emails to people who had contacted the researcher previously to express an interest in participating in the program of research. These invitations were based on the information sheet developed for the pen-and-paper version of the questionnaire, presented in Appendix C.3. The researcher then contacted moderators of online forums for permission to join the forum and post information about the research and a link to the survey on the site. This process was repeated with a number of car-related forums over a period of approximately six weeks, at which time the desired number of participants had been 116 Hooning behaviours
reached, and the allocation of movie ticket vouchers had been exhausted. There was no separate consent form for this study. After reading the information sheet that formed the first page of the online survey, participants were required to click a button confirming their consent to participate in the research before continuing to the selection criteria and remainder of the survey. Participants who completed the entire online survey were thanked for their time and participation, and invited to enter an email address to allow the researcher to contact them regarding sending them two movie ticket vouchers. While participants were assured that email addresses were stored in a database separate to the survey and, therefore, could not be matched to responses, some participants (2.9%) entered an incomplete or invalid email address. All participants who entered a valid email address were sent a message within 48 hours of completing the survey asking them to reply to the email with a postage address. They were encouraged to use only their initials or a PO Box to preserve their anonymity, but were reminded that it was not possible to match their contact details to their survey responses. A small percentage (8.6%) of participants did not reply to the repeated attempts to send them their gift. Two movie ticket vouchers and a thank you note were posted the same or following business day to participants who provided contact details. Participants who contacted the researcher again as they had not received their tickets were sent replacements. In accordance with ethical clearance for this project, the contact details provided by participants for the purpose of sending them their movie ticket vouchers were deleted six months after the survey had closed.
4.2.6 Statistical analyses
The online survey data were downloaded into a number of Excel spreadsheets (one for each page of the online survey). A code generated by the survey tool was allocated to each participant who commenced the survey, and was used to link their data between the various Excel files, with the exception of the file that contained the email addresses, which was not coded. The code was a combination of the Internet Protocol (IP) address of the device they were using, and the date and time they submitted the first page of the survey. The dataset was cleaned and screened as described in section 4.3.1, and the final dataset was copied from the Excel files into an SPSS data file for analysis. An Hooning behaviours 117 alpha level of p < .05 was adopted for all analyses. The selection of specific tests for analyses was based on the distributions of the data. Where the data violated the assumptions of the desired parametric test, the non-parametric alternative was used. Data measured on Likert scales were assumed to be of an interval nature to facilitate their use in analyses.
4.3 Results
4.3.1 Data cleaning
Prior to compiling the SPSS data file, the data were examined and cleaned based on a number of factors. As noted in 4.2.3, 370 people met the selection criteria and were able to successfully submit this page of data, having answered “yes” to question 1 “Do you drive in Queensland?”, and giving at least one answer greater than zero to question 2, that asked the number of times in the previous month the person had engaged in a number of different types of hooning behaviours. However, of these 370 eligible participants, only 322 (87.0%) completed at least one more page of the survey allowing them to be included in analyses and therefore be considered participants. Thus, the rows of data for the 48 people who only submitted the selection criteria data were deleted from the data files. The second step in the data cleaning process was to attempt to identify duplicate participants in the dataset, using the IP address contained in the codes used to link data files. Once IP address duplicates were identified, responses to demographic questions were examined to determine whether these duplicate IP addresses were due to the same person commencing the survey multiple times, or multiple individuals completing the survey on the same computer (e.g., a group completing the survey together at one person’s house, at work, or in a computer laboratory). Rows of data were only deleted where there was evidence that the duplicate IP addresses were the same person (e.g., responses were identical), rather than the data suggesting that there were multiple individuals (i.e., responses indicated different genders, ages, occupations, and / or vehicles). All three duplicate cases identified only consisted of one or two pages, suggesting that there was an internet browser or some other type of technical error that resulted in the person starting the survey over again. In these cases, and when these data were identical, the incomplete 118 Hooning behaviours
case was deleted, leaving a sample of 319. It should be noted that it is possible that more duplicate cases existed in the data that were not able to be identified. For example, this method would not identify duplicate responses submitted by people using dynamic IP addresses, or different devices connected to different internet accounts (e.g., completing the survey on a computer at home and then again at work or at a friend’s house). However, in a further attempt to identify cases of duplicate data, the files were sorted by occupation, and data from participants with the same occupation were examined. No additional duplicate cases were identified. The next step in the data cleaning process involved attempting to identify response set bias. This type of bias is common in lengthy surveys, and was a possibility in this study as the offer of a thank you gift may have been an incentive for some people to click any response and proceed through the survey to the end without actually reading the items or responding accurately. The use of alternatively worded (i.e., reverse-scored) items is a useful way of identifying potential response sets, as participants should not be responding in the same way to all items within a scale where some are reverse-scored (Mitchell & Jolley, 2001). As the differential reinforcement component of social learning theory involved questions that were worded positively and negatively regarding hooning (Qs 74 – 79, 83 – 92, and 121 – 129), these pages of data were examined for evidence of response set. This involved manually reviewing responses for these questions in order to identify cases where participants had all of the same responses on this scale. The previous responses of these cases were then reviewed to determine whether their survey generally reflected response set bias (i.e., multiple pages of the same response for each question), or whether it was more likely that they had simply misread some of these items. Ten cases were deemed to show evidence of response set bias due to pages of the same responses, and were subsequently deleted, further reducing the sample size to 309. The final step in the data cleaning process was the identification of outliers. These were apparent in the frequency of hooning behaviour items, where participants could enter any value to indicate the frequency of engaging in a number of hooning behaviours in the previous month. Outliers were identified using descriptive statistics and plots, and a number of outliers on the two main frequency variables used in analyses (noise and smoke related hooning behaviours such as burn outs [n = 11] and illegal street racing [n = 10]) were found, with two participants reporting extreme scores on both variables. As Mahalanobis distances revealed that all 19 participants Hooning behaviours 119 were multivariate outliers (p < .001), threatening the validity of the hierarchical regression analyses required to test study hypotheses, these 19 cases were removed, leaving a final sample size of 290. Finally, it should be noted that survey data were downloaded one page at a time, and that the number of respondents decreased page by page, as only 228 people (78.6%) completed the entire survey. However, the 62 incomplete cases were not deleted to preserve statistical power. Rather, all 290 cases were retained and participants were included in any analyses for which they had complete data.
4.3.2 Main dependent variables
The majority of participants reported performing behaviours like burn outs at least once in the previous month (n = 245, 84.5%), resulting in a positively skewed distribution with a median of two (IQR = 4). Illegal street racing and speed trials were less common, with 186 (64.1%) participants reporting engaging in this behaviour at least once in the previous month. This variable was also positively skewed, with a median of one race or speed trial in the previous month (IQR = 3). Keeping back traffic as part of a rolling road block, and racing while others formed a rolling road block were far less common, with only 38 (13.1%) and 41 (14.1%) participants respectively reporting performing these behaviours at least once in the previous month. Thus, both behaviours had medians and inter-quartile ranges of zero. As responses to rolling road block items indicated that they were relatively infrequent compared to the two main types of hooning behaviours, and most of the survey items only differentiated between the two main types of hooning behaviours, they were not used as dependent variables in analyses. Rather, analyses were limited to noise and smoke-related hooning behaviours and illegal street racing. However, as noted above, there was heavy positive skew to the data, even after the deletion of influential outliers discussed in section 4.3.1. Figure 4.1 shows the histogram of the raw data for the frequency of engaging in noise and smoke related hooning behaviours (such as burn outs) in the previous month, while Figure 4.2 shows the square-root transformed data for this variable. While there was still a slight positive skew to the transformed scores, skewness and kurtosis statistics were less than one. 120 Hooning behaviours
Figure 4.1. Frequency histogram for raw data for frequency of noise and smoke- related hooning behaviours such as burn outs in the previous month (N = 290)
Figure 4.2. Frequency histogram for square root transformed data for frequency of noise and smoke-related hooning behaviours in the previous month (N = 290) Hooning behaviours 121
Figures 4.3 and 4.4 show the raw and transformed data for frequency of illegal street racing in the previous month.
Figure 4.3. Frequency histogram for raw data for frequency of illegal street racing / speed trials in the previous month (N = 290)
Figure 4.4. Frequency histogram for square root transformed data for frequency of illegal street racing / speed trials in the previous month (N = 290) 122 Hooning behaviours
Again, the histogram for the transformed illegal street racing frequency scores showed slight positive skew, the skewness and kurtosis statistics were less than one. Hypothesis testing analyses were performed on these transformed scores. Table 4.1 outlines the frequency of each response to the future intentions (likely to engage in hooning behaviour in the next month) items. As can be seen in the table, the relatively low frequency of rolling road blocks in the previous month was also reflected in intentions regarding future hooning behaviour, as the distributions for the two rolling road block items were heavily skewed, with most participants indicating that it was very unlikely that they would perform these behaviours in the next month. The variability within intentions to perform behaviours such as burn outs or take part in a street race in the next month was far greater. These distributions were multi-modal, as the peaks at the extremes and neutral responses along the scales suggest there was a tendency for participants to select responses with anchor points. As already noted, due to the low numbers of participants indicating intentions to engage in rolling road blocks in the future, these results were not included in tests of hypotheses.
Table 4.1 Intentions regarding future (next month) hooning behaviour (N = 290)
Very Even Very
Unlikely Chance Likely 1 2 3 4 5 6 7 Burn outs etc 62 33 30 72 15 27 51 Illegal street race 72 36 31 69 29 20 33 Road block – others race 212 27 14 22 4 1 10 Road block – self race 215 24 13 16 11 3 8
Table 4.2 reports the bivariate correlations between the dependent measures tested in this study, and shows that there were significant positive correlations between all dependent measures. The strongest correlations were between the frequency and intentions of the same type of hooning behaviour (i.e., between frequency of burn outs etc in the last month and intentions regarding burn outs etc in the next month, and frequency of illegal street racing in the last month and intentions regarding illegal street racing in the next month).
Hooning behaviours 123
Table 4.2 Bivariate correlations (Pearson’s correlation coefficient) between dependent measures of hooning behaviour (N = 290)
Frequency Intentions Burn outs Racing Burn outs Racing Frequency of burn outs etc ~ Frequency of illegal street racing .26*** ~ Intentions regarding burn outs etc .56*** .12* ~ Intentions regarding illegal street racing .19** .57*** .42*** ~ * p < .05; ** p < .01; *** p < .001
Table 4.3 summarises the responses to crash involvement items, when participants were drivers and passengers, for the previous three years. As responses to questions regarding the number of crashes was extremely skewed (most crash- involved participants had only been in one crash), responses were recoded into dichotomous variables (0 = No; 1 = Yes).
Table 4.3 Number of participants involved in crashes as a driver and passenger by crash type (N = 277)
Crash type No injury, No injury, Injury crashes vehicle damage vehicle damage (towing) (no towing) n % n % n % Drivers in crashes Any crashes 22 8.9% 55 19.9% 70 25.3% Reported 16 72.7% 32 58.2% 15 21.4% Burn out crashes 6 2.2% 19 6.9% 35 12.6% Reported 3 50.0% 3 15.8% 3 8.6% Racing crashes 5 1.8% 9 3.2% 10 3.6% Reported 5 100.0% 1 11.1% 1 10.0% Passengers in crashes Burn out crashes 12 4.3% 21 7.6% 36 13.0% Reported 7 58.3% 9 42.9% 6 16.7% Racing crashes 5 1.8% 7 2.5% 12 4.3% Reported 2 40.0% 4 57.1% 1 8.3%
124 Hooning behaviours
Almost half of the participants (n = 126, 45.5%) who responded to the crash questions reported being a driver in at least one crash in the previous three years. As shown in Table 4.2, while only a small number of participants had been driving in a crash that resulted in an injury, one fifth to one quarter had been involved in less serious crashes were no one was injured, but a vehicle was damaged. A total of 47 participants (17.0%) reported driving in at least one crash where doing things like burn outs was a factor, and 17 people (6.1%) reported driving in at least one crash where illegal street racing was a factor in the previous three years. Results for hooning-related crash involvement as a passenger was similar, as 49 (17.7%) participants reported being a passenger in a vehicle involved in a burn out-related crash. Involvement as a passenger in illegal street racing-related crashes was less common but consistent with involvement as a driver, with only 18 participants (6.5%) reporting this type of involvement. In terms of participants reporting their crashes, this was generally highest for injury crashes, and decreased with the severity of the crash. This trend was observed for all crashes as a driver, and hooning-related crashes as a driver and passenger, with the exception of racing-related crashes. However, the small sample sizes for racing-related crashes may have caused the deviation from the overall trends in crash reporting. Reporting of hooning-related crashes was generally lower than for all crashes as a driver. While the crash data were collected for use as a dependent variable, due to the low number of crash-involved participants and, therefore, low statistical power, no hypotheses relating to the factors contributing to crash involvement status were tested, with the exception of hypotheses 8 and 9, relating to the relationships between hooning behaviours and crash involvement.
4.3.3 Demographic characteristics
In addition to the gender and age of participants reported in section 4.2.3, Table 4.4 outlines the responses to the education and employment questions that relate to hypothesis 1. Consistent with the other studies in this program of research, and hypothesis 1, the most common major occupation group was tradespersons. Tradespeople were over-represented in this sample relative to Queensland wage and salary earners (Australian Bureau of Statistics, 2009).
Hooning behaviours 125
Table 4.4 Participants’ education, employment status and usual occupation (N = 290) Qld wage Survey respondents and salary earnersa n % %b % Highest level of education Primary school 2 0.7% Secondary school 101 34.8% TAFE or Technical College 57 19.7% Trade apprenticeship 62 21.4% University – Undergraduate 51 17.6% University – Postgraduate 17 5.9% Current employment statusc Not working 12 4.1% Casual worker 35 12.1% Part-time worker 14 4.8% Full-time worker 208 71.7% Self-employed 36 12.4% Usual occupation by ABS Major Groups Tradespersons and related workers 60 20.7% 25.0% 12.1% Professionals 43 14.8% 17.9% 17.5% Elementary clerical, sales, service workers 31 10.7% 12.9% 11.2% Associate professionals 27 9.3% 11.3% 7.6% Intermediate clerical, sales, service workers 24 8.3% 10.0% 20.2% Labourers and related workers 20 6.9% 8.3% 12.1% Managers and administrators 18 6.2% 7.5% 9.2% Intermediate production & transport workers 15 5.2% 6.3% 7.8% Not workingd 15 5.2% ~ ~ Self-employedd 8 2.8% ~ ~ Advanced clerical and service workers 2 0.7% 0.8% 2.3% Not specified 27 9.3% 8.3% a Source: Australian Bureau of Statistics (2009). Percentages for the known Major Codes used the known occupation codes as the denominator to allow comparisons with hooning offenders, thus the total of percentages in this column sum to 108.3% if the “Not specified” group are added. b Percentages calculated using only ABS Major Codes (n = 240) as denominator. c Participants could tick more than one option, resulting in a sum of more than 100%. d These groups were created in addition to the ABS Major Codes. “Not Working” includes the unemployed, students, pensioners and retirees. “Self-employed” includes people whose occupation was listed as self-employed, owner/operator or business owner.
In terms of current licence level, approximately two thirds of the participants (n = 205, 70.7%) reported holding an Open driver’s licence, while 48 (16.6%) held a Provisional licence, 15 (5.2%) held a P2 licence, 18 (6.2%) held a P1 licence, and one (0.3%) held a Learner’s permit. Three participants (1.0%) reported being 126 Hooning behaviours
unlicensed. The median number of years participants had held at least a Provisional licence allowing them to drive unsupervised was five years (range = 0 – 38 years), and was heavily positively skewed (IQR = 5 years). The similarity between the frequency histograms for age and years driving, and the strong positive correlation
between these variables (rs [287] = .90, p < .001) suggest that the majority of people in this sample became licensed within a year or two of turning 17 years, the minimum age for obtaining a Provisional licence in Queensland. Approximately two thirds of participants (n = 195, 67.2%) indicated that they needed to drive for their job. The mean number of hours driven per week was 16.57 (SD = 14.55); however, the data were positively skewed (Mdn = 13 hours) due to significantly larger values for participants who reported driving for work (n = 195, Mdn = 15, IQR = 10) than those who do not (n = 95, Mdn = 10, IQR = 10), Mann- Whitney U = 7401.50, z = -2.79, p = .005. Table 4.5 reports the associations between demographic characteristics and the dependent measures in this study using analyses appropriate for the relevant data. The relationships between gender and the need to drive for work and the dependent measures were assessed using independent samples t-tests; the relationships between age, years driving experience and driving hours per week and the dependent measures were assessed via Spearman’s rho correlation coefficients due to skewed data on these variables; and the relationships between highest level of education and current employment status and the dependent measures were assessed via one-way between groups ANOVAs.
Table 4.5 Associations between demographic characteristics and driving history variables and frequency and intentions regarding hooning behaviours
Frequency Intentions N Burn outs Racing Burn outs Racing Gender 290 t(288) = 2.57* t(288) = 0.39 t(288) = 2.23* t(288) = 0.08
Age 289 rs = .01 rs = .03 rs = .02 rs = .06 Education 290 F(5, 284) = 1.03 F(5, 284) = 0.76 F(5, 284) = 0.70 F(5, 284) = 0.40 Drive for work 290 t(288) = -0.46 t(288) = 0.09 t(288) = -0.73 t(288) = -1.35 Licence 290 F(5, 284) = 1.16 F(5, 284) = 0.82 F(5, 284) = 0.40 F(5, 284) = 1.21
Years driving 290 rs = -.01 rs = .06 rs = .03 rs = .11
Driving hrs/wk 290 rs = .22*** rs = .21*** rs = .15** rs = .17** * p < .05; ** p < .01; *** p < .001 Hooning behaviours 127
As can be seen in the table, the only significant associations between demographic characteristics and hooning behaviours were found for gender and the number of hours driven in the average week. Gender was associated with both frequency and future intentions for noise and smoke-related hooning behaviours, where males had significantly higher scores than females on both measures. However, effect sizes were small, and should be interpreted with caution given the over-representation of males relative to females in the sample. The number of hours driving per week was significantly related to all dependent measures. As these associations were positive, in that the more hours the person drove, the more they engaged or intended to engage in the behaviour, these results may reflect an effect of exposure. It was also noted that these effects were small, explaining 2.3 – 4.8% of variability in the dependent measures.
4.3.4 Driving history and vehicle type
More than three quarters of the sample (n = 220, 76.7%) reported being booked for at least one traffic offence other than hooning in the previous three years. Table 4.6 shows the number of respondents with previous offences (by type). Consistent with Study 1a and Study 2b, the most common previous offences reported were speeding and those related to vehicle defects or unapproved vehicle modifications.
Table 4.6 Participants with at least one previous offence by type (N = 271)
Range (number n % of offences)a Speeding 181 66.8% 0 – 15 Drink driving 11 4.1% 0 – 1 Drug driving 0 0.0% 0 Seatbelt 9 3.3% 0 – 3 Unlicensed driving 16 5.9% 0 – 7 Vehicle defects / illegal modifications 95 35.1% 0 – 15 a For total sample (N = 271)
The trends in previous offences were consistent with frequency of self- reported illegal behaviour in the previous month, scored from 1 (never) to 7 (every 128 Hooning behaviours
time I drive), where the highest medians were observed for exceeding the posted speed limit (Mdn = 5, IQR = 2) and driving a car that wasn’t roadworthy or had modifications that weren’t approved (Mdn = 2, IQR = 3). All other medians were 1. Table 4.7 reports the associations between driving history variables and the dependent measures in this study. Crash involvement variables were dichotomous (where 0 = No; 1 = Yes), so independent samples t statistics are reported in the table. The previous offences and self-reported driving behaviour variables were positively skewed, so Spearman’s rho correlations are reported for these variables.
Table 4.7 Associations between driving history variables and frequency and intentions regarding hooning behaviours (N = 277)
Frequency Intentions Burn outs Racing Burn outs Racing Crash involvement (last 3 years) All crashes -0.17 -0.45 1.63 1.42 Burn out-related crashes 1.19 1.24 2.82** 2.30* Racing-related crashes 0.32 2.57* 1.76 3.63*** Offences (last 3 years)a Speeding .08 .16* .19** .23*** Drink driving .03 .08 .14* .12* Seatbelt .06 .04 .04 .06 Unlicensed driving .00 .00 .10 .03 Vehicle defects / illegal mods. .03 .15* .07 .13* Self-reported behaviour (last month) Speeding .08 .09 .30*** .29*** Drink driving .00 -.06 .10 .08 Drug driving .11 .01 .13* .09 Seatbelt .06 .08 .10 .17** Unlicensed driving .07 -.01 .17** .08 Vehicle defects / illegal mods. .03 .12* .13* .21*** a Measured continuously. Drug driving offences are not included as no such offences were reported. * p < .05; ** p < .01; *** p < .001
As shown in Table 4.7, general crash involvement was not associated with hooning behaviour. However, there were significant relationships between hooning- related crash involvement and hooning behaviour. In all cases, hooning-related crash-involved drivers reported higher frequencies of hooning behaviours, and Hooning behaviours 129 stronger intentions to engage in hooning in the next month. However, these differences were only significant for drivers involved in hooning-related crashes, thus supporting hypothesis 8, but contrary to hypothesis 10. As shown in the table, drivers involved in burn out-related crashes indicated significantly stronger intentions to engage in either type of hooning behaviour in the next month. Drivers involved in illegal street racing-related crashes reported a significantly higher frequency of illegal street racing in the last month, and stronger intention to illegal street race in the next month. Table 4.7 also shows that there were small but significant positive relationships between the number of previous traffic offences and self-reported driving behaviour and the dependent measures, providing partial support for hypothesis 9. Self-reported speeding and previous speeding offences appeared to be the most important, as these items had the strongest relationships with the dependent measures. Vehicle type questions were asked separately for vehicle driven most often, and vehicle used to do things like burn outs or have street races. Most participants reported driving a vehicle registered to them most of the time (n = 244, 88.1%), with 32 (11.6%) driving a vehicle registered to someone else, and one participant (0.4%) reported driving an unregistered vehicle. Among the survey respondents who perform behaviours like burn outs (n = 245), most use their everyday vehicle (66.9%), while 55 (23.3%) reported using a different vehicle. This vehicle was less likely to be registered to them than their everyday vehicle (61.8%) and, therefore, more likely to be registered to someone else (25.5%) or unregistered (12.7%). Similar trends were observed for illegal street racing, where among those respondents who engage in the behaviour (n = 186), most use their everyday vehicle (71.4%), while 35 (20.0%) report using a different vehicle. This vehicle was also less likely to be registered to them than their everyday vehicle (80.0%), and therefore more likely to be registered to someone else (17.1%) or unregistered (2.9%). Of note, the vehicles used to do things like burn outs and participate in illegal street races, when different to the vehicles driven normally, were slightly older, with median years of manufacture of 1989 and 1992 respectively compared to 1997. The years of manufacture of these “hooning” vehicles is fairly consistent with the typical age of vehicles used in hooning offences in Study 2a (mean year of manufacture of 1992), 130 Hooning behaviours
reported in the following chapter.
4.3.5 Hypothesis testing
The remainder of this section will focus on factors contributing to hooning behaviours (hypotheses 2 – 7) and the effectiveness of vehicle impoundment and forfeiture laws for hooning from the drivers’ perspective (hypotheses 11 and 12). Descriptive data for the study variables will be provided before the results of statistical analyses designed to test the relevant hypothesis are reported.
4.3.5.1 Expanded deterrence theory
Hypothesis 2 related to expanded deterrence theory variables. Direct experience with punishment was measured by two variables each for behaviours such as burn outs and illegal street racing. Participants were asked how many times they had been caught for these types of offences in the last three years, and how long the longest period of time they had their vehicle impounded for one of these offences. Indirect experience with punishment was measured by three items: how many of the participants’ friends had been caught for a hooning offence of each type; was the vehicle impounded; and what was the longest impoundment period applied. Table 4.8 outlines descriptive statistics for these items. In terms of direct experience, 53 participants (19.6%) reported at least one burn out-related offence, while 20 (7.4%) reported at least one illegal street racing offence in the last three years. A Wilcoxon Signed Rank test revealed that this difference was significant, as there were significantly more burn out type offences reported than illegal street racing offences, z = -5.18, p < .001, representing a small to medium effect (r = .22). Interestingly, as shown in Table 4.8, very few of these participants reported having their vehicles impounded for either hooning offence type, even though vehicle impoundment laws for hooning were in place in Queensland for the full period in the question. When vehicles were impounded, it was normally for 48 hours, and no participants reported having their vehicle forfeited. Overall (i.e., regardless of hooning offence type), only 14 participants (5.2%) reported having their vehicle impounded for a hooning offence in the three years prior to completing the survey. Hooning behaviours 131
Table 4.8 Descriptive statistics for direct and indirect experience with punishment (N = 271)
Burn outs etc Illegal street racing Direct experience Hooning offences in last 3 yrs Mdn = 0 (IQR = 0)a Mdn = 0 (IQR = 0)b None 77.4% None 85.0% Longest impoundment 48 hours 18.9% 48 hours 10.0% 3 months 3.8% 3 months 5.0% Indirect experience Friends with offences in last 3 yrs Mdn = 2 (IQR = 4) Mdn = 1 (IQR = 3) No 39.4% No 35.8% Vehicle impounded Yes 53.0% Yes 49.0% Don’t know 7.6% Don’t know 15.2%
Not sure 18.1% Not sure 17.6% 48 hours 56.2% 48 hours 58.1% Longest impoundment 3 months 22.9% 3 months 20.3% Forfeited 1.0% Forfeited 4.1% Other 1.9% Other 0.0% a Median and inter-quartile range are reported as the distribution was skewed, however to provide more information about the distribution, the mean was 0.35 and SD was .87. b M = 0.11, SD = 0.49
Regarding indirect experience with punishment, almost three quarters of participants (73.1%) knew at least one person who had been caught for a burn out- related offence in the last three years, while only 55.7% knew at least one person who had been caught for illegal street racing. A Wilcoxon Signed Rank test revealed that participants knew significantly more people who had been caught for a burn out- related offence than an illegal street racing offence, z = -6.12, p < .001, representing a small to medium effect (r = .26). As shown in Table 4.8, participants were more likely to report avoiding having their vehicle impounded when caught for a hooning offence than indicated in their responses regarding their friends’ hooning offences. The most common vehicle impoundment period reported was 48 hours, the penalty for a first hooning offence in Queensland. Table 4.9 describes the mean scores for the other direct experience with punishment avoidance items, where participants indicated how often they’ve been able to avoid getting caught using a variety of strategies. The table shows that the 132 Hooning behaviours
most commonly reported method of avoiding getting caught since vehicle impoundment laws for hooning were implemented, regardless of the type of hooning behaviour, were engaging in the behaviours in locations where the chances of getting caught are low, and reducing how often they participate in the behaviours. Other strategies for avoiding detection included: using legal venues; participating as part of a large group to enhance anonymity; only engaging in hooning in places with minimal traffic that are far away from residential areas; and fleeing from police.
Table 4.9 Use of different punishment avoidance strategies (N = 243)
Illegal street Burn outs etc racing M SD M SD Doing it less often 4.26 2.00 4.06 2.05 Choose locations with low chance of getting caught 4.82 1.89 4.22 2.11 Using mobile phones or police scanners 3.25 2.21 3.12 2.12 Participating as a passenger in someone else’s car 3.31 2.12 3.02 1.94 Driving a car registered to someone else 1.75 1.54 1.88 1.58 Scale 3.48 1.25 3.26 1.38 Cronbach’s alpha (5 items) .64 .74
Table 4.10 describes the same results for indirect experience with punishment avoidance, where participants indicated how often their friends used a variety of strategies to avoid detection.
Table 4.10 Friends’ use of different punishment avoidance strategies (N = 243)
Illegal street Burn outs etc racing M SD M SD Doing it less often 4.11 1.81 4.02 1.93 Choose locations with low chance of getting caught 4.81 1.88 4.36 2.01 Using mobile phones or police scanners 3.55 2.18 3.30 2.12 Participating as a passenger in someone else’s car 3.56 1.96 3.37 1.94 Driving a car registered to someone else 2.37 1.86 2.32 1.73 Scale 3.68 1.34 3.47 1.42 Cronbach’s alpha (5 items) .73 .78
Hooning behaviours 133
These responses were similar to the strategies participants reported using themselves, as the most common methods of avoiding detection where choosing locations with a low perceived probability of detection, and participating in the behaviours less often. Additional strategies reported were also the same as those suggested to avoid detection for themselves. To test hypothesis 12, responses to the “doing it less often” punishment avoidance item for each behaviour were examined. Figure 4.5 shows that more than half of respondents indicated that they have been able to avoid getting caught for either type of hooning behaviour by doing it less often (responding sometimes – every time they drive), offering support for hypothesis 12.
1 - Never 2 3 4 - Sometimes 5 6 7 - All the time 40% 35.4% 35.0% 35% 30% 22.2% 25% 21.0% 20% 18.9% 15% 14.4% 10%
Percent of participants Percent 5% 0% Burn outs etc Illegal street racing
Figure 4.5. Participant responses to Q70a and 71a “How often have you been able to avoid getting caught by doing it less often?”
Perceptions of likelihood of detection were assessed separately for the type of hooning behaviour and for a number of different contexts discussed in the focus groups reported in the previous chapter. Scores on these items were averaged to give a scale score. Participants indicated their agreement with a general statement about the chances of getting caught for both types of hooning behaviour for each context (direct), and also rated their agreement with a statement about the likelihood of “people” generally being caught by police (indirect) for both types of hooning offences. Table 4.11 outlines descriptive statistics and Cronbach’s alphas for each of the scales. All items (and therefore scale scores) could range from 1 to 7, with higher 134 Hooning behaviours
scores reflecting higher perceived likelihood of detection.
Table 4.11 Descriptive statistics for perceptions of likelihood of detection for self and “people” generally
Burn outs etc Illegal street racing N M SD M SD Direct Built-up suburban area 253 4.00 1.91 4.08 1.89 Main street 253 4.76 1.74 4.64 1.67 Highway 253 3.97 1.69 4.14 1.82 Back street / industrial estate 253 2.66 1.67 2.92 1.65 Chances of getting caught 231 4.06 1.65 4.19 1.69 Scale 231 3.89 1.04 3.96 1.08 Cronbach’s alpha (5 items) .56 .60 Indirect 243 3.86 1.43 4.03 1.53
The internal consistency of both scale scores would have been improved (to .64 and .61 respectively) if the back street / industrial estate item was removed, as these items had the lowest mean likelihood of detection scores. The internal consistency of the illegal street racing scale could also be improved to .64 of the general chances of getting caught item was removed. Table 4.11 shows that, regardless of the type of hooning behaviour, participants believed that they were most likely to be caught on a main street, and least likely to be caught on a back street or in an industrial estate. When compared to a response of 4 (even chance) via single sample t-tests, it was found that the perceived likelihood of detection scores were significantly likely for main streets, but significantly unlikely on a back street or in an industrial estate (all ps < .001, representing medium to large effects). Perceived likelihood of detection scores for the remaining items, including scale scores, were statistically equivalent to even chance. Repeated measures t-tests revealed that scale scores for perceived likelihood of detection for themselves did not differ significantly as a function of the type of hooning behaviour (t[230] = -1.38, p = .169, η2 = .01); however, there was a small but significant difference in perceptions for other people generally (t[242] = -2.15, Hooning behaviours 135 p = .032, η2 = .02), where participants felt it was more likely that people would be caught illegal street racing than performing behaviours such as burn outs. There were no significant differences in perceived likelihood of detection for themselves or others as a function of whether the participant had or had not experienced vehicle impoundment (all ps > .05). Perceptions of the certainty and swiftness for punishment for themselves and others were assessed with one item for each of the two main groups of hooning behaviours. Table 4.12 outlines the descriptive statistics for these items.
Table 4.12 Descriptive statistics for perceptions of certainty and swiftness of punishment for self and others
Burn outs etc Illegal street racing N M SD M SD Direct Certainty 253 4.02 2.09 4.64 2.11 Swiftness 253 Mdn = 7 IQR = 2 Mdn = 7 IQR = 1 Indirect Certainty 243 4.58 1.74 5.05 1.68 Swiftness 243 4.93 1.84 5.18 1.80
In all cases, participants gave significantly higher ratings for illegal street racing items compared to the items for noise and smoke-related hooning behaviours such as burn outs (all ps ≤ .01), as participants perceived that it was more likely that a vehicle would be impounded, and that the vehicle would be impounded more quickly, for an illegal street race than for a burn out-related offence. Participants perceived that others were significantly more likely than them to have their vehicle impounded, but that their own vehicles would be impounded significantly more swiftly than others’ vehicles9 for either type of hooning offence (all ps ≤ .001). When certainty scores were compared to a rating of 4 (even chance) via a series of single sample t-tests to test hypothesis 11, results only partially supported the hypothesis, as it was found that participants perceived there was a significantly greater than even chance of having their vehicle impounded for an illegal street
9 As swiftness scores for self were skewed, this was analysed using Wilcoxon Signed Rank tests. 136 Hooning behaviours
racing offence (t[252] = 4.83, p < .001, representing a medium effect, η2 = .08), but their perceptions regarding punishment for a burn out-related offence were statistically equivalent to ‘even chance’ (p = .904). This is consistent with the previous finding that participants perceived certainty of punishment as more likely for illegal street racing offences. However, for others, participants rated the certainty of punishment for both hooning offence types as significantly greater than ‘even chance’ (both ps < .001, representing medium to large effects). This may suggest an optimism bias, where people underestimate the likelihood of negative consequences of their own behaviour relative to that of others (Weinstein, 1980). Finally, while there were no differences in perceptions of certainty and swiftness of punishment for others as a function of whether the participant had experienced vehicle impoundment (all ps > .05), perceptions for themselves did differ. Regardless of the type of hooning behaviour, participants who had experienced impoundment perceived that punishment was significantly more certain and swift than those who had not experienced it (all ps < .05). Questions regarding the perceived severity of penalties were asked separately for themselves (direct) and others (indirect), the relevant penalty period for each hooning offence (48 hours, 3 months and vehicle forfeiture), and for each type of hooning offence. These questions asked participants to rate the severity of the penalty, and indicate the difference it would make to their daily life. Severity scale scores were calculated by averaging the six severity items for each type of hooning behaviour. An additional question possibly related to severity (but not included in severity scale scores) was the participants’ willingness to flee in order to avoid the relevant penalty. Table 4.13 reports the descriptive statistics of these items and scales. Participants’ perceptions of severity for themselves (severity scale scores) varied between burn out-related offences and illegal street racing, with the penalties perceived as significantly more severe for burn out-related offences than for illegal street racing, t(252) = 2.80, p = .006, representing a small effect, η2 = .03. However, there was no significant difference in perceptions of severity of penalties for others, t(242) = -0.75, p = .451. When severity scale scores were compared to a neutral response of 4 to test hypothesis 11, it was found that vehicle impoundment and forfeiture laws were perceived as severe for both noise and smoke-related hooning behaviours (t[252] = 29.07, p < .001) and illegal street racing (t[252] = 25.75, Hooning behaviours 137 p < .001), as the mean scale scores were significantly greater than neutral.
Table 4.13 Descriptive statistics for perceptions of the severity of vehicle impoundment periods for self and others
Burn outs etc Illegal street racing N M SD M SD Direct Perceived severity 48 hours 253 5.31 1.68 5.10 1.82 3 months 253 Mdn = 7 IQR = 2 Mdn = 7 IQR = 2 Forfeiture 253 Mdn = 7 IQR = 0 Mdn = 7 IQR = 0 Difference to daily life 48 hours 253 5.00 2.17 5.02 2.11 3 months 253 Mdn = 7 IQR = 2 Mdn = 7 IQR = 2 Forfeiture 253 Mdn = 7 IQR = 0 Mdn = 7 IQR = 0 Severity scale scores 253 5.86 1.02 5.77 1.09 Cronbach’s α (6 items) .66 .72 Likely to flee from police 48 hours 253 2.72 2.19 2.80 2.29 3 months 253 3.62 2.42 3.60 2.39 Forfeiture 253 Mdn = 7 IQR = 3 Mdn = 7 IQR = 3 Indirect 243 5.22 1.64 5.28 1.68
Although severity scale scores were normally distributed, severity items relating to perceptions of severity and perceived difference to daily life were not. Further, some of the likelihood of fleeing item distributions were also skewed. Thus, participant responses to these items were compared used Friedman’s tests to determine whether perceptions differed as a function of the penalty period. The results of these tests, and Wilcoxon Signed Rank tests to test planned comparisons (48 vs. 3 months; 3 months vs. Forfeiture) using Bonferroni adjustments to control Type I errors are presented in Table 4.14. As can be seen in the table, in all cases, perceptions differed as a function of the length of the penalty period, with significant increases between each increase in the penalty period. In all cases, effect sizes were medium or small to medium.
138 Hooning behaviours
Table 4.14 Perceptions of severity items as a function of penalty period (N = 253)
Burn outs etc Illegal street racing Perceived severity χ2 (2) = 139.38*** χ2 (2) = 148.12*** 48 hours vs. 3 months z = -5.49, r = .24*** z = -7.43, r = .33*** 3 months vs. Forfeiture z = -6.37, r = .28*** z = -6.26, r = .28*** Difference to daily life χ2 (2) = 194.41*** χ2 (2) = 179.78*** 48 hours vs. 3 months z = -8.14, r = .36*** z = -7.59, r = .34*** 3 months vs. Forfeiture z = -6.22, r = .28*** z = -7.17, r = .32*** Likely to flee from police χ2 (2) = 269.67*** χ2 (2) = 259.45*** 48 hours vs. 3 months z = -8.72, r = .39*** z = -8.26, r = .37*** 3 months vs. Forfeiture z = -9.95, r = .44*** z = -10.13, r = .45*** * p < .05; ** p < .01; *** p < .001
The item regarding the need to drive for work was included in this study to examine this was related to perceptions of severity. It was found that perceptions of severity (either as severity ratings, scores on difference to daily life questions, or severity scale scores) did not differ as a function of whether the participant needed to drive for work (all ps > .05). A series of single sample t-tests revealed that participants perceived all penalty periods applied to themselves or others as severe, as mean ratings were significantly greater than ‘neutral’ (a rating of 4), all ps < .001. Further, while there was significantly less than an ‘even chance’ that participants would flee from police to avoid the 48 hour and 3 month penalty periods for either hooning offence type (all ps < .05), single sample t-tests revealed that the average likelihood of fleeing from police to avoid vehicle forfeiture for either offence type was significantly greater than ‘even chance’ (both ps < .001). To test hypothesis 2, the correlations between expanded deterrence theory variables and frequency and intentions regarding hooning behaviours were explored. The results of these analyses are reported in Table 4.15. The number of hooning offences in the last 3 years reported by participants was associated with hooning behaviour, but in the opposite direction to what would be expected, as people with more punishment experience engaged in hooning more frequently and reported stronger intentions to do so in the future. While correlations cannot be used to infer causality, it is unlikely that the experience of punishment has caused any increase in hooning behaviour or intentions. Rather, it is likely that this is due to exposure, in Hooning behaviours 139 that people who engage in the behaviour more (and are also more likely to intend to in the future) are more at-risk of being caught and, therefore, have more offences.
Table 4.15 Bivariate correlations (Pearson’s correlation coefficient) between expanded deterrence theory variables and frequency and intentions regarding hooning behaviours
Frequency Intentions N Burn outs Racing Burn outs Racing Punishment experience Direct Number of offences 271 .26*** .15* .24*** .21*** Impoundmenta 271 .09 .04 .08 .06 Indirect No. of people with offences 271 .00 .12* .12 .17** Impoundmentb -.07 c -.05 d -.01 c .03 d Punishment avoidance Direct Avoidance score 271 .06 .17** .11 .19** Use of strategies 243 .05 .20** .18** .31*** Indirect Use of strategies 243 .02 .15* .16* .24*** Perceived likelihood of detection Direct 231 -.04 -.16* -.04 -.18** Indirect 243 .01 -.07 -.13* -.24*** Perceived certainty of punishment Direct 253 .10 .00 .18* -.04 Indirect 243 .00 -.09 .02 -.13* Perceived swiftness of punishment Direct 253 -.04 .09 -.01 .00 Indirect 243 .00 .01 .07 .02 Perceived severity of punishment Direct 253 .05 .16* .01 .13* Indirect 243 .11 .08 .03 -.03 a 0 = Never experienced impoundment, 1 = Experienced impoundment in previous 3 years b Did any friends with offences experience impoundment? 1 = No, 2 = Yes c n = 183 d n = 128 * p < .05; ** p < .01; *** p < .001
Similarly, the more people the participant knew that had experienced vehicle 140 Hooning behaviours
impoundment, the higher frequency of their own illegal street racing behaviour, and higher the intention to engage in street racing in future. Experiencing impoundment was not related to any of the dependent measures, nor was knowing someone who had experienced impoundment. All punishment avoidance scores were related to illegal street racing behaviours and intentions, and in the expected direction. Participants with more direct and indirect experience with punishment avoidance reported higher frequency of illegal street racing, and stronger intentions to continue to engage in illegal street racing in the future. The only punishment avoidance scores that were significantly related to noise and smoke-related hooning behaviours were the use of punishment avoidance strategies scale scores, also in the expected direction according to deterrence principles. Perceptions of the likelihood of detection (direct) were significantly associated with frequency and future intentions regarding illegal street racing, but not noise and smoke-related hooning behaviours. Higher perceptions of likelihood of detection were associated with lower frequency of, and intentions to engage in, illegal street racing. Perceptions of the likelihood of others being detected hooning were also significantly related to intentions regarding both types of hooning behaviour in the future, consistent with deterrence principles. Results related to certainty of punishment were mixed. The only significant finding for perceptions of having their own vehicle impounded was for noise and smoke-related offences, where people who reported a higher perception of certainty that their vehicle would be impounded reported stronger intentions to engage in noise and smoke-related hooning behaviours in the future. Conversely, for perceptions regarding the certainty that other people would lose their vehicle for a hooning offence, participants who perceived higher certainty of impoundment for illegal street racing offences reported being less likely to have an illegal street race in the next month, consistent with deterrence theory. Perceptions of swiftness of punishment were not associated with any of the dependent measures. The only severity scale scores that were significantly associated with any of the dependent measures were the severity scales scores for themselves for the illegal street racing items. Thus, hypothesis 2 was only partially supported, with only some of the expanded deterrence theory variables being associated with hooning behaviour, and some being significantly associated in the opposite direction Hooning behaviours 141 to theory predictions. Further, expanded deterrence theory variables generally explained more variance in illegal street racing than noise and smoke-related hooning behaviours, although all significant relationships were small. As discussed previously, participants were also asked to indicate their perceptions of the severity of crushing vehicles as an alternative penalty for a third or subsequent hooning offence. Table 4.16 reports the descriptive statistics for these items.
Table 4.16 Descriptive statistics for perceptions relating to the crushing of cars compared to vehicle forfeiture (N = 253)
Median IQR Statistics Perceived severity 7 0 Compared to forfeiture M = 5.05 SD = 1.69 t(252) = 9.91, p < .001, η2 = .28 Likely to flee from police 7 3
While the median severity rating of crushing cars (shown in Table 4.16) is equal to the median severity ratings for forfeiting vehicles for either hooning offence type (shown in Table 4.13), Wilcoxon Signed Rank tests revealed that while there was no significant differences to the severity of burn out-related offences (z = -1.71, p = .088, r = .07), crushing cars was seen as significantly more severe than forfeiture for illegal street racing offences (z = -3.02, p = .003, r = .13), representing a small effect. Similarly, when asked to directly compare the severity of crushing cars to vehicle forfeiture, the median rating was 4, labeled ‘much the same’, while the mean reported in Table 4.16 was slightly above equal. When compared to a rating of 4 with a single sample t-test (results presented in Table 4.16), it was found that participants rated crushing cars as significantly more severe than vehicle forfeiture, representing a large effect. While the likelihood of fleeing item medians were equal to those for vehicle forfeiture for both hooning offence types, there were significant differences in the distributions of these ratings, with Wilcoxon Signed Rank tests revealing that participants reported significantly higher likelihood of fleeing to avoid having their vehicle crushed than forfeited for a burn out-related (z = -2.31, p = .021, r = .10) or illegal street racing offences (z = -2.34, p = .019, r = .10), representing small effects. Finally, participants were asked how long the initial vehicle impoundment 142 Hooning behaviours
period (in days) would need to be to deter them from either hooning offence type. The distributions of responses were positively skewed and multi-modal, with responses clustering around days associated with weeks, months and even years (e.g., 7, 30, 90, 365). The largest peak was at 0 days, possibly representing the participants that do not currently, nor do they intend in the future, to engage in that type of hooning behaviour. There were similarly large peaks at 1 and 2 days, which may indicate a preference for the penalty to stay as it is (48 hours in Queensland), or at least a motivation to respond in this way to avoid giving policymakers evidence for increasing the first offence penalty period. The next highest peaks were at 7 and then 30 days. There were also (outlying) peaks at 365 and 999 days. As 999 was the highest number allowable in that field (limited to three characters), this may indicate that these participants intend to continue engaging in that behaviour, regardless of the length of the first offence impoundment period.
4.3.5.2 Social learning theory
Table 4.17 reports the descriptive statistics and Cronbach’s alphas for each of the additional social learning theory variable scales (i.e., variables in addition to expanded deterrence variables). Sample sizes differ for some scales as scales scores were only calculated for participants who answered every question in the scale. High scores indicate endorsement of the particular hooning behaviour, except for the punishment variables and negative definitions, where lower scores indicate endorsement. All punishment and negative definition items were reverse scored when used to calculate composite scale scores. Generally speaking, the internal consistency of scales developed to measure social learning theory variables were adequate (i.e., ≥ .70), however scales with only two or three items tended to have lower values. The specific definitions alphas were particularly poor (.48 and .56, based on 7 items), although the alphas for the overall definitions scales were adequate. As such, caution should be used when interpreting the results relating to these scales. On all scales where questions were asked separately for friends and family, participants perceived their friends to be significantly more supportive of hooning behaviours than their family (all ps < .001). Where questions were also asked separately for other people generally, participants’ perceptions about others’ views Hooning behaviours 143 did not differ from those of their family (all ps > .05).
Table 4.17 Descriptive statistics for additional social learning theory variables
Burn outs etc Illegal street racing αa αa N M SD M SD (items) (items) Differential association 235 3.66 1.11 .72 (5) 3.24 1.13 .74 (5) Behavioural 290 3.76 1.33 .71 (2) 3.26 1.43 .77 (2) Normative 235 3.60 1.29 .63 (3) 3.22 1.28 .68 (3) Friends 235 5.23 1.61 ~ (1) 4.75 1.78 ~ (1) Family 235 2.89 1.87 ~ (1) 2.49 1.70 ~ (1) Others 235 2.69 1.61 ~ (1) 2.40 1.45 ~ (1) Imitation 290 2.75 1.54 .82 (4) 2.55 1.51 .85 (4) Differential reinforcement 228 3.87 0.92 .90 (35) 3.65 0.95 .91 (35) Rewards 228 3.45 1.11 .84 (10) 3.28 1.13 .85 (10) Social 235 3.11 1.16 .77 (6) 2.84 1.18 .80 (6) Friends 235 4.14 1.51 .74 (3) 3.77 1.62 .81 (3) Family 235 2.07 1.28 .82 (3) 1.91 1.21 .85 (3) Non-social 228 4.02 1.62 .89 (4) 3.99 1.65 .90 (4) Punishments 228 3.97 1.08 .86 (17) 4.19 1.11 .87 (17) Social 228 4.36 1.27 .84 (10) 4.46 1.30 .85 (10) Friends 228 3.42 1.49 .82 (5) 3.54 1.55 .82 (5) Family 228 5.18 1.55 .82 (5) 5.26 1.54 .81 (5) Non-social 228 3.08 1.47 .86 (5) 3.53 1.46 .85 (5) Instrumental 228 4.23 1.77 .44 (2) 4.47 1.68 .42 (2) Absence of punishment 235 4.14 1.57 .86 (6) 3.91 1.47 .83 (6) Friends 235 5.44 1.61 .75 (2) 5.30 1.64 .70 (2) Family 235 3.59 2.20 .85 (2) 3.11 2.15 .88 (2) Others 235 3.41 1.97 .81 (2) 3.31 1.79 .74 (2) Overall Balance 228 3.86 1.50 .42 (2) 3.55 1.50 .49 (2) Definitions 231 4.45 0.86 .80 (18) 4.56 0.96 .83 (18) Specific 231 4.86 0.87 .48 (7) 4.56 0.96 .56 (7) Context 231 5.32 1.51 .52 (2) 4.98 1.69 .62 (2) Comparative 271 4.69 1.09 .59 (5) 4.43 1.16 .62 (5) Favourable 231 3.89 1.48 .66 (3) 3.82 1.47 .64 (3) Neutral 231 4.38 1.45 .79 (4) 4.28 1.55 .84 (4) Negative 231 3.76 1.23 .62 (4) 4.09 1.32 .68 (4) a For scales with one item, no Cronbach’s alpha value is reported. For scales with two items, the values reported are Pearson’s correlation coefficients (r).
It was also noted that there was stronger support for burn out-related behaviours than illegal street racing for all four components of social learning theory (all ps < .005); however, this may reflect the nature of the sample, as reporting of burn out-related behaviours was more common than illegal street racing. 144 Hooning behaviours
Table 4.18 reports the correlations between the additional social learning theory variables and frequency of hooning behaviour in the previous month and intentions regarding hooning behaviour in the next month.
Table 4.18 Bivariate correlations (Pearson’s correlation coefficient) between additional social learning theory variables and frequency and intentions regarding hooning behaviours
Frequency Intentions N Burn outs Racing Burn outs Racing Differential association 235 .26*** .39*** .44*** .52*** Behavioural 290 .29*** .40*** .46*** .51*** Normative 235 .19** .28*** .31*** .39*** Imitation 290 .17** .17** .31*** .26*** Differential reinforcement 228 .25*** .38*** .40*** .45*** Rewards 228 .23*** .32*** .38*** .37*** Social 235 .19** .29*** .26*** .30*** Non-social 228 .18** .23*** .37*** .31*** Punishments 228 -.17** -.31*** -.28*** -.37*** Social 228 -.13 -.21*** -.22*** -.31*** Non-social 228 -.19** -.35*** -.33*** -.35*** Instrumental 228 -.03 -.17** -.01 -.12 Absence of punishment 235 .18** .24*** .23*** .30*** Overall balance 228 .23*** .32*** .41*** .42*** Definitions 231 .22*** .42*** .26*** .39*** * p < .05; ** p < .01; *** p < .001
These results supported hypothesis 3, as all of the social learning theory variables were associated with frequency of hooning behaviours in the previous month and intentions to engage in hooning behaviours in the next month, with the exception of instrumental punishments (where scores were only weakly related to frequency of illegal street racing in the previous month) and social punishments, which was not related to frequency of noise and smoke-related hooning behaviours in the previous month. All relationships were in the direction expected by the theory. Differential association and differential reinforcement appear to be the most important components of social learning theory, as these variables had the strongest correlations with frequency of hooning behaviour and intentions to engage in Hooning behaviours 145 hooning behaviours in the next month. It was generally the case that correlations were stronger for future intentions than for frequency of current hooning behaviour, and correlations were also generally stronger for illegal street racing than for noise and smoke-related hooning behaviours.
4.3.5.3 Driver thrill-seeking
Driver thrill-seeking scores were calculated according to authors’ instructions by averaging the eight item scores. The mean driver thrill-seeking scale score was 7.89 (SD = 1.96). Cronbach’s alpha was adequate at .82 (N = 243). Table 4.19 presents the bivariate correlations between driver thrill-seeking scores and the main dependent measures of frequency and intentions regarding noise and smoke-related hooning behaviours and illegal street racing. In terms of the hypotheses, hypothesis 4 was partially supported by these results, as driver thrill-seeking scores were only significantly associated with intentions regarding future hooning behaviour. It was found that participants who had high scores on the driver thrill-seeking scale reported stronger intentions to engage in hooning behaviours of either type in the next month.
Table 4.19 Bivariate correlations (Pearson’s correlation coefficient) between driver thrill- seeking scores and frequency and intentions regarding hooning behaviours (N = 243)
Frequency Intentions Burn outs Racing Burn outs Racing Driver thrill-seeking scale .06 .12 .28*** .30*** * p < .05; ** p < .01; *** p < .001
4.3.5.4 Multivariate analyses
Hypotheses 5 through 7 were tested using hierarchical regression analyses. However, the analyses reported throughout section 4.3 have shown that a number of demographic and driving history variables were significantly associated (bivariately) with hooning behaviour. To account for shared variance between these variables and the theoretical predictor variables (see Appendix C.4) in the tests of these 146 Hooning behaviours
hypotheses, additional study variables were included in the analyses. As some of the significant relationships observed in this study were weak, only those with bivariate relationships greater than r = .20 with at least one of the dependent measures were included10, meaning that no demographic variables were included in analyses. Four hierarchical multiple regression analyses were performed to test the hypotheses with each of the dependent measures. As noted in section 4.1.1.2, the order in which variables were entered into the analyses was consistent with the relevant hypotheses. Prior to the entry of theoretical variables, driving history variables were entered as control variables at Step 1: driving hours per week; involvement in burn out-related crashes (dichotomous); involvement in illegal street racing-related crashes (dichotomous); self-reported speeding in the last month; and self-reported driving a vehicle with defects / illegal modifications in the last month. To test hypothesis 5, the expanded deterrence theory variables were added at Step 2, and the additional social learning theory variables were added at Step 3 to test hypothesis 6. Finally, driver thrill-seeking scores were entered at Step 4 to test hypothesis 7. The results of these analyses are reported in Table 4.20 for noise and smoke-related hooning behaviours, and Table 4.21 for illegal street racing. Correlation matrices presented in Appendix C.4 revealed no evidence of multicollinearity, as none of the correlations between predictors approached perfect. For the frequency of noise and smoke-related hooning behaviour, the driving history variables (Step 1) explained 3.3% of the variance in frequency of this behaviour. Consistent with hypothesis 5, when the expanded deterrence variables were added at Step 2, the explained variance was significantly increased to 10.6%. Consistent with hypothesis 6, when the additional social learning theory variables were added at Step 3, the explained variance again significantly increased, to 13.5%. Finally, hypothesis 7 was supported, as the addition of driver thrill-seeking scores at Step 4 did not explain significant additional variance. The entire model explained 13.3% of variability in self-reported frequency of noise and smoke-related hooning behaviour in the last month, which is quite low.
10 All theoretical predictors were included, regardless of the bivariate correlations with the dependent measures. Hooning behaviours 147
Table 4.20 Hierarchical regression analyses for noise and smoke-related hooning behaviours (N = 228)
Frequency Intentions B SE β B SE β Step 1 Driving hrs/wk .010 .005 .137 .014 .009 .101 Burn out-related crashes -.120 .222 -.037 .291 .361 .051 Racing-related crashes -.155 .354 -.030 .235 .577 .025 Self-reported speeding -.004 .056 -.005 .140 .090 .108 Self-rep. veh. def. / ill. mods -.001 .036 -.002 -.012 .059 -.013 Adj. R2 .033, F(5, 222) = 2.57* .119, F(5, 222) = 7.12*** Step 2 Punishment experience Number of offences .583 .172 .427*** .519 .280 .216 Impoundment (self) -1.808 .796 -.317* -2.070 1.298 -.206 No. people with offences -.047 .053 -.064 -.027 .086 -.021 Punishment avoidance Avoidance score (self) -.674 .341 -.244 -.533 .556 -.109 Use of strategies (self) -.005 .094 -.006 .068 .153 .041 Use of strategies (others) -.083 .085 -.095 -.094 .139 -.062 Likelihood of detection Direct -.109 .086 -.097 -.006 .141 -.003 Indirect .026 .063 .032 -.110 .102 -.076 Perceived certainty Direct .105 .045 .182* .196 .073 .193** Indirect -.100 .065 -.148 -.079 .106 -.066 Perceived swiftness Direct -.066 .047 -.101 -.109 .077 -.096 Indirect -.017 .056 -.027 .118 .091 .105 Perceived severity Direct -.077 .084 -.066 -.144 .137 -.070 Indirect .106 .065 .148 -.029 .106 -.023 Adj. R2 .106, F(19, 208) = 2.42*** .168, F(19, 208) = 3.41*** 2 ∆ Adj. R .073, Fchange(14, 208) = 2.29** .049, Fchange(14, 208) = 1.94* Step 3 Differential association .174 .098 .161 .452 .160 .238** Imitation .020 .053 .026 .143 .086 .105 Differential Reinforcement .054 .132 .043 .265 .214 .118 Definitions .134 .124 .098 -.041 .202 -.017 Adj. R2 .135, F(23, 204) = 2.55*** .252, F(23, 204) = 4.32*** 2 ∆ Adj. R .029, Fchange(4, 204) = 2.75* .084, Fchange(4, 204) = 6.82*** Step 4 Driver thrill-seeking -.028 .044 -.047 .112 .072 .106 Adj. R2 .133, F(24, 203) = 2.45*** .257, F(24, 203) = 4.27*** 2 ∆ Adj. R -.002, Fchange(1, 203) = 0.41 .005, Fchange(1, 203) = 2.44 * p < .05; ** p < .01; *** p < .001 Note: Coefficients in table are those for Step 4. 148 Hooning behaviours
The most important (and only significant) predictors in the model were the number of noise and smoke-related offences in the previous three years (such that people with higher offence scores also reported higher frequency), personal experience with vehicle impoundment for hooning (such that drivers who had experienced impoundment reported lower frequency), and perceived certainty of punishment for themselves (such that people who thought impoundment was more certain reported higher frequency). As noted in the description of the results presented in Table 4.15, the positive relationship between frequency of noise and smoke-related hooning behaviour and number of previous offences is contrary to deterrence principles, and possibly reflects an exposure effect, in that the more someone engages in a behaviour (i.e., the higher frequency), the more likely it is that they will be caught. Similarly, the finding for certainty of punishment is also in the opposite direction to what would be expected under deterrence principles. Perhaps this is related to the number of offences the person has, and is also indirectly measuring exposure. The study variables were able to explain more variance in intentions regarding noise and smoke-related hooning behaviours in the next month. The driving variables entered at Step 1 explained 11.9% of the variance, and the addition of expanded deterrence theory variables at Step 2 significantly increased the variance explained to 16.8%, supporting hypothesis 5. Supporting hypothesis 6, the additional social learning theory variables explained significant additional variance (4.9%) when entered at Step 3. Consistent with hypothesis 7, driver thrill-seeking scores did not add significant explanation when entered at Step 4. The model explained 25.7% of variance in intentions to engage in noise and smoke-related hooning behaviours in the next month. The significant predictors in the model were the differential association component of social learning theory (such that people who perceived that their significant others held positive attitudes towards noise and smoke-related hooning behaviours were more likely to intend to engage in noise and smoke-related hooning behaviours in the next month), and perceptions of certainty of punishment (such that people who were more certain that their vehicle would be impounded if caught reported stronger intentions to hoon in future). When hierarchical regression analyses were conducted for the illegal street racing dependent measures reported in Table 4.21, it was found that for the frequency of illegal street racing in the previous month dependent measure, the Hooning behaviours 149 driving history variables (Step 1) explained 6.4% of the variance in frequency of this behaviour. When the expanded deterrence variables were added at Step 2, the explained variance was significantly increased to 13.7%, supporting hypothesis 5. Consistent with hypothesis 6, when the additional social learning theory variables were added at Step 3, the explained variance again significantly increased to 24.4%. Finally, hypothesis 7 was also supported, as the addition of driver thrill-seeking scores at Step 4 did not add significant variability to the model, as the total model explained 24.1% of variability in frequency of illegal street racing in the last month. The most important (and significant) predictors in the model were punishment avoidance, the definitions and differential associations components of social learning theory, involvement in illegal street racing-related crashes, and the number of hours driven per week. The results showed that higher frequency of illegal street racing scores were associated with: avoiding vehicle impoundment when caught illegal street racing; having positive attitudes towards illegal street racing; perceiving that significant others have positive attitudes towards illegal street racing; having at least one crash while illegal street racing in the previous three years; and driving a high number of hours per week. For intentions regarding illegal street racing in the next month, the driving variables entered at Step 1 explained 9.5% of the variability in the data. When the expanded deterrence variables were entered at Step 2, the explanatory power of the model significantly increased to 22.2%, consistent with hypothesis 5. Supporting hypothesis 6, the additional social learning theory variables explained 12.7% of additional variability in the data. Contrary to hypothesis 7, the inclusion of driver thrill-seeking scores at Step 4 added significant explanation of variance, although at 1% this addition was very small. The full model explained 35.9% of variability in intentions to engage in illegal street racing in the next month. The most important (and significant) predictors in the model were the differential association component of social learning theory, followed by the use of punishment avoidance strategies themselves, the use of punishment avoidance strategies by friends, punishment experience, punishment avoidance, perceived likelihood of detection for others, and driver thrill-seeking scores.
150 Hooning behaviours
Table 4.21 Hierarchical regression analyses for illegal street racing (N = 228)
Frequency Intentions B SE β B SE β Step 1 Driving hrs/wk .010 .004 .143* .007 .007 .055 Burn out-related crashes -.205 .190 -.067 -.176 .312 -.032 Racing-related crashes .729 .316 .147* .685 .519 .078 Self-reported speeding -.083 .048 -.119 .045 .078 .036 Self-rep. veh. def. / ill. mods .011 .031 .022 .048 .051 .055 Adj. R2 .064, F(5, 222) = 4.11*** .095, F(5, 222) = 5.79*** Step 2 Punishment experience Number of offences -.219 .243 -.099 -.263 .398 -.066 Impoundment (self) 1.835 1.078 .155 4.989 1.770 .236** No. people with offences -.008 .047 -.011 -.002 .077 -.002 Punishment avoidance Avoidance score (self) 1.000 .499 .228* 1.691 .820 .216* Use of strategies (self) .072 .093 .090 .459 .153 .319** Use of strategies (others) -.122 .091 -.155 -.376 .150 -.267* Likelihood of detection Direct -.056 .072 -.055 .080 .118 .044 Indirect -.003 .051 -.004 -.190 .084 -.146* Perceived certainty Direct .039 .039 .075 .016 .064 .017 Indirect -.134 .069 -.204 -.130 .114 -.111 Perceived swiftness Direct .061 .047 .086 -.019 .078 -.015 Indirect .002 .061 .003 .155 .100 .140 Perceived severity Direct .014 .067 .014 .102 .111 .056 Indirect .099 .056 .148 -.038 .092 -.032 Adj. R2 .137, F(19, 208) = 2.89*** .222, F(19, 208) = 4.41*** 2 ∆ Adj. R .073, Fchange(14, 208) = 2.33** .127, Fchange(14, 208) = 3.58*** Step 3 Differential association .183 .086 .187* .674 .141 .384*** Imitation .018 .048 .025 -.007 .079 -.005 Differential Reinforcement .072 .117 .062 .082 .191 .040 Definitions .265 .103 .227* .025 .170 .012 Adj. R2 .244, F(23, 204) = 4.19*** .349, F(23, 204) = 6.28*** 2 ∆ Adj. R .107, Fchange(4, 204) = 8.42*** .127, Fchange(4, 204) = 11.13*** Step 4 Driver thrill-seeking -.016 .038 -.029 .132 .063 .130* Adj. R2 .241, F(24, 203) = 4.01*** .359, F(24, 203) = 6.31*** 2 ∆ Adj. R -.003, Fchange(1, 203) = 0.182 .010, Fchange(1, 203) = 4.40* * p < .05; ** p < .01; *** p < .001 Note: Coefficients in table are those for Step 4.
Hooning behaviours 151
It was found that stronger intentions to take part in an illegal street race in the next month were associated with: perceiving that significant others have positive attitudes towards illegal street racing; successfully using punishment avoidance strategies; having friends who have not been successful in using punishment avoidance strategies; experiencing vehicle impoundment for an illegal street racing offence; avoiding vehicle impoundment when caught for an illegal street racing offence; perceiving that others are unlikely to be detected for an illegal street racing offence; and high driver thrill-seeking scores. While the findings relating to differential association, driver thrill-seeking, perceived likelihood of detection for others and use of punishment avoidance strategies for themselves were in expected directions, the results for the punishment experience and punishment avoidance variables were somewhat contradictory. It is counterintuitive that both the experience of vehicle impoundment and avoidance of vehicle impoundment should both be positively related to intentions to street race in the future. Further, the successful use of punishment avoidance strategies by friends was significantly related to intentions to street race in the future, but in the opposite direction to what would be expected according to deterrence principles.
4.4 Discussion
The overall purpose of Study 1, described in this and the previous chapter of this thesis, was to explore the factors associated with hooning behaviours using a sample of drivers who report engaging in these behaviours. This also allowed an exploration of the effectiveness of current approaches to dealing with hooning, which in Queensland involves a vehicle impoundment and forfeiture program, from the perspective of targeted drivers whose behaviour puts them at-risk of experiencing this penalty. This study involved the development and administration of a quantitative instrument, based on the review of the literature in Chapter 2, and the results of Study 1a reported in the previous chapter. Participant responses to this survey were used to address a number of research questions.
4.4.1 Status of hypotheses
This study tested hypotheses related to all of the key research questions in 152 Hooning behaviours
this program of research. The results of these hypotheses will be discussed in the order of the key research question to which they relate.
4.4.1.1 RQ1: Who engages in hooning in an Australian context?
This research question was addressed by hypothesis 1, where it was predicted that drivers involved in hooning would be predominantly young males working in trade professions. Consistent with the previous illegal street racing research reviewed in section 2.2 of this thesis, the typical participants in this study were young males, and tradesperson was the most common occupation group. If the sample of this study is representative of the population of drivers who engage in hooning behaviours (and it appears that they may be, as the age and gender characteristics of this sample are similar to those of the offenders in Studies 2 and 3), then this study has found support for this hypothesis. However, it is important to note that the sample did not consist entirely of young, male tradesmen. While this may represent the typical hooning driver, it is important not to ignore the atypical hooning driver in attempts to understand the behaviour and develop countermeasures to reduce hooning. Further, there are other key variables, such as attitudes, motivations and personality characteristics, which could be used to assess the representativeness of samples, which was not possible in this research due to the limited nature of data collected regarding hooning offenders.
4.4.1.2 RQ2: What are the legal, social and psychological factors that contribute to hooning behaviour?
This research question was explored by hypotheses 2 through 7. Legal factors contributing to hooning behaviours were explored in hypothesis 2, which was not fully supported by the results. While there were some (small) significant relationships between expanded deterrence theory variables and the dependent measures, these were sometimes in the opposite direction than expected. For example, high numbers of previous hooning offences for participants and their friends were associated with higher frequency and intentions scores. However, one could argue that these results are understandable, as the more someone engages in a behaviour, the more chance they have of being caught and punished (and, therefore, Hooning behaviours 153 the more chance of having a high number of offences). Consistent with the theory and previous research (Freeman & Watson, 2006; Gee Kee, 2006; Gee Kee et al., 2007; Watson, 2004c), punishment avoidance was the most important component of the expanded deterrence theory variables, although effect sizes for all significant correlations were small. Finally, the relationships between perceived likelihood of detection (for self and others) and the self-reported frequency and future intentions relating to illegal street racing may indicate that increasing perceptions of detection (e.g., through increased visible enforcement and/or public education campaigns designed to increase awareness about the enforcement of hooning laws and therefore risk of detection) may be useful strategies to reduce hooning behaviour. Social factors contributing to hooning behaviours were explored using additional social learning theory variables. Hypothesis 3 was supported, as all social learning theory variables were associated with frequency of hooning behaviour and intentions to engage in hooning in the future, with the exception of instrumental punishments, which was only associated with frequency of illegal street racing in the previous month, and social punishments, which was not associated with frequency of noise and smoke-related hooning behaviours in the previous month. The strength of these relationships ranged from small to moderate, and were all in the direction expected by social learning theory, as high frequency and intentions scores were associated with: perceiving that significant others have positive attitudes towards hooning behaviours (differential association); having more models of hooning behaviours (imitation); perceiving that more rewards are likely to result from hooning behaviour than punishments (differential reinforcement); and positive attitudes towards hooning behaviours (definitions). Hypothesis 4 was partially supported in this study, as drivers with high scores on the driver thrill-seeking scale reported strong intentions to engage in hooning behaviour in the next month. However, it was noted that these relationships, although significant, were small. For hypotheses 2 through 4, relationships between study variables and future intentions were generally stronger than those observed between study variables and current hooning behaviour. This was also the case for the hierarchical regression analyses conducted to test hypotheses 5 through 7, as the models explained more variance in intentions to engage in hooning behaviours than variance in frequency scores. Also consistent with the results of hypotheses 2 through 4, the regression 154 Hooning behaviours
models explained more variance in illegal street racing dependent measures than those for noise and smoke-related hooning behaviours. Hypothesis 5 was supported by the results of the hierarchical regression analyses, as it was the found that the expanded deterrence theory variables explained significant variability in all of the dependent measures over and above that already explained by the driving history variables that were related to the dependent measures. The most important components of the theory (i.e., those with the highest beta values, and significant beta values across more of the four dependent measures) appeared to be punishment avoidance and punishment experience, while perceived likelihood of detection and perceived certainty of punishment were important for some dependent measures. Hypothesis 6 was supported by the results for all dependent measures, as the additional social learning theory variables explained significant variability above that already explained by expanded deterrence theory variables and the driving history variables that were significantly related to hooning behaviours in bivariate analyses. The most important components of the theory were differential association and definitions. The support of this hypothesis suggests that a purely legal perspective encapsulated in the expanded deterrence theory is insufficient to fully understand hooning behaviours, as the influence of others was shown to be important in this study. These results also highlight the utility of incorporating non-legal perspectives in understanding hooning behaviour, and may be useful in identifying potential targets for intervention. Hypothesis 7 was also supported by the results, highlighting the comprehensive nature of social learning theory, and supporting Akers’ (1990) assertion that the model incorporates driver thrill-seeking. Driver thrill-seeking scores did not add significant explanation of variance in dependent measures after driving history, expanded deterrence theory and additional social learning theory variables were entered into the regression analyses, with the exception of intentions to illegal street race in the next month, where these scores added only 1% explanation to the model. Taken together, the results relating to this research question suggest that there are a variety of legal, social, and psychological factors that are associated with hooning behaviours. Further, the difference in results between the types of hooning behaviours as divided for the purposes of this research highlights the diversity of the Hooning behaviours 155 behaviours grouped together under the collective label of hooning in Australia. Thus it is unlikely that a single approach to dealing with this complex issue is likely to be effective. An understanding of the complexities of the behaviours and varied factors contributing to them is imperative to effectively dealing with the issue and developing countermeasures. Although it was beyond the scope of this research, future studies should explore in more detail how these factors interrelate, and in particular how significant others influence hooning behaviour, to inform interventions. It is also important to note that, generally, correlations between predictors and frequency of hooning behaviours were lower than those between the predictors and intentions regarding future behaviour. This may suggest that frequency scores were less sensitive than intention scores, as participants were likely to experience more difficulty remembering how many times they performed a behaviour in the past, as opposed to rating their intentions to engage in the same behaviours in the future. Thus intentions scores may be more reflective of a general disposition to engage in hooning that is more sensitive than the frequency scores, leading to better quality data for analysis and clearer statistical outcomes. Further, the predictors explained a relatively low proportion of variance in frequency scores for burn out-related hooning behaviours, which may be reflective of the lack of sensitivity concerns discussed above, or highlight the complexity of these behaviours. That is, in addition to the broad group of factors assessed in this research, it appears that a considerable proportion of variance in frequency of hooning behaviours is influenced by other factors.
4.4.1.3 RQ3: What are the road safety implications of hooning behaviours?
This research question was addressed by hypothesis 8, which was supported in this study, as drivers who had been involved in at least one noise and smoke- related crash in the last three years had significantly higher scores on the future intentions dependent measures than drivers who had not. Further, drivers who had been involved in at least one illegal street racing-related crash had higher scores on the illegal street racing dependent measures. Although only a small percentage of participants reported being involved in hooning-related crashes, the association between hooning behaviour and hooning-related crashes suggests that engaging in 156 Hooning behaviours
hooning behaviour increases the risk of being involved in a hooning-related crash. Further, the percentage of drivers reporting that they had been involved in a hooning- related crash was comparable to the general crash involvement of participants sampled from the general driving population in Queensland in a similar time period (Centre for Accident Research & Road Safety - Queensland, 2008; Fleiter, 2010), indicating that the involvement of hooning in crashes is actually quite high. This study also explored other high risk driving behaviours that participants engage in (discussed in section 4.4.1.4). However, future research should explore the extent to which people engage in these other high risk behaviours while engaging in hooning. For example, such research should explore issues such as seatbelt use and impaired driving while hooning, as the combination of high risk road user behaviours may further increase the road safety implications of hooning behaviours. Such research may facilitate the development of education programs.
4.4.1.4 RQ4: Do drivers who engage in hooning also engage in other risky driving behaviours?
This research question was addressed by hypotheses 9 and 10. Consistent with hypothesis 9, self-reported frequencies of engaging in some types of other illegal driving behaviour, and previous traffic offences, were associated with hooning behaviours. The most important other driving behaviours (i.e., those that were associated with most dependent measures, and most strongly) were speeding and vehicle defects. Speeding offences in the last three years and self-reported speeding in the last month were positively associated with intentions regarding both types of hooning behaviours, and frequency of frequency of illegal street racing in the previous month. Self-reported frequency of driving vehicles with defects was positively associated with illegal street racing dependent measures, while vehicle defect offences were associated with both intentions variables and the frequency of illegal street racing in the previous month. There were also other significant relationships between traffic offences and self-reported illegal behaviour and the dependent measures, although effect sizes were small. These results suggest that drivers who engage in hooning behaviours frequently and intend to continue engaging in hooning in the next month are more likely to engage in other illegal driving behaviours, and have other traffic offences. That is, drivers who engage in Hooning behaviours 157 hooning behaviours appear to engage in other risky driving behaviours, particularly related behaviours such as speeding and driving vehicles with defects or illegal modifications. However, hypothesis 10 was not supported by the results, as contrary to the results of hypothesis 8 regarding hooning-related crashes, there were no significant relationships between general crash-involvement and any of the hooning behaviour dependent measures.
4.4.1.5 RQ5: How effective are vehicle impoundment and forfeiture programs at reducing hooning behaviour?
The final research question in this study was addressed by hypotheses 11 and 12. Hypothesis 11 was partially supported by the results, as penalties for hooning behaviours are perceived as severe, but the results for certainty of punishment were mixed. While participants were generally certain that other people would have their vehicle impounded if caught for a hooning offence, they only perceived it was certain that their own vehicle would be impounded for an illegal street racing offence. On average, participated perceived the chances of their vehicle being impounded for a noise and smoke-related hooning offence to be even chance. Regarding hypothesis 12, there is some evidence that drivers who engage in hooning behaviours have reduced their hooning in response to Queensland’s vehicle impoundment and forfeiture laws for hooning, as many participants reported engaging in hooning less as a successful punishment avoidance strategy. However, strategies such as moving the location of hooning behaviour were more strongly reported.
4.4.2 Implications for policy and practice
The results of this study suggest that there are other factors that influence the decision to engage in hooning behaviours besides an evaluation of the risks of legal punishment. Further, these results suggest that purely legal approaches to dealing with hooning behaviours are unlikely to be successful in dealing with the problem, as they are unable to address the non-legal factors this study has demonstrated are associated with hooning. However, it was noted earlier in this chapter that when it 158 Hooning behaviours
appears that laws are not effectively deterring behaviour, it is common for policymakers to be encouraged to increase the severity of the penalty. While the results of this study indicate that increasing penalty periods are associated with increased perceptions of severity, these perceptions were not related to current frequency of hooning behaviour, or future intentions. Previous road safety research has found similar results when using deterrence theories, where perceived severity was unrelated (e.g., Watling et al., 2010; Watson, 2004b) or positively related (e.g., Fleiter, Watson, Lennon, King, & Shi, 2009; Gee Kee et al., 2007) to illegal behaviour, whereas punishment avoidance was a stronger predictor of future behaviour (e.g., Fleiter & Watson, 2006; Freeman & Watson, 2006; Watling et al., 2010; Watson, 2004b). Previous road safety literature exploring deterrence principles has concluded that increases in punishment severity are unlikely to affect behaviour unless they are accompanied by increasing the perception of detection and certainty of punishment (Briscoe, 2004; Nichols & Ross, 1990; von Hirsch, Bottoms, Burney, & Wikstrom, 2000). This is important in light of the results of this study, where perceptions of the likelihood of detection were related to hooning (particularly illegal street racing) behaviour, and it was suggested in section 4.4.1.2 that these perceptions represent a potential target for intervention. The significant variance in intentions regarding future hooning behaviour predicted by social learning theory variables over and above expanded deterrence theory variables indicates that it may be necessary to target non-legal factors in conjunction with deterrence-oriented initiatives in order to enhance the likelihood of a hooning countermeasure succeeding. From this study, it can be surmised that while punishment is generally seen as severe, the non-legal benefits of engaging in hooning behaviours appear to outweigh the threat of punishment. Participants in this study were asked about their intentions to flee from police in order to avoid the various penalty periods for hooning offences. While these responses may not reflect their true intentions (or their actual behaviour), given that they were purely hypothetical for the majority of participants who did not have a previous hooning offence and, therefore, were not eligible for the longer impoundment and forfeiture periods, participant responses were concerning. While relatively few participants reported a willingness to flee to avoid the initial 48 hour impoundment period, willingness significantly increased with each increase in the penalty period. These results are concerning because if people have a desire to flee Hooning behaviours 159 from police to avoid losing their vehicles, and act on this desire, they may be putting themselves, the police, and other road users in more serious danger than the hooning offence that attracted the attention of police in the first place. Queensland, like other jurisdictions, has strict protocols regarding police pursuits to minimise risk to road users. However, it is important for police to be aware that repeat hooning offenders may be motivated to flee, and to consider this risk when enforcing hooning laws. It is common practice in Queensland for some hooning offences to be video- recorded and followed up a later date. For example, police with the Traffic Response Group often patrol known hooning areas in unmarked vehicles and when they detect an illegal street race, they video the event and all participants for identification and processing at a later time. This allows them to follow up and charge all of the offenders, rather than intercepting only one vehicle while the others are able to evade apprehension. While this approach may compromise the swiftness component of deterrence principles, such an approach may be safer if repeat hooning offenders are detected, to avoid a high-speed pursuit and potential harm. Queensland also has clear guidelines regarding police pursuits, and can impose severe additional penalties (including vehicle impoundment) for drivers who evade police. This study found that one fifth of participants had been involved in a hooning-related crash, which is indicative of the road safety implications associated with hooning behaviour, particularly when compared to the findings of other research with the general population of drivers, where a similar proportion of participants from South East Queensland (Fleiter, 2010) and crash-involved drivers in North Queensland (Centre for Accident Research & Road Safety - Queensland, 2008) reported general crash involvement of 20% or less over the same or longer time period respectively. However, given that more participants reported general crash involvement, and involvement in other illegal driving behaviours (and traffic offences) was common, it could be argued that it is the hooning driver that represents the better target for intervention, rather than hooning behaviours per se posing the greatest road safety risk11. However, regardless of the extent to which hooning behaviours are a road safety problem, they appear to represent a significant public nuisance, based on public complaints and media coverage.
11 The risk associated with the hooning driver was explored in Study 2b of this program of research. 160 Hooning behaviours
4.4.3 Strengths and limitations
The results of this study should be interpreted with the strengths and limitations of the design in mind. The major strength of this study, like Study 1a, was that it was the first study to explore the perceptions and self-reported driving behaviour of a large sample of drivers who engage in hooning behaviours. Previous hooning research has recruited from the general community, resulting in only small sub-samples of drivers who engage in hooning. The specific targeting of drivers who have recently engaged in hooning allowed a large number of study variables and theoretical frameworks to be explored with adequate statistical power. However, as discussed in the previous chapter that described Study 1a, it is possible that the targeting of drivers who have engaged in hooning recently introduced a bias, in that these drivers could be described as not being deterred. To address this, the sample could have been recruited from the general population of drivers (as in previous research), or an attempt could have been made to recruit participants who have engaged in hooning at some point in the past (not necessarily the previous month as in this study and Study 1a), allowing for a comparison between drivers who no longer engage in the behaviour (who could be described as the deterred) and those who still participate in hooning behaviours (who could be described as the undeterred). It is important to acknowledge that recruitment such as this would be difficult in terms of screening and accurately classifying participants. Further, there may be a bias in classifying people who no longer engage in hooning as being successfully deterred, as they may have ceased their participation for other reasons. Instead it was of interest in this program of research to better understand drivers who engage in hooning and are at-risk of experiencing Queensland’s vehicle impoundment and forfeiture laws for hooning. While this may have biased the sample as it is more likely to include hard-core, undeterred drivers, the sample still demonstrated sufficient variability to allow relationships between study variables to be explored. Finally, there are benefits for researchers and policymakers alike in focussing on drivers who do not comply with laws and continue to engage in illegal behaviours despite the threat of severe penalties. There may have been a selection bias in this study, such that the people who volunteered to participate are not representative of the population of hooning drivers. Hooning behaviours 161
Similar to Study 1a, there were responses to some of the calls for participants on online forums that suggested people were concerned about the potential legal ramifications of their participation. However, as the population of drivers who engage in hooning behaviours is unknown, there is no accurate way of assessing the extent of any selection bias. The responses to the survey indicate that any bias may be minimal, given the willingness of participants to report engaging in illegal behaviours. Also, people often replied to these concerned posts on forums assuring the person that the researcher had been Googled and found to be “legit”, and many forums included posts from participants reassuring others that the call for participants was not a covert police operation, and that they had participated without legal consequences and received their movie tickets in the mail as promised. Self-report data can also be biased. Participants can demonstrate a social desirability bias and under-report their illegal behaviour, or exaggerate it. They may also give inaccurate responses due to poor recall, not reading the questions properly (or misunderstanding them), or exhibit response set bias in order to complete the survey and be eligible for the small thank you gift. Again, it is difficult to assess the extent to which these possibilities affected the results of this study, although this chapter has discussed the strategies employed to make the survey as clear and user- friendly as possible, and attempts to identify response sets. However, the use of self- report data can also be considered a strength, as it gives a more accurate estimate of the true frequency of illegal behaviour than official data. For example, responses to the crash questions showed that there are many occasions when crashes are not reported. Further, self-reported frequencies of engaging in illegal driving behaviours far exceeded offences. Thus, the use of a self-report design was the only means of obtaining the data required to better understand the factors associated with hooning behaviours, and the effectiveness of the vehicle impoundment and forfeiture laws, from the perspective of the targeted driver. In terms of limitations of the statistical analyses, the large number of variables in the hierarchical regression analyses reduced power, as did the significant relationships between predictor variables (although there were no strong correlations indicative of multicollinearity). While the issue of power can be addressed with a larger sample size, this would increase the problem of Type I errors for bivariate correlations (i.e., many of the significant correlations in this study were small, and increasing sample size may result in even smaller relationships becoming statistically 162 Hooning behaviours
significant). It may be more appropriate to use practical significance cut-offs (e.g., effect size) rather than statistical significance if larger samples are used. Finally, it is acknowledged that some of the Cronbach’s alphas for scales created for use in this research were low.
4.5 Chapter summary
Study 1b involved the development and administration of a quantitative survey designed to explore the factors associated with hooning behaviour, and the effectiveness of the vehicle impoundment and forfeiture program in Queensland from the perspective of drivers who have recently engaged in hooning and are therefore at-risk of being penalised under these laws. The results of this study revealed that there are a number of factors associated with hooning, and that there are differences between the behaviours grouped together under the common label of hooning. It is important to acknowledge this complexity when designing countermeasures, as these results suggest that a single, legal-oriented approach is unlikely to successfully deter a complex group of people from engaging in a complex group of behaviours that provide differing benefits and risks for the individual. This study also found that legal factors are not as important as other factors, such as the differential association component of social learning theory. This indicates that non-legal approaches to dealing with hooning may be required in addition to current laws. This study and Study 1a explored hooning behaviours and countermeasures to deal with hooning from the targeted drivers’ perspective. The focus of this thesis now narrows to drivers caught and punished for a hooning offence in Queensland, and the analysis of official traffic offence and crash data sources, to explore the research aims of this thesis.
Hooning behaviours 163
CHAPTER 5: STUDY 2A – THE CHARACTERISTICS OF HOONING OFFENDERS AND OFFENCES
5.1 Introduction
The literature profiling drivers reviewed in section 2.2 focussed on illegal street racers. However, hooning in an Australian context encompasses a broader group of behaviours than street racing alone. Thus, the main aim of this study was to contribute to limited body of knowledge in the area by systematically profiling hooning offenders and their offences. Profiling the problem will result in a better understanding of the nature of the problem and involved drivers, and can also provide insight into the road safety implications of hooning behaviour. For example, it would be valuable to determine the proportion of hooning offences that have resulted in a crash. The profile generated in this study was also used to select the appropriate comparison group for the case / comparison Study 2b (described in the next chapter), where the road safety implications of hooning were explored from the drivers’ perspective using official driving and crash records. Thus this study addressed the first research aim of this thesis, which was to investigate the road safety implications of illegal street racing and associated (hooning) behaviours. An important difference between this study and Studies 1a and 1b (described in the previous two chapters) is that the sampling population for those studies was drivers who reported engaging in hooning behaviours in Queensland. That is, they focussed on drivers who had not necessarily been detected and punished for hooning, but who engage in driving behaviours that mean they are eligible for punishment under Queensland’s vehicle impoundment and forfeiture laws for hooning. In contrast, the sampling population for this study was limited to drivers detected and punished for a hooning offence on Queensland’s roads.
5.1.1 Hypotheses
This study examined two of the key research questions of this program of research (RQ1 and RQ4). Specific hypotheses were developed to address these research questions, and are outlined below. 164 Hooning behaviours
5.1.1.1 RQ1: Who engages in hooning in an Australian context?
As this study focussed on drivers detected and punished for hooning offences in Queensland, this study explored this research question in terms of who is involved in hooning offences in Queensland. Based on the previous literature reviewed in section 2.2, and the characteristics of drivers involved in hooning generally that participated in Studies 1a and 1b, it was predicted that:
H1: Hooning offenders will be predominantly young males
5.1.1.2 RQ4: What are the road safety implications of hooning behaviours?
There was some information regarding crashes that occurred during the hooning offences in this dataset that allowed the exploration of the proportion of hooning offences that result in crashes. As there are no data of this type available in the published literature, there was no specific hypothesis tested.
5.1.1.3 Additional analyses
This study also described other variables available in the dataset. Specifically, it was possible to describe the nature of hooning offences in Queensland (i.e., in terms of the main groups of hooning behaviours as distinguished in Queensland legislation: noise and smoke-related offences and illegal street racing), and the types of vehicles involved in hooning offences.
5.2 Method
5.2.1 Selection of sample
Since the introduction of this legislation in November, 2002 (and until the end of 2009), 5,470 vehicles have been impounded for hooning offences in Queensland (Queensland Police Service, unpublished data). However, the drivers of these vehicles are difficult to identify in official datasets. While a number of offence codes can be used for the prescribed behaviours identified as hooning offences, these offences are not unique to the hooning legislation. For example, dangerous operation of a motor vehicle does not always indicate that the offender committed a hooning Hooning behaviours 165 offence, and can be applied in other instances, such as after a road traffic crash, or in conjunction with a drink driving offence, and may not result in vehicle impoundment. This means that identifying hooning offenders in official datasets is not as simple as searching for a particular offence code, and an alternative method of identifying offenders was required. As discussed in section 2.5.1, in order to impound a driver’s vehicle for up to three months for a second hooning offence within three years, or forfeit it for a third hooning offence within three years, police must apply to a magistrate for an impoundment or forfeiture order during the initial 48 hour impoundment period. To allow police officers to identify whether a hooning offence was the first, second or third for a particular driver, from July 1, 2005 “hooning identifiers” were added to hooning offences when they were entered into the Crime Reporting Information System for Police (CRISP) database. As a consequence, it was not possible to easily identify all drivers with a hooning offence since the legislation was implemented for this research, but those who offended on or after July 1, 2005 could be searched for using this field in the CRISP database. This resulted in a sample of 834 drivers who committed one of the 848 hooning offences that occurred between July 1, 2005 and the day before the extraction date of October 1, 2006. Although this sample does not represent all hooning offenders and offences since the legislation was implemented, it does represent all offenders and offences for the 15-month time period adopted for this study. Thus, there is no reason to expect any systematic sampling bias is present. It is important to note that while some drivers in this sample were convicted of more than one offence in the dataset during this period, it is likely that more drivers within the sample would be considered “repeat” hooning offenders under Queensland legislation, that is if they had be detected and punished for one or more hooning offences prior to July 1, 2005. As a result, hooning offenders in this study were not classified as “first-time” or “repeat” offenders.
5.2.2 Data sources
Data relating to the nature of hooning offenders and their offences analysed in this study were provided by Queensland Police Service. As described in section 5.2.1, police personnel identified all drivers with a hooning offence in Queensland between July 1, 2005 and September 30, 2006 that was entered in the CRISP 166 Hooning behaviours
database. These data were downloaded and de-identified before being forwarded to the researcher. Unique codes were substituted for identifying information so it was possible to determine when an individual had multiple offences in the dataset. The variables relating to hooning offenders included: gender; age; racial appearance [as judged by attending police officer]; and occupation, which was later recoded according to the Australian Standard Classification of Occupations (2nd edition) (1997), consistent with Studies 1a and 1b. Variables relating to the offence included: description (e.g., illegal street racing; unnecessary noise and smoke); day of week the offence occurred; offence scene (e.g., street, shopping area); and modus operandi (the reporting police officer’s description of the offence). Variables relating to the vehicle used in the offence included: vehicle type; vehicle make; year of manufacture; and registration status (e.g., registered to driver; stolen).
5.2.3 Procedure
Prior to requesting the required data, clearance to conduct external research with the Queensland Police Service through Ethical Standards Command was obtained. Approval to conduct research was then obtained from the Queensland University of Technology Human Research Ethics Committee (reference number 0600000525). The research project risk assessment was also approved by the School of Psychology and Counselling Workplace Health and Safety Officer (project number 67). Queensland Police Service personnel extracted offence information from the CRISP database relating to all drivers with a hooning conviction in Queensland between July 1, 2005 and the day prior to extraction, September 30, 2006. As discussed in section 5.2.1, this time period was selected as an additional field was added to the database on July 1, 2005 allowing police to quickly determine the number of previous hooning offences on a driver’s record, to determine whether an impoundment or forfeiture order was required due to the number of previous hooning offences. The dataset was de-identified, as Queensland Police Service allocated arbitrary codes to each offence and individual to facilitate later matching with the other data sources used in this program of research. Prior to data cleaning, the dataset consisted of 983 offences. The data were cleaned to remove a small number of offences (n = 12) that Hooning behaviours 167 occurred prior to July 1, 2005, and cases that did not appear to be hooning offences, but rather represented some degree of human error in data entry (n = 24). For example, a 13-year-old girl riding a bicycle without a helmet was included as the offence was coded as dangerous operation of a motor vehicle, but had no hooning identifier code. Thus, the dataset was scrutinised more closely in an attempt to identify and delete any other incidents that did not represent hooning for the purposes of this research, but an unrelated dangerous operation of a motor vehicle or careless driving of a motor vehicle offence, with no hooning identifier code. All offences with illegal street racing or noise and smoke codes in the offence description field were retained, as the modus operandi field confirmed these descriptions. The modus operandi field was also examined for all dangerous operation of a motor vehicle and careless driving of a motor vehicle offences, and these offences were only retained if the description indicated hooning behaviour (e.g., described a street race or burn out), mentioned the hooning legislation, or specifically stated that the vehicle was impounded for a hooning offence. Thus, offences that appeared ambiguous as they did not have a racing or noise and smoke code, and also had nothing entered in the modus operandi field, were deleted. This may have resulted in eligible offenders and their hooning offences being removed from the dataset; however, it also meant that the researcher was confident that only hooning offences and offenders remained, which was imperative for the case / comparison analyses in Study 2b. The final step in the data cleaning process was to remove drivers whose offence in the Queensland Police dataset was not also present in the traffic infringement data provided by the Queensland Department of Transport and Main Roads for Study 1b. Finally, a total of 99 rows were deleted as they were either duplicate rows in the dataset (n = 8), or the offender was charged with more than one offence as part of the one incident (as indicated by a common identifier code applied by Queensland Police Service). For example, a person may be convicted of both illegal street racing and dangerous operation of a motor vehicle, and these offences were listed in separate rows with the same identifier as they were applied as the result of one incident. The final cleaned dataset consisting of 834 drivers involved in 848 offences was entered into SPSS for analysis. The alpha level adopted for all tests was p < .05. When the data violated the assumptions of the appropriate parametric test, the equivalent non-parametric test was used. Chi-square tests were performed for variables with categorical coding, and only adjusted standardised residuals (dij) 168 Hooning behaviours
greater than +/- 1.96 were interpreted and described for significant tests.
5.3 Results
5.3.1 Demographic characteristics of hooning offenders
As shown in Table 5.1, the demographic characteristics of hooning offenders in this study was consistent with the previous illegal street racing research discussed in section 2.2, as offenders were primarily young, Caucasian males.
Table 5.1 Demographic characteristics of hooning offenders
Hooning Queensland licensed
offenders (N = 834) driversa (N = 2,718,563) N % N % Gender Male 812 97.4% 1,405,795 51.7% Female 22 2.6% 1,312,768 48.3% Age group Under 17 years 6 0.7% 12,872 0.5% 17 – 20 years 437 52.4% 170,060 6.3% 21 – 24 years 207 24.8% 192,189 7.1% 25 – 29 years 104 12.5% 238,477 8.8% 30 – 39 years 61 7.3% 544,387 20.0% 40 – 49 years 18 2.2% 552,858 20.3% 50 – 59 years 1 0.1% 485,501 17.9% 60+ years 0 0.0% 522,217 19.2% Racial appearance Caucasian 762 91.7% European 24 2.9% South East Asian 13 1.6% Aboriginal 11 1.3% Pacific Islander 11 1.3% Oriental Asian 4 0.5% Indian 3 0.4% Middle Eastern 2 0.2% Other 1 0.1% Missing 3 a Source: Department of Transport and Main Roads (2009) – June 30, 2006 statistics reported. Hooning behaviours 169
The age of offenders was heavily positively skewed. The median age of offenders was 20, with more than three quarters (77.9%) of hooning offenders aged under 25, and more than half (53.1%) under 21. When compared to Queensland licensed drivers generally (using Queensland Department of Transport and Main Roads age groups), young males were significantly over-represented (all ps < .001). Table 5.2 shows the occupations of drivers in the hooning offender sample, coded according to ABS Major Codes. Where occupation was known, the most common ABS Major Codes were Tradespersons and Related Workers, Not Working (an additional group created for this program of research), and Labourers and Related Workers. These three groups accounted for more than three quarters of hooning offenders for whom occupation was known, far greater than the proportions of these occupations in the general population.
Table 5.2 Occupation of hooning offenders in Australian Standard Classification of Occupation major codes
Hooning offenders Queensland
(N = 834) wage and salary b c N % % earnersa Tradespersons and related workers 180 35.5% 47.5% 12.1% Not workingd 121 23.9%~ ~ Labourers and related workers 82 16.2% 21.6% 12.1% Intermediate production & transport workers 52 10.3% 13.7% 7.8% Elementary clerical, sales & service workers 27 5.3% 7.1% 11.2% Intermediate clerical, sales & service workers 18 3.6% 4.7% 20.2% Associate professionals 9 1.8% 2.4% 7.6% Professionals 9 1.8%2.4% 17.5% Self-employedd 7 1.4%~ ~ Managers and administrators 1 0.2% 0.3% 9.2% Advanced clerical and service workers 1 0.2% 0.3% 2.3% Not stated 327 8.3% a Source: Australian Bureau of Statistics (2009). Percentages for the known Major Codes used the known occupation codes as the denominator to allow comparisons with hooning offenders, thus the total of percentages in this column sum to 108.3% once the “Not stated” group are added. b Percentages calculated using the known occupation codes (n = 507) as the denominator. c Percentages calculated using only ABS Major Codes (n = 379) as the denominator. d These groups were created in addition to the ABS Major Codes. “Not Working” includes the unemployed, students, pensioners and retirees. “Self-employed” includes people whose occupation was listed as self-employed, owner/operator or business owner.
170 Hooning behaviours
Tradespersons and Related Workers included occupations such as automotive tradespersons (n = 56); structural construction tradespersons (n = 29), mechanical engineering tradespersons (n = 19), fabrication engineering tradespersons (n = 17), and electrical and electronics tradespersons (n = 16). The Not Working code created for this program of research was dominated by the unemployed (n = 86) and students (n = 33). Labourers and Related Workers included occupations such as labourers (n = 41), process workers (n = 11), and mining and construction labourers (n = 8).
5.3.2 Characteristics of hooning offences
Table 5.3 describes the characteristics of the 848 hooning incidents.
Table 5.3 Characteristics of hooning offences (N = 848) N % Hooning offence typea Dangerous operation of a motor vehicle 94 11.1% Careless driving of a motor vehicle 113 13.3% Racing and speed trials on roads 175 20.6% Wilfully starting or driving a vehicle in a way that causes 642 75.7% unnecessary noise or smoke Scene of hooning offence Street 807 95.2% Shopping area 17 2.0% Recreational area 6 0.7% Otherb 18 2.1% Day of week offence occurred Monday 48 5.7% Tuesday 65 7.7% Wednesday 64 7.5% Thursday 156 18.4% Friday 175 20.6% Saturday 182 21.5% Sunday 158 18.6% a Numbers and percentages of hooning offence types indicate the number and proportion of the 848 incidents that involved each type of hooning behaviour. As an incident could have more than one offence code, these values sum to more than N = 848 and 100%. b “Other” locations were hotel, restaurant, club, court, beach, garage, private grounds, and school.
Hooning behaviours 171
The most common hooning offence type was unnecessary noise and smoke, which accounted for three quarters of all hooning incidents. Illegal street racing was less common, being associated with one fifth of all hooning incidents. Almost all hooning offences were detected on public streets, and tended to occur on weekends. While these trends may reflect trends in hooning behaviour generally, it is important to note that they are also influenced by enforcement practices, and the ease with which police can substantiate the different offence types. Of the 848 hooning incidents, at least 31 (3.7%) resulted in a crash (i.e., 31 incidents had a crash described in the modus operandi field of the data in the Queensland Police Service’s CRISP database). Table 5.4 describes the nature of these crashes12 and the number of vehicles involved, and shows that crashes that occurred with a hooning offence tended to be single-vehicle crashes where the driver left the road and collided with a fixed object.
Table 5.4 Characteristics of crashes that occurred with hooning offences (N = 31) N % Crash nature Hit fixed object 20 64.5% Hit parked vehicle 3 9.7% Angle 2 6.5% Overturned 2 6.5% Head-on 1 3.2% Unknown 3 9.7% Number of vehicles involved Single-vehicle 25 80.6% Multi-vehicle 3 9.7% Unknown 3 9.7%
Crashes were less likely to occur with an illegal street racing or speed trial offence than with an excessive noise and smoke offence when only the two offence 2 types were compared, χ (1) = 5.33, p = .021, dij = -2.3, as only one crash occurred during an illegal street racing offence, whereas 28 crashes occurred during noise and smoke offences. While this data is limited in that it includes only those crashes (and
12 As this information was obtained in offence rather than crash data, further information such as crash severity was not available from this source. 172 Hooning behaviours
offences) known to police, it may suggest that the loss of traction with the road surface and therefore control of the vehicle in noise and smoke offences represents a crash risk. When all hooning offence types and crashes were explored, it was found that dangerous operation of a motor vehicle was significantly more likely to be applied when a crash occurred than when this offence was not applied, χ2 (1) =
82.29, p < .001, dij = 9.1, although it is likely that the crash itself contributed to this offence being applied in addition to the noise and smoke or illegal street racing offence. As Study 2b of this thesis involved analysis of traffic and crash information for this sample of offenders, it was possible to search the crash histories of these offenders to further investigate these hooning offence crashes. The crash data was limited in that the only date fields included were month and year. It was, therefore, assumed that crashes for the same month and year as the hooning offence most likely were for the crash that occurred during the offence. Sixteen (51.6%) of the 31 hooning offence crashes were able to be found in the Phase 2 crash records. Given that police witnessed all 31 crashes, it is likely that the remaining 15 crashes were not in the Phase 2 crash data records as they did not meet the criteria for eligibility for entry into the Road Crash Information System (i.e., no injury, or low damage bill). These 16 records were analysed in order to determine the severity of the crashes, who was injured if the crash involved a casualty, and what circumstances or contributing factors were attributed to the crash by police. Table 5.5 summarises this information. Table 5.5 shows that more than half of the crashes that occurred during a hooning offence for which the crash data file was able to be identified did not involve an injury. If the remaining 15 hooning offence crashes were eligible for entry into the database, then the proportion of non-casualty crashes would be even greater. When these crashes did involve at least one casualty, it was equally likely that it was the driver rather than passenger/s that were injured. As hooning is not a circumstance or contributing factor on crash forms in Queensland, the circumstances attributed to these crashes were described. Generally, the factors attributed to these crashes involved fault of behalf of the driver, as indicated by the most common factors being violations or driver factors.
Hooning behaviours 173
Table 5.5 Severity, casualties and circumstances / contributing factors of crashes that occurred with hooning offences (N = 16) N % Crash severity (and casualties by road user type) Fatal 0 0.0% Hospitalisation 3 18.8% Driver 2 Passenger 1 Medical treatment 3 18.8% Driver 3 Passenger 3 Minor Injury 1 6.3% Driver 1 Passenger 0 Property damage only 9 56.3% Circumstances / contributing factors a Violation – Dangerous driving 7 46.7% Violation – Undue care and attention 6 40.0% Driver – Inexperience / lack of expertise 6 40.0% Excessive speed for circumstances 5 33.3% Police chase 2 13.3% Violation – Over prescribed concentration of alcohol 2 13.3% Violation – exceeding speed limit 1 6.7% Condition – Under influence of liquor / drug 1 6.7% Driver – Fatigue related by definition 1 6.7% Road – Wet / slippery 1 6.7% No circumstances / contributing factors listed 1 a Percentages calculated using N = 15 as one crash had no circumstances / contributing factors listed
5.3.3 Application of vehicle impoundment periods for hooning offences
At the time the data for this study were extracted, there was no dedicated database for recording the details relating the length and location of the vehicle impoundment period applied to hooning offences in Queensland. However, many of the offences in this study had information relating to the impoundment of the offender’s vehicle in the modus operandi field, presented in Table 5.6.
174 Hooning behaviours
Table 5.6 Vehicle impoundment period for hooning offences (N = 848) as described in the modus operandi field of the CRISP database
N % Vehicle impounded for 48 hours 588 90.5% Impounded for 48 hrs, application for 3 month impoundment order 14 2.2% Impounded for 48 hrs, application for forfeiture order 2 0.3% Vehicle impounded, period not specified 36 5.5% Vehicle not impounded 10 1.5% No reference to vehicle impoundment in modus operandi field 198
It is important to reiterate that police only have the power to immediately impound vehicles for 48 hours for a hooning offence. If it is the drivers second or third (or subsequent) hooning offence within three years, the police officer must apply to a magistrate during the initial 48 impoundment period for an impoundment or forfeiture order. As the data in this dataset was generally recorded the same day as the offence, references to impoundment periods in these data generally related to the initial 48 hour period, but would indicate where an application for a longer impoundment period had been made. The data did not indicate whether those applications were successful. Most of the hooning offences in the dataset appear to be for first-time hooning offenders, as references to vehicle impoundment in the modus operandi field were typically 48 hour impoundment periods. The percentage of offences where applications for longer impoundment periods were sought was fairly consistent with the proportions of repeat hooning offenders in Queensland at this time, as 2.2% of impoundments up until the end of 2006 were 3 month impoundments for second hooning offences, and 0.1% of impoundments were forfeiture orders for third or subsequent hooning offences (Queensland Police Service, unpublished data).
5.3.4 Characteristics of the vehicles used in hooning offences
Table 5.7 describes the characteristics of vehicles used in hooning offences. An interesting finding related to vehicles used in hooning offences was that in more than one third of cases, the vehicle was not registered to the offender.
Hooning behaviours 175
Table 5.7 Characteristics of vehicles used in hooning offences (N = 848) Australian Hooning offences registered (N = 848) vehiclesa N % % Registration status Registered to offender 547 64.7% Not registered to offender 219 25.9% Unregistered 19 2.2% False registration plates 13 1.5% Commercial registration 12 1.4% Stolen 2 0.2% Unknown 33 3.9% Missing 3 Vehicle type Car / station wagon 665 80.8% Utility / panel van 130 15.8% Motorcycle 20 2.4% 4WD 8 1.0% Missing 25 Vehicle Make Holden 410 49.9% 18.5% Ford 130 15.8% 16.8% Nissan 110 13.4% 6.6% Toyota 69 8.4% 18.8% Mitsubishi 21 2.6% 8.8% Mazda 20 2.4% 4.7% Honda 15 1.8% 3.7% Subaru 12 1.5% 3.0% Hyundai 11 1.3% 4.8% Other 23 2.8% 14.4% Missing 27 Year of vehicle manufacture 2002 – 2006 93 11.6% 1997 – 2001 146 18.2% 1992 – 1996 221 27.6% 1987 – 1991 187 23.4% 1982 – 1986 87 10.9% Up to 1981 66 8.2% Missing 48 a Source: Australian Bureau of Statistics (2006)
As the Queensland anti-hooning legislation has a provision where the registered owner of the vehicle can appeal vehicle impoundment if they did not commit the offence and were not aware the vehicle was being used in an offence, this 176 Hooning behaviours
finding may represent a means of punishment avoidance on behalf of the offender. It is also possible that this finding reflects the youthfulness of the sample, as some of these offences may represent young people driving their parent’s vehicle. While it would be interesting to further explore the relationship between the offender and registered vehicle owner, this information was not available in this dataset. However, the registration status of vehicles was included as a variable in Study 1b described in the previous chapter. When the registration status of vehicles used in offences were compared by gender, it was found that female hooning offenders were significantly more likely than males to be driving a vehicle that was not registered in their name for their 2 hooning offence, χ (6) = 35.52, p < .001, dij = 3.6. Due to the small number of females in the sample, this test had more than 20% of cells with an expected count of less than five. However, confidence can be placed in this result as when the test was performed with only the first two registration status categories (vehicle registered to offender and vehicle not registered to offender), and there was no longer a breach of the expected count assumption, the test was still significant, χ2 (1) = 15.14, p < .001,
dij = 3.9. Almost two thirds of vehicles involved in hooning offences were Holdens or Fords (65.7%). Although these are the most common makes of vehicles on Australian roads according to the 2006 Motor Vehicle Census (Australian Bureau of Statistics, 2006), Holdens are over-represented in hooning offences (49.9% vs. 18.5%). Similarly, Nissans are driven in 13.4% of hooning offences, but make up only 6.6% of registered vehicles in Australia. Given the media perception that hooning involves high-powered or “souped- up” vehicles (e.g., Cox, 2007), and vehicle power restrictions imposed under Graduated Driver Licensing programs in many Australian jurisdictions including Queensland (see Appendix A.1), analysis of the power specifications or engine capacity of these vehicles would be of interest. However, this information was not available in the dataset. The average age of registered passenger vehicles in Queensland is 9.6 years (9.8 years in Australia), while for all registered vehicles the average ages are 9.8 and 10.1 years respectively (Australian Bureau of Statistics, 2006). Vehicles used in hooning offences were older, with a mean year of manufacture of 1992 (or age of approximately 14 years), and almost two thirds (64.2%) of vehicles were 10 or more Hooning behaviours 177 years old, having been manufactured during or prior to 1995. There were significant differences in vehicle characteristics as a function of hooning offence type, χ2 (18) = 84.02, p < .001, as illegal street racing offences were more likely than noise and smoke offences to occur in Nissans (dij = 2.3), and significantly less likely to occur in Holdens (dij = -3.5) or Fords (dij = -2.3). An independent groups t-test revealed that vehicles used in illegal street racing offences (M year of manufacture = 1994.44, SD = 6.51) were significantly newer than those used in noise and smoke offences (M year of manufacture = 1991.70, SD = 7.79), t(269.91) = 4.43, p < .001. It is acknowledged that the characteristics of vehicles used in hooning offences are likely to be related the age of hooning offenders. That is, young people are less likely than older drivers to have the financial means to purchase a new vehicle. Used vehicles are usually older, and less likely to have advanced safety features such as crash avoidance mechanisms, or inclusions that minimise injury in the event of a crash (such as airbags). It is also possible that drivers likely to engage in hooning behaviours have a general interest in cars, and purchase older vehicles with the intention of reconditioning and / or modifying them.
5.4 Discussion
The aim of this study was to contribute to the limited body of knowledge in the area by conducting a systematic profile of drivers caught and punished for a hooning offence in Queensland, and describing the nature of their offences. Although the previous literature in the area has focused on illegal street racing, this study found that a relatively small proportion (one fifth) of all hooning offences in Queensland involve illegal street racing. This illustrates the difference between hooning in an Australian context and the existing illegal street racing literature, and highlights the need to profile hooning offenders, as hooning encompasses a variety of risky driving behaviours.
5.4.1 Status of research questions and hypotheses
This section discusses the results of this study in terms of the key research questions it was designed to address. 178 Hooning behaviours
5.4.1.1 RQ1: Who engages in hooning in an Australian context?
The profile of hooning offenders in Queensland described in this chapter was similar to those in published studies of illegal street racers internationally. As predicted, young Caucasian males were the typical hooning offenders. In terms of gender and age, young males were significantly over-represented relative to the characteristics of licensed drivers in Queensland (racial appearance data is not available for all licensed drivers). This raises the question of whether hooning behaviours should be viewed as part of the broader young driver problem, or whether this behaviour and the drivers who engage in it represent a unique, additional, road safety risk over and above young males. This question is addressed in Study 2b, described in the next chapter of this thesis. Further, this study found that young, Caucasian males who are not working, or working in trades or as labourers, are the most common drivers caught and punished for hooning offences in Queensland. Car- oriented occupations, such as those in the automotive industry, were common, suggesting that many of the offenders could be considered car enthusiasts. This study found that there were few gender, age or hooning offence type differences observed in the data, suggesting that although around one quarter of hooning offences are committed by drivers who do not fit the stereotype of the young male driver, differences between the typical and atypical offenders do not appear to be of practical significance. Although the sample of offenders was not all young males, there did not appear to be any distinct sub-groups. However, there are distinct differences in the types of hooning behaviours, and the vehicles used in these offences. Holdens and Fords, the most common vehicles in Queensland and Australia, were the most common vehicles used in hooning offences generally, but these makes are also the most common on Queensland and Australian roads. They are also very common on the used car market, and as family vehicle, which means they are more likely to be driven by young people. When the two main types of hooning offences were compared, Holdens and Fords were more likely to be used in unnecessary noise and smoke offences, whereas Nissans were more likely in illegal street racing offences, most probably due to the capabilities of the different vehicle makes and models. Hooning behaviours 179
5.4.1.2 RQ4: What are the road safety implications of hooning behaviours?
It was possible to explore the road safety implications of hooning behaviour in this study by examining the information entered by the reporting police officer in the modus operandi field. It was found that very few hooning offences result in crashes, and that when crashes do occur, they tend to be single-vehicle crashes where the driver leaves the roadway and collides with a fixed object. In this regard, hooning-related crashes in this phase appear similar to the street racing crashes described by Vaaranen and Wieloch (2002). While it could be argued that this suggests that hooning drivers are only risking their own safety, there may be other passengers in the vehicle, pedestrians, and property that are at-risk. Although the crashes associated with hooning offences may not be serious in nature, there are still costs to the community. Further analysis of these crashes with the data collected for Study 2b revealed that the casualties in the injury crashes were equally likely to be the driver or their passengers, and that it was common for fault to be attributed to the hooning driver, as violations or other driver circumstances were commonly listed as circumstances or contributing factors for these crashes. It may be argued that only illegal street racing or speed trial offences pose a crash risk, due to the speeds attained by involved vehicles, while hooning offences involving unnecessary noise or smoke are better considered a public amenity issue. However, the potential risks associated with unnecessary noise and smoke offences, where the vehicle has lost traction with the road surface and is essentially out of the driver’s control, was illustrated in this study, where all but one crash that occurred during a hooning offence was an unnecessary noise and smoke offence. Finally, crashes that occurred during hooning offences are more likely to be detected by police and accurately recorded as crashes involving hooning than crashes that occur during acts of hooning that are not witnessed (and, therefore, detected) by police. That is, the proportion of hooning offences that resulted in a crash as estimated in this study should not be used as an indication of the proportion of all hooning incidents that result in a crash. The under-reporting of crashes involving hooning, particularly low severity crashes (i.e., where no injuries occurred) was noted in Study 1b. 180 Hooning behaviours
5.4.1.3 Additional analyses
The data collected for this study allowed a more detailed description of the nature of hooning offences and vehicle involved than has been conducted previously. In terms of the nature of hooning offences, it was found that the majority of hooning offences were those involving unnecessary noise and smoke, with illegal street racing accounting for one fifth of all hooning offences. While it is possible that this reflects true differences in the incidence of the different types of hooning behaviour, these trends are influenced by the ease with which police are able to detect and substantiate the different offence types. In addition to the makes of vehicles used in hooning offences discussed in section 5.4.1.2, this study found that more than one third of offenders were driving a vehicle that was not registered to them at the time of the offence. As discussed in section 5.3.3, this may mean that the owner of the vehicle can appeal the vehicle impoundment, and the offender avoids this part of the punishment for their hooning offence. Driving vehicles registered to others was discussed as a deliberate method of avoiding punishment by Study 1a (focus group) participants, and was confirmed in Study 1b (online survey). However, given the youth of the sample, this data may not reflect deliberate attempts to avoid punishment, but simply reflect that some hooning drivers do not have the financial means to own their own vehicles and instead borrow the family vehicle. The finding that vehicles involved in hooning offences are 10 or more years old, which is older than the average car on the road, may have implications for the deterrent effect of vehicle sanctions, as these vehicles may be low in financial value. They may also pose an additional road safety risk as they are less likely to have crash avoidance and occupant protection mechanisms.
5.4.2 Implications for policy and practice
While the main aim of this study was to generate a profile of hooning offenders and offences that would inform Study 2b, the results of this study also have implications for policy and practice. The profile can be used to inform the management of vehicle impoundment laws for hooning and enforcement of these laws. For example, this study found that hooning offences tend to involve young males, which may suggest that policies Hooning behaviours 181 targeting young drivers, such as Graduated Driver Licensing schemes, may represent an additional effective means of targeting hooning behaviour. This is particularly relevant in Queensland as the new scheme implemented on July 1, 2007 included restrictions on the power of vehicles driven by young novice drivers. However, it is important to note that the data obtained in this study may be biased by targeted enforcement. For example, if it is mainly young drivers in particular vehicles that are targeted by police, then this may be reflected in the data analysed in this study. It would therefore be inappropriate to target enforcement based on this type of intelligence. An additional outcome of this study was that recommendations were made to Queensland Police Service and Queensland’s Department of Transport and Main Roads regarding potential enhancement to data collection and storage practices to facilitate future internal and independent research into the nature of the hooning problem in Queensland, and evaluations of the effectiveness of sanctions. Many changes were made in this area when the vehicle impoundment and forfeiture program in Queensland was expanded to other offences.
5.4.3 Strengths and limitations
This was the first study of its kind to systematically profile hooning offenders. Although it was not possible to obtain data for the population of drivers caught and punished for hooning in Queensland since the vehicle impoundment laws were implemented, an adequate sample of all drivers with a hooning offence in a 15- month period was able to be analysed for this study. As all offences during this period were included in the initial data extraction, there is unlikely to be any bias in this data relative to the population of hooning offenders to date. While there are limitations in using secondary data collected for routine purposes, errors in the data were minimised by multi-stage data cleaning and validation with other data sources. Although this resulted in a 13.7% reduction in offence sample size, and some drivers who were caught and punished may have been erroneously excluded from the study as a result of incomplete or unclear data, statistical power was adequate for most analyses. Further, this process ensured that those offenders and offences that remained in the final sample did represent hooning offenders and offences. 182 Hooning behaviours
Using official data in this study complemented the self-report data in Studies 1a and 1b, making it possible to compare results across the two studies and consider potential differences in the sampling populations. It was, therefore, possible to explore whether drivers caught and punished for a hooning offence differ from those who report engaging in the behaviour, but have not necessarily been caught and punished, at least in terms of age, gender and occupation.
5.5 Chapter summary
This study aimed to profile drivers caught and punished for a hooning offence in Queensland, and their offences. It was found that consistent with published illegal street racing research, hooning offenders in Queensland are typically young males. Interestingly, only one fifth of hooning offences involved street racing, which may reflect trends in the different types of hooning behaviours, or ease of detection. Hooning offences tend to occur on weekends, and there are differences in the types of vehicles used in the two main types of hooning offences (illegal street racing and offences involving unnecessary noise and smoke). While the entire sample of offenders did not fit the stereotypical profile of the young male hooning offender, suggesting that while hooning offenders do not appear to be a homogeneous group, there were few practically significant differences between typical and atypical offenders. Few hooning offences result in reported crashes, and those crashes that do occur tend to be single-vehicle and result from the driver leaving the road and colliding with a fixed object. While this may suggest that the road safety implications of hooning are minimal, this is likely to be an underestimate as it is based on the reporting police officer mentioning the crash in the modus operandi field. It should also not be confused with an estimate of the proportion of all incidents of hooning that result in crashes, as there may be differences between incidents of hooning that go undetected and those that do result in the driver being caught and punished. The results of Study 1b reported in the previous chapter also indicated that drivers involved in hooning-related crashes are unlikely to report them unless they involve an injury, so the issue of under-reporting of crashes must be considered. It is important to note that many of the trends in the data analysed in this study could be attributed to the majority of the sample being young. Further, young males are a known at-risk group for crashes. Thus, although this study has found that Hooning behaviours 183 there appears to be a relatively small risk of crashing with hooning offences, Study 2b (reported in the following chapter) explores whether drivers who are caught and punished for hooning offences in Queensland represent a significant road safety problem over and above young males, by conducting a case / comparison analysis of previous traffic infringements, licence sanctions and crashes as a driver of the males in this sample and a comparison group of male Queensland licensed drivers with the same age distribution. 184 Hooning behaviours
Hooning behaviours 185
CHAPTER 6: STUDY 2B – THE ROAD SAFETY RISK OF DRIVERS WITH A HOONING OFFENCE
6.1 Introduction
One of the research aims of this thesis was to investigate the road safety implications of illegal street racing and associated (hooning) behaviours. Three methods of calculating crash risk were discussed in section 2.4: the riskiness of hooning behaviour; the involvement of hooning in crashes; and the general crash risk of drivers who engage in hooning driving behaviours. Section 2.4 also discussed the difficulties associated with accurately quantifying the crash risk associated with hooning using the first two methods, mainly due to limitations in current official data collection practices in Queensland, and the willingness of drivers to make admissions regarding their illegal behaviour to police when they crash. A variation of the first method was used in Study 2a reported in the previous chapter, where it was possible to estimate the proportion of hooning offences that resulted in a crash, based on the descriptions of the offences the reporting police officer entered into the modus operandi field of the CRISP database. However, this may over-estimate the true proportion of all hooning incidents that result in a crash, as the police were generally present when or shortly after the offences occurred and therefore witnessed and reported the crashes, while crashes (particularly minor crashes) that occur during hooning incidents that are not detected by police may be less likely to be reported. For example, participants in Study 1b admitted being less likely to have reported crashes that involved hooning than they were to report crashes generally, and reporting of less serious (i.e., non-injury) crashes that involved hooning was particularly low. Further, crashes that do not involve an injury to any occupant and that have a low property damage bill are not eligible for inclusion in Queensland’s crash data. Thus attempts to quantify the proportion of all crashes that involve hooning using official data sources alone are likely to underestimate the true involvement of hooning in crashes. The third method of investigating the crash risk of hooning (rather than illegal street racing only), yet to be used in any published studies to date, is somewhat more promising. The crash and driving histories of drivers who engage in 186 Hooning behaviours
hooning behaviours can be compared to those of drivers who do not in order to quantify the general crash risk of the hooning driver. Important considerations regarding this method are the sampling populations selected and methods used. For example, if the risk of involved drivers (i.e., those who engage in the behaviour but have not necessarily been caught and punished, or the sampling population of Studies 1a and 1b in this program of research, where only 5.6% of Study 1b participants reported experiencing impoundment) is investigated, it is imperative that the sample of drivers obtained is representative of all drivers who engage in hooning. As noted throughout this thesis, the population of drivers who engage in hooning is unknown, and it is therefore not possible to assess the representativeness of an obtained sample, although it is likely that there will be some degree of volunteer bias. Limiting the sample to drivers caught and punished for hooning reduces external validity, as drivers caught and punished may not be representative of all drivers who engage in the behaviour, but this approach does have the advantage that the parameters of the population of hooning offenders are known. The selection of an appropriate comparison group also requires careful consideration. Study 2a found that, consistent with previous illegal street racing literature, hooning offenders are typically young males. This means that using a comparison group of all drivers would be problematic, as young males are a known at-risk group, and there would therefore be internal validity problems in concluding that any differences in the dependent variables are the result of involvement in hooning, rather than simply an outcome of the hooning driver’s demographic characteristics. A more appropriate comparison group is one that limits rival explanations for the results. That is, using a comparison group with the same gender and age distribution as the hooning group controls for the effects of gender and age. Finally, the selection of data is also important. Self-report data may be problematic due to recall or social desirability biases, while official data sources only include illegal behaviours and crashes that have come to the attention of police and meet the requirements for inclusion in official databases, therefore underestimating the dependent variables. In consideration of these issues, the aim of this study was to explore the risk associated with hooning from the perspective of the hooning driver. That is, this study was designed to address the third and fourth key research questions of the program of research. Hooning behaviours 187
6.1.1 Hypotheses
Using the sample of hooning offenders profiled in the previous chapter, this phase of Study 2 used a case / comparison design to compare the traffic and crash histories of the males in the Study 2a sample of drivers caught and punished for a hooning offence with a comparison group of males with the same age distribution randomly selected from the population of Queensland licensed drivers to explore research question three, and described the traffic and crash histories of the sample of hooning offenders to address research question four. This section outlines the specific hypotheses tested for each research question.
6.1.1.1 RQ3: What are the road safety implications of hooning behaviours?
In order to address research question three from the perspective of the hooning driver, the traffic and crash histories of a sample of hooning offenders were compared to the histories of a random sample of drivers with the same gender and age distribution. The specific hypotheses tested to assess this research question were:
H1: Hooning offenders will have more previous traffic infringements of any type compared to the comparison group; H2: Hooning offenders will have more previous licence sanctions of any type compared to the comparison group; and H3: Hooning offenders will have more previous crashes compared to the comparison group
It is acknowledged that the dependent measures examined by these hypotheses are likely to be related. As many traffic infringements in Queensland result in demerit points on the drivers’ licence, drivers with many traffic infringements are more likely to have licence sanctions, specifically demerit point suspensions or good behaviour bonds, which are applied when the driver exceeds the maximum number of demerit points on his/her licence. Further, there is evidence that drivers with traffic infringements are more likely to be crash-involved (e.g., Chandraratna, Stamatiadis, & Stromberg, 2005; Chen, Cooper, & Pinili, 1995), and some crashes may result in the detection of traffic infringements, thus crash- involvement is also likely to be related to the other dependent measures. 188 Hooning behaviours
6.1.1.2 RQ4: Do drivers who engage in hooning also engage in other risky driving behaviours?
This study also addressed research question four by describing the nature of the traffic and crash histories of hooning offenders. Although hooning is not a specific contributing factor in Queensland’s crash database, it is possible to explore other factors that may be related to hooning. Specific hypotheses in this regard were made based on the literature described in Chapter 2, and the nature of hooning behaviours. For example, previous literature (Leigh, 1996) and discussions with Queensland Police Service personnel indicate that enforcing vehicle standards and checking whether modifications have been approved is a common method of dealing with hooning behaviours by discouraging involved drivers from gathering in large groups. As such it was predicted that:
H4: Hooning offenders will have more vehicle defect and illegal modification offences in their driving histories than the comparison group
Further, given the nature of illegal street racing, it was also predicted that:
H5: Speeding offences, high speed licence suspensions and crashes involving speeding will be more common for the offender group than for the comparison group
6.2 Method
6.2.1 Samples
6.2.1.1 Hooning offenders
The group of 834 drivers with a hooning offence in Queensland between July 1, 2005 and September 20, 2006 that formed the sample for Study 2a were the sampling population for this study. However, 32 of these drivers were excluded from this study. All of the females (n = 22) were excluded as the low numbers would not allow sufficient cell sizes and therefore statistical power for the required analyses. A further 10 drivers were excluded because they could not be identified in Department of Transport and Main Roads maintained databases and, therefore, had no driving history data, leaving a hooning offender sample size of 802. Hooning behaviours 189
6.2.1.2 Comparison group
The comparison group for this study consisted of 802 male drivers. These drivers were randomly selected from the Transport Registration and Licensing System (TRAILS) database maintained by the Queensland Department of Transport and Main Roads, with the criteria that the comparison group sample had the same age distribution13 as the offender sample, and that none of the drivers randomly selected for the comparison group were already in the offender group sample. This meant that age, known to be a factor in road traffic crashes, did not have to be controlled for or used as a covariate in any statistical analyses.
6.2.2 Design
This study involved a case / comparison design, where the independent variable was group (hooning offender vs. comparison group), and the dependent variables were traffic infringements, licence sanctions and crashes that occurred on Queensland roads in the previous three years. The reference date for the hooning offender group was their hooning offence date (or first offence date for those with more than one offence during the study period). However, drivers in the comparison group did not have an equivalent reference date, as they were selected randomly from the licensing database and may not have had any offences in the study period. The reference dates for the offender sample were listed in order and the median date was February 12, 2006. Accordingly, this date was used as the reference date for all drivers in the comparison group.
6.2.3 Data sources
There were two data sources for this study that were used to provide information about the traffic and crash histories of drivers in both samples. Both sets of data were provided by the Queensland Government’s Department of Transport and Main Roads and are described below.
13 Age was matched by randomly selecting a sample of male drivers with a date of birth within one week of a driver in the hooning offender sample. Thus the ages at reference date were statistically equal for the two samples. 190 Hooning behaviours
6.2.3.1 Traffic history information
These data included descriptions of all traffic infringements that occurred in Queensland, and all sanctions on the Queensland driver’s licence sanctions included in the TRAILS database. However, only infringements and sanctions that occurred within three years of the reference date were included in the analyses for this study, to be consistent with the three-year follow-up period used in Study 3 (described in the next chapter). Only infringements and sanctions that were upheld were included in the analyses, as all those that were waived on appeal were deleted.
6.2.3.2 Crash history information
The Department of Transport and Main Roads also provided information regarding the crash histories of both samples of drivers. Details of all crashes on Queensland roads in which the person was in control of the motor vehicle or motorcycle were extracted from the Road Crash Information System database. To be eligible for inclusion in this database, at least one person must have been injured in the crash, or the damage to property must have exceeded $2500. This database includes all crashes that occurred since January 1, 1986, and contains data provided by the attending police officer. Similar to the traffic history information, only crashes that occurred within three years of the reference date were retained for analyses.
6.2.4 Procedure
This study was included in the Queensland Police Service, University Ethics Committee and Health and Safety applications described in the previous chapter. Once the sample for Study 2a was finalised, the Department of Transport and Main Roads provided a random sample of male drivers with the same age distribution, not including any drivers from the offender group sample. The Department created a set of arbitrary codes to link the comparison group data files in lieu of any identifying information. The licence, traffic and crash histories for the hooning offender and comparison group samples were then requested, and no start date was set. Thus any infringements, sanctions or crashes included in the databases that occurred on Queensland roads prior to the extraction date were provided. Although only incidents Hooning behaviours 191 in the three years prior to the reference date were to be included in the analyses for this study, requesting the complete histories made the extraction process more parsimonious than if the Department was required to change the search parameters for each driver in the offender sample.
6.2.4.1 Data coding
The de-identified data files were provided to the researcher in the form of Excel spreadsheets. Most of the data were in text form (i.e., written descriptions of offence types) with numeric codes as labels. Prior to analysis, this dataset was coded and transformed into a numerical dataset that could be analysed using SPSS. Prior to coding, as noted previously, any offences or licence sanctions that were waived on appeal were deleted from the datasets so only upheld convictions and sanctions remained. Further, any infringements where the driver was not in control of a motor vehicle or motorcycle on a public road were deleted (i.e., offences relating to travelling on public transport, on a waterway, or on a roadway as a pedestrian or cyclist were deleted). Traffic infringements were recoded according to their text descriptions, and grouped into nine main offence groups created for this research, described in Table 6.1.
Table 6.1 Offence groups and sub-groups created for Study 2b Offence groups Offence sub-groups Dangerous driving; Driving without due care and attention; Racing and Hooning-related speed trials on roads; Undue noise and smoke Impaired driving Alcohol; Drugs; Fail to supply specimen Police / government Administrative requirement; Crash duties; Fail to stop; Inspection; Produce instruction licence; Provide information Registration plates / labels; Transfer of registration; Uninsured (compulsory Registration-related third party); Unregistered Restraint Helmet (self); Helmet (passengers); Seatbelt (self); Seatbelt (passengers) Road rule / Body out of car; Fail to give way; Follow too closely; Headlights; Horn; Illegal manoeuvre; Lane-keeping; Mobile phone; Other; Overtaking; Radar sign / marking detector; Railway crossing; Road marking; Sign; Signalling; Traffic lights Low-range (up to 15km/hr over limit); Mid-range (15 – 30km/hr over limit); Speeding High-range (30km/hr or more over limit); Not specified Condition of licence; Disqualified driving; Expired licence; Inappropriate Licence-related class of licence; Learner Plates; Non-Queensland licence; Suspended licence; Unaccompanied learner driver; Unlicensed driving Vehicle defect / Defective vehicle; Ground clearance; Modifications; Noisy; Notice; modification Silencer 192 Hooning behaviours
These offence groups were further divided into sub-groups of offences (also created for this research). Offences were allocated to groups and sub-groups based on the offence description. A table outlining the complete list of infringements in each of the offence groups and sub-groups, and those that were deleted, is included as Appendix D.1. As an illustrative example, the offence “Driver under influence of liquor (under .15)” was in the offence group “Impaired driving offences”, and the sub-group “Alcohol”.
6.2.4.2 Statistical analyses
The alpha level adopted for all statistical tests was p < .05. As the data violated the assumptions of parametric tests, the equivalent non-parametric test was used. For example, the previous traffic infringement, licence sanction and crash data violated the normality and homogeneity assumptions of the t-test due to strong positive skews to the distributions, so Mann-Whitney U tests were performed to compare the two groups. Chi-square tests were performed to test hypotheses for
variables with categorical coding, and only adjusted standardised residuals (dij) greater than +/- 1.96 were interpreted and described for significant tests.
6.3 Results
6.3.1 Demographic characteristics of drivers
As indicated in section 6.2.1, both samples consisted entirely of males, with 802 drivers in each sample. The age distributions were statistically identical as the age distribution of the offender sample was used to select the comparison group. Ages at the reference date ranged from 16 to 50, with a median of 20 years for each sample. These characteristics are similar to those of the samples in Studies 1a and 1b. It is acknowledged that there may be pre-existing differences between the two groups in terms of residence and driving in Queensland and, therefore, exposure to Queensland traffic policing, which may influence the results of this study. Drivers in the offender sample may not have resided in Queensland, as their inclusion in this study was the result of them committing a hooning offence in Queensland14. In
14 However, out of state drivers would be expected to represent only a small proportion of the sample. Hooning behaviours 193 contrast, the comparison group was drawn from the TRAILS database, meaning that at the time of the extraction (May 2009) they held a Queensland driver’s licence, or had previously committed a traffic infringement or been involved in a crash on Queensland roads. This was not necessarily the case for drivers in the offender group. That is, the comparison group may be more likely than the offender group to have previous convictions and crashes recorded in the databases used to obtain data for the dependent measures in this study. However, as this potential bias was in the opposite direction to study predictions, this issue posed a potential power problem rather than a Type I error, and therefore cannot be considered a rival explanation for significant results. Further, it was not possible to accurately determine the mobility or driving exposure of either sample, as only official data sources were used.
6.3.2 Hypothesis testing
In order to address the first research question regarding evidence that hooning offenders are generally risky drivers, the previous traffic infringements, licence sanctions and crashes of male drivers in the hooning offender sample were compared to a random sample of male drivers with the same age distribution.
6.3.2.1 Prior traffic infringements
Within the hooning offender sample, the total number of traffic infringements in the three years prior to the index hooning offence recorded in Queensland where they were the driver of a motor vehicle or rider of a motorcycle was 3645, and per driver ranged from 0 to 51, with a heavy positive skew to the data. Within the comparison group, the total number of traffic infringements in the three years prior to the reference date was 1005, and per driver ranged from 0 to 22, also with a positive skew. As expected from these descriptive statistics, Table 6.2 shows that the Chi- square test of independence supported hypothesis 1, as drivers in the offender group were significantly more likely than drivers in the comparison group to have prior traffic infringements, representing a moderate to large effect. Further, the Mann- Whitney U test showed that drivers in the offender sample had significantly more traffic infringements than drivers in the comparison group, and a series of Chi-square tests revealed that this trend held for all offence types. 194 Hooning behaviours
Table 6.2 Comparison of prior traffic infringements of hooning offenders and a random sample of drivers of comparable age (n’s = 802)
Hooning Comparison Statistics Offenders Group Prior infringements χ2 (1) = 285.90, = .42*** Yes 686 (85.5%) 364 (45.4%) No 116 (14.5%) 438 (54.6%) Median number 3 0 U = 143540.5, z = 19.68*** Mean rank 1024.52 580.48 Drivers with particular infringement typesa Hooning 255 (31.8%) 38 (4.7%) χ2 (1) = 196.63, = .35*** Impaired 68 (8.5%) 42 (5.2%) χ2 (1) = 6.60, = .06** Police / govt. 91 (11.3%) 23 (2.9%) χ2 (1) = 43.67, = .17*** Registration 166 (20.7%) 60 (7.5%) χ2 (1) = 57.87, = .19*** Restraint 80 (10.0%) 26 (3.2%) χ2 (1) = 29.46, = .14*** Road rule / sign 253 (31.5%) 101 (12.6%) χ2 (1) = 83.75, = .23*** Speeding 521 (65.0%) 257 (32.0%) χ2 (1) = 173.96, = .33*** Licence related 216 (26.9%) 65 (8.1%) χ2 (1) = 98.38, = .25*** Vehicle defect 254 (31.7%) 47 (5.9%) χ2 (1) = 175.24, = .33*** a Percentages are proportion of sample with at least one of the applicable offence type. As drivers could have more than one infringement, percentages for each sample sum to more than 100%. * p < .05; ** p < .01; *** p < .001
Consistent with hypothesis 4, drivers in the hooning offender sample were significantly more likely than those in the comparison group to have previous vehicle defect or speeding offences (as shown in Table 6.2), although the most common traffic infringements for both samples, in terms of total number (as shown in Table 6.3) and proportion of drivers with at least one offence of this type (Table 6.2), was speeding-related. When hooning and vehicle defect offences were excluded from the calculation of percentages of all traffic infringements for each group in Table 6.3, the distribution of infringement types were fairly similar. Although the offender sample had far more drivers with at least one speeding infringement (Table 6.2) and speeding infringements (Table 6.3), the comparison group had a slightly higher proportion of speeding-related offences than the offender sample; however, this result reflects the amount of manual and automated enforcement devoted to speeding in Queensland, as speeding is a common traffic offence among the general driving population. Hooning behaviours 195
Table 6.3 Comparison of the traffic infringements of the hooning offender (n = 3645) and comparison (n = 1005) samples
Hooning Offenders Comparison Group Excluding Excluding All All hooning-relateda hooning-relateda Hooning 409 (11.2%) ~ 44 (4.4%) ~ Impaired 79 (2.2%) 2.9% 49 (4.9%) 5.5% Police / govt. 122 (3.3%) 4.5% 26 (2.6%) 2.9% Registration 449 (12.3%) 16.4% 129 (12.8%) 14.4% Restraint 97 (2.7%) 3.6% 37 (3.7%) 4.1% Road rule / sign 371 (10.2%) 13.6% 112 (11.1%) 12.5% Speeding 1128 (30.9%) 41.3% 434 (43.2%) 48.5% Licence-related 486 (13.3%) 17.8% 107 (10.6%) 12.0% Vehicle defect 504 (13.8%) ~ 67 (6.7%) ~ a Percentages calculated using total number of infringements less hooning and vehicle defect offences for each sample (n = 2732 for offenders; n = 894 for comparison group) as denominator.
Vehicle defect offences for each sample were compared to explore hypothesis 4. Although the median number of these offences for each sample was zero, a Mann- Whitney U test revealed that the hooning offender group (mean rank = 907.72) had significantly more of these offences in the three years prior to the reference date than the comparison group (mean rank = 697.28), U = 237213.5, z = 13.38, p < .001. Further, Table 6.2 shows that the hooning offender sample had more of these offences than the comparison group, and this group of offences was more common among the total number of infringements for the offender group compared to the comparison group (Table 6.3). However, the group x offence sub-group relationship 2 was not significant, χ (5) = 2.45, p = .784, v = .07, as the proportions of each of the sub-groups of vehicle defect offences did not vary between the samples. Speeding offences for each sample were compared to explore hypothesis 5. The median number of speeding offences for the hooning offender sample was 1, while the median for the comparison group was 0. The Mann-Whitney U test revealed that the hooning offender group (mean rank = 949.64) had significantly more of these offences in the three years prior to the reference date than the comparison group (mean rank = 655.36), U = 203592.0, z = 13.83, p < .001. A Chi- square test for independence was used to explore the group x speeding offence sub- group relationship, revealing a small but significant relationship, χ2 (3) = 16.10, 196 Hooning behaviours
p = .001, v = .10. Examination of the adjusted standardised residuals revealed that this effect was due to the offender sample having a higher than expected number of high-range speeding offences (30km/hr or more over the speed limit) relative to the
comparison group (dij = 3.7).
6.3.2.2 Prior licence sanctions
To further address the first research question, licence sanctions of the offender and comparison groups in the previous three years were compared. Within the hooning offender sample, the total number of licence sanctions in the three years prior to the reference date for the group was 1053. Per driver, the number of previous licence sanctions ranged from 0 to 11, with a median of 1 as the distribution was heavily positively skewed. There was a similar positive skew within the comparison group sample, where there were 281 licence sanctions in the three years prior to the reference date. Per driver in this sample, prior licence sanctions ranged from 0 to 8, with a median of 0. As shown in Table 6.4, testing of hypothesis 2 revealed that drivers in the offender group were significantly more likely than those in the comparison group to have had a prior sanction on their licence, representing a moderate effect. The Mann- Whitney U test also revealed that drivers in the offender group had significantly more prior licence sanctions than the comparison group, and a series of Chi-square tests revealed that this trend was observed for all sanction types. The data in this table are also relevant to the second research question. Similar to the results regarding traffic infringements, the most common licence sanctions among the offenders in terms of both numbers of drivers with any sanction of each type, and total numbers of sanctions within each group, were those related to exceeding the maximum number of demerit points on the driver’s licence and unpaid fines. In Queensland, when a driver loses all of the demerit points on their driver’s licence, he/she can serve a licence suspension (“demerit points” sanction group in this study) or opt for a good driving behaviour option (“good behaviour”), where only one demerit point remains on the licence for a period of 12 months. If this point is lost, a longer suspension period than initially offered is applied.
Hooning behaviours 197
Table 6.4 Comparison of prior licence sanctions of hooning offenders and a random sample of drivers of comparable age (n’s = 802)
Hooning Comparison Statistics Offenders Group Prior sanctions χ2 (1) = 190.28, = .34*** Yes 415 (51.7%) 151 (18.8%) No 387 (48.3%) 651 (81.2%) Median number 1 0 U = 207770.0, z = 14.41*** Mean rank 944.44 660.56 Drivers with particular sanction types a Disqualification 142 (17.7%) 59 (7.4%) χ2 (1) = 39.18, = .16*** Demerit points 247 (30.8%) 50 (6.2%) χ2 (1) = 160.36, = .32*** Good behaviour 183 (22.8%) 75 (9.4%) χ2 (1) = 53.88, = .18*** Unpaid fines 140 (17.5%) 32 (4.0%) χ2 (1) = 75.96, = .22*** High speed 52 (6.5%) 9 (1.1%) χ2 (1) = 31.51, = .14*** Total number of sanctions for each sample b n = 1053 n = 281 Disqualification 172 (16.3%) 82 (29.2%) Demerit points 413 (39.2%) 71 (25.3%) Good behaviour 203 (19.3%) 78 (27.8%) Unpaid fines 210 (19.9%) 40 (14.2%) High speed 55 (5.2%) 10 (3.6%) a Percentages are proportion of sample with at least one of the applicable sanction type. As drivers could have more than one licence sanction, percentages for each sample sum to more than 100%. b Percentages are proportion of all licence sanctions for each sample. * p < .05; ** p < .01; *** p < .001
Consistent with hypothesis 5, Table 6.4 shows that a higher proportion of drivers from the offender sample had at least one licence suspension due to a high- range speeding offence compared to drivers in the comparison sample.
6.3.2.3 Prior crashes as a driver
As shown in Table 6.5, drivers in the hooning offender sample were significantly more likely to have been involved in a crash recorded in the Queensland Road Crash Information System in the previous three years than drivers in the comparison group, representing a small effect.
198 Hooning behaviours
Table 6.5 Prior crashes recorded in Queensland’s Road Crash Information System of hooning offenders and a random sample of drivers of comparable age (n’s = 802)
Hooning Comparison Statistics Offenders Group Prior crashes χ2 (1) = 29.33, p < .001, = .14 Yes 103 (12.8%) 41 (5.1%) No 699 (87.2%) 761 (94.9%) Median number 0 0 U = 296761.5, z = 5.41, p < .001 Mean rank 833.47 771.53 Number of crashes per driver 0 699 (87.2%) 761 (94.9%) 1 94 (11.7%) 37 (4.6%) 2 9 (1.1%) 4 (0.5%) a 2 Crash severity n = 112 n = 45 χ (3) = 4.13, p = .247, v = .16 Fatal 0 0
Hospitalisation 18 (16.1%) 13 (28.9%) dij = -1.8
Medical treatment 23 (20.5%) 8 (17.8%) dij = 0.4
Minor injury 15 (13.4%) 3 (6.7%) dij = 1.2
Property damage 56 (50.0%) 21 (46.7%) dij = 0.4 b 2 Contributing circumstances n = 156 n = 77 χ (12) = 15.46, p = .217, v = .26
Animal 4 (2.6%) 1 (1.3%) dij = 0.6
Environment 6 (3.8%) 4 (5.2%) dij = -0.5
Road 10 (6.4%) 2 (2.6%) dij = 1.2
Vehicle 6 (3.8%) 0 dij = 1.7
Other road user 2 (1.3%) 1 (1.3%) dij = 0 Driver
Alcohol 8 (5.1%) 2 (2.6%) dij = 0.9
Dangerous 2 (1.3%) 2 (2.6%) dij = -0.7
Fatigue 6 (3.8%) 7 (9.1%) dij = -1.6
Inexperience 48 (30.8%) 27 (35.1%) dij = -0.7
Speed 9 (5.8%) 4 (5.2%) dij = 0.2
Undue care 32 (20.5%) 10 (13.0%) dij = 1.4
Violation 15 (9.6%) 15 (19.5%) dij = -2.1
Other 8 (5.1%) 2 (2.6%) dij = 0.9 a Adjusted standardised residuals (dij) are from the perspective of the hooning offender group, where negative residuals indicate a less than expected frequency, and positive residuals indicate a greater than expected frequency. b As crashes can have multiple contributing circumstances, these sum to more than the total number of crashes for each sample.
There were 112 crashes in the hooning offender group, compared to only 45 for the comparison group. Within each sample, the median number of crashes was 0, with a maximum of two crashes in the three year period. The Mann-Whitney U test Hooning behaviours 199 on the data revealed that hooning offenders were involved in significantly more crashes than drivers in the comparison group, although very few drivers in either sample had been involved in more than one crash in this relatively short time period. Table 6.5 also shows that there was no difference in the severity of crashes between the two groups. The attending police officer attributes circumstances believed to have contributed to road traffic crashes in Queensland. The circumstances attributed to the crashes of each group were compared, and the results are also presented in Table 6.5. As there are a large number of circumstances the attending officer can select on the crash forms used in Queensland, circumstances were grouped for these analyses. The “Animal” category included circumstances where there was an uncontrolled animal on the road; “Environment” included weather and lighting conditions; “Road” included slippery road surface or obstruction; “Vehicle” included any defects with the vehicle; “Other road user” included cases where the actions of another road user contributed to the crash; and “Other” included ‘miscellaneous driving conditions’ and any contributing circumstances not included in the previous or “Driver” categories. The driver categories were those where the driver committed a violation, or their behaviour contributed to the crash in some way. The driver categories created were alcohol-related crashes, dangerous driving, fatigue, inexperience / lack of expertise, speed-related, undue care and attention, and any other driving violation. Within both samples, the most common factors attributed to the crashes were inexperience / lack of expertise followed by driving with undue care and inattention. The Chi-square test for independence conducted to test hypothesis 5 was not significant, although the effect size suggests that power was low in this analysis of the group x crash contributing circumstance relationship. Regardless, inspection of the adjusted standardised residuals and percentages of crashes within each group revealed only small offender versus comparison group differences.
6.4 Discussion
The overall purpose of this study was to explore the road safety implications of illegal street racing and associated hooning behaviours. This was done from the perspective of involved drivers, specifically drivers with a hooning offence, by analysing the traffic histories of male hooning offenders used in Study 2a, and 200 Hooning behaviours
comparing them to those of a group of male drivers with a comparable age distribution to determine whether there was any evidence of hooning offenders being a more at-risk group than young male drivers in general. This study therefore addressed the fourth and fifth research question in this program of research. As it may be argued that any risk associated with hooning can be explained by the youthfulness of the drivers, and the over-representation of young drivers (particularly males) in crashes, the age distributions of the groups were matched, meaning that age did not have to be controlled in analyses, and cannot be considered a rival explanation for the pattern of results of the tests of the specific hypotheses related to research question four.
6.4.1 Status of research questions and hypotheses
Research question three was explored by three specific hypotheses, predicting that the drivers in the offender sample would have significantly more traffic infringements, licence sanctions and crashes as a driver in Queensland in the three years prior to their reference date compared to drivers in the comparison sample. Each of these three hypotheses were supported by the results. As the results regarding traffic infringements were significant, it followed that the licence sanction hypothesis (hypothesis 2) would also be supported, given that most traffic infringements attract demerit points in Queensland, and the most common licence sanctions among the hooning offender sample were those related to the accrual of demerit points. The smaller effect size for licence sanctions is also to be expected, as Queensland Provisional and Open licence holders have 4 and 12 demerit points respectively, and it therefore takes more than one traffic infringement to lose all of these points and become eligible for a licence sanction. The between group differences on the crash measures were also significant, consistent with Finnish research with car club members (Vaaranen & Wieloch, 2002). The effect size was smaller than that for traffic infringements or licence sanctions, reflecting the lower numbers of drivers involved in crashes relative to the traffic infringement and licence sanctions, and therefore lower statistical power. However taken together, these results suggest that drivers charged and punished with a hooning offence have traffic and crash histories that provide evidence of other risky driving behaviours, to a significantly greater degree than other similar aged drivers. Hooning behaviours 201
The second research question (RQ4) addressed in this study related to the evidence that drivers who engage in hooning also engage in other risky behaviours. The descriptive statistics reported in this study revealed that the majority of drivers in the hooning offender sample had at least one traffic infringement in the previous three years, compared to less than half of the comparison sample. The most common types of infringements for the hooning offender sample in terms of the number of drivers with at least one offence of this type were speeding, hooning, vehicle defect and road rule / sign violations. The most common infringements in terms of total number of infringements of this type were similar, where the most common was speeding, followed by vehicle defect, unlicensed driving, registration, hooning and road rule / sign offences. It is important to note that as the registration and compulsory third party insurance procedures are combined in Queensland, it was common for drivers to have both of these offences that were group together as “registration” offences. Many of the drivers charged with these offences were also charged with unlicensed driving. In terms of licence sanctions, just over one half of the hooning offender sample had at least one licence sanction in the previous three years, compared to less than one fifth of the comparison sample. The most common licence sanctions among the hooning offender sample in terms of number of drivers with at least one sanction of this type was demerit point suspensions, followed by good behaviour bonds, both of which are applied when the driver exceeds the maximum number of demerit points on their licence. This result is therefore consistent with the large proportion of the hooning offender sample with more than one traffic infringement. In terms of the total number of sanctions for this sample, the most common was again demerit point suspensions, followed by suspensions due to unpaid fines and good behaviour options, which is also consistent with the pattern of results for previous traffic infringements. Reflecting the relatively rare nature of crashes compared to traffic infringements and licence sanctions, one eighth of the hooning offender sample had been involved in a crash as a driver in the previous three years, compared to only one twentieth of the comparison sample. None of the hooning offender sample crashes were fatal, with half involving at least a minor injury to one occupant, and the other involving only damage to property. While current crash coding practices in Queensland do not include a specific “hooning” category as a factor contributing to 202 Hooning behaviours
the crash, the most common factors attributed by police for the crashes where a driver from the hooning offender sample was driving were those relating to an error of the driver, with less than one quarter being attributed to other factors. The most common contributing factors assigned were inexperience / lack of driver expertise and driving with undue care and attention. However, these are often attributed to young driver crashes in Queensland, and may simply reflect that the outcome of their driving was a crash (i.e., that there must have been some element of lack of expertise or inattention to result in a crash). The hooning offender and comparison group samples were also compared to test two further hypotheses under this research question. The results supported hypothesis 4, as drivers in the offender sample did have significantly more vehicle defect offences in the previous three years than the comparison sample. However, as this may have been an outcome of the offender sample having more traffic infringements in the previous three years generally, this hypothesis was further explored by comparison the proportion of drivers in each sample with at least one of this type of offence, and the proportion of all offences within each sample that involved vehicle defects. These analyses also supported the hypothesis, as the proportions were greater for the offender sample than for the comparison sample using drivers with this offence type or the proportion of all offences as the observations in the analysis. This finding may be related to the concurrent enforcement of hooning-related offences and vehicle defect issues, as some drivers had an offence of each type on the same date. Further, this is consistent with Leigh’s (1996) assertion that police may enforce vehicle standards and other traffic laws as a method of dealing with illegal street racing or hooning when there is insufficient evidence to substantiate a hooning offence. Hypothesis 5 predicted that drivers in the hooning offender sample would have significantly more speed-related infringements, licence sanctions and crashes in the previous three years relative to the comparison sample. The data supported this hypothesis in terms of the total number of speeding infringements and the proportion of each sample with at least one offence of this type, as would be expected given the overall number of traffic infringements for each group. However, the proportion of speeding offences was greater for the comparison group than the hooning offender sample. As noted previously, this probably reflects the differing levels of enforcement of illegal driving behaviours, where the resources devoted to enforcing Hooning behaviours 203 speeding mean that this is the most commonly detected traffic offence. When the speeding offences for each sample were further analysed in sub-groups of low-range, mid-range and high-range, the hooning offender group had significantly more high- range speeding offences (defined as offences of 30km/hr or more over the posted speed limit) than the comparison group, which is consistent with hypothesis 5. The licence sanction data partially supported hypothesis 5, as significantly more drivers in the hooning offender sample had at least one high speed suspension in the previous three years than drivers in the comparison sample, which is expected given the higher number of high-speed offences in the offender sample. Finally, the crash data did not support hypothesis 5, as the group x contributing factor analysis was not significant. While the effect size suggests that power was low for this analysis, there was little difference in the proportions of all crashes that were deemed to have involved speeding by the attending police officer. It was interesting that speeding was not a common contributing factor for crashes for either sample relative to other factors. This may be because speeding was not involved in the crashes, or because there was no or insufficient evidence for the police officer to attribute speeding as a potential factor in the crash. It is important to note that crash data, particularly the identification of circumstances that contributed to the crash, can be very subjective in nature, and thus analyses based upon crash data should be interpreted with caution.
6.4.2 Implications for policy and practice
The research questions and underlying hypotheses addressed in this study relate to the first research aim of this thesis: To investigate the road safety implications of illegal street racing and associated (hooning) behaviours, in terms of the specific behaviours, and the drivers who engage in the behaviours. This study explored the road safety implications of illegal street racing and associated behaviours from the perspective of involved drivers, specifically those caught and punished for a hooning offence in Queensland. Taken together, the findings of this study suggest that drivers who engage in illegal street racing and associated hooning behaviours (and get caught) are likely to have a driving history with evidence of other risky driving behaviours, such as traffic infringements, licence sanctions and crashes. Further, they have more of each of 204 Hooning behaviours
these indicators of risky driving behaviours than drivers matched for age. Therefore, this group of offenders could be described as generally more risky drivers, and this risk cannot be attributed to their youth alone. These results suggest that drivers with an illegal street racing or associated hooning offence represent a significant road safety problem over and above the young driver problem. The implications of these results for policy and practice are that drivers who engage in hooning behaviours and are detected by police appear to represent a significant road safety problem. It is important to note that these results relate to the hooning driver (specifically, hooning offender), rather than to hooning behaviours per se and, therefore, do not provide evidence that hooning behaviours represent a road safety risk warranting traffic policing attention. If there is less evidence that hooning behaviours represent a significant road safety risk, it may be argued that traffic policing resources should not be devoted to hooning. Rather, general policing or other community resources could be used to deal with the public nuisance hooning represents. However, it is possible that hooning offences are a useful way of identifying these high-risk drivers, and vehicle impoundment represents a means of reducing, or at least constraining, their opportunity to offend. Moreover, it could be argued that if the only evidence of risk is related to the driver, then vehicle impoundment and forfeiture programs should not be related to hooning offences, but the accrual of a large number of traffic infringements and licence sanctions. In this regard, vehicle impoundment and forfeiture would be used in a similar way to its application in North American jurisdictions, where the aim of these programs was to strengthen licence sanctions in addition to deterring future offending (Beirness, Simpson, & Mayhew, 1997; Voas, 1992; Voas et al., 1998). Further, additional high-risk driving behaviours known as Type 2 offences now also attract vehicle impoundment in Queensland, which may be addressing this issue.
6.4.3 Strengths and limitations
To the best of the author’s knowledge of the published literature, this is the first study to explore the road safety implications of hooning behaviours (rather than illegal street racing alone) from the perspective of the driver. In this regard, this study contributes to the limited body of knowledge in the area, and complements Hooning behaviours 205 previous attempts to explore the road safety implications of the behaviour in terms of the proportion of all fatal crashes that involve illegal street racing (Knight et al., 2004), or describing young driver crashes that have evidence of hooning-related behaviours in the free-text crash description field (Armstrong & Steinhardt, 2006). This study has provided empirical evidence that drivers with an illegal street racing or associated hooning offence represent a significant road safety problem over and above the known risk of young males, which may justify the use of a severe penalty of vehicle impoundment or forfeiture for these types of offences in Australian and other jurisdictions. However, the results of this study should be interpreted in light of its limitations. First, drivers caught and punished for illegal street racing and associated hooning behaviour may not be representative of the (unknown) population of drivers who engage in this behaviour. While the age and gender characteristics of this sample of hooning offenders are similar to those of the sample of drivers who self- report engaging in these behaviours that participated in Studies 1a and 1b, further research should be conducted to explore whether the trends observed in this study are consistent for the entire population of involved drivers (i.e., both detected and not detected). Such research could also explore whether there are specific factors that increase the likelihood of being detected and punished for a hooning offence (or perhaps more importantly, evading detection and punishment). It was also noted in section 6.3.1 that the use of the licensing database to select drivers for the comparison group may have introduced a bias. However, given the nature of the data required for this study (traffic infringement, licence sanction, and crash data), this was the only feasible method of obtaining a comparison sample for whom the required data would be available. It could be argued that there may have been other, more appropriate, populations that could have been used as a control group in this study, such as young male traffic offenders who do not (as far as can be determined) engage in hooning. This approach was not adopted in this study for a number of reasons. First, randomly sampling a group of offenders rather than general drivers would have been more resource-intensive and, therefore, time- consuming for Queensland Department of Transport and Main Roads to complete. Second, given the exploratory nature of this research, it was not clear which type of offenders would be most appropriate to obtain a comparison group that was independent of the hooning offender sample. There was concern that young male 206 Hooning behaviours
speeding offenders would be a problematic comparison group, as illustrated by the high proportion of hooning offenders with speeding offences, and the similarities between illegal street racing and speeding. For example, it is possible that illegal street racers may receive speeding infringements detected by automatic speed detection devices, or even police officers, if there is insufficient evidence to justify a racing offence, while there is an objective measure of vehicle speed. Further, this study relied on official data collected for routine purposes that may include some errors, and only includes crashes reported to police and that meet other inclusion criteria (i.e., amount of damage). There are many other personal, social and even cultural factors that may influence hooning behaviour and general driving behaviour that may explain any between groups differences that were not able to be measured in this study. Finally, this study was limited to male hooning offenders and, therefore, the results of this study may not generalise to all hooning offenders. However, given the small number of females detected and punished for hooning offences in Queensland, the reduction in external validity is likely to be minimal.
6.5 Chapter summary
This chapter described Study 2b, which was designed to explore the road safety implications of illegal street racing and associated hooning behaviours from the perspective of involved drivers. This study compared the driving and crash histories of a sample of males caught and punished for a hooning offence in Queensland with a sample matched for age. In this regard, it was possible to explore whether hooning constitutes a significant road safety problem over and above the young driver problem, given that Study 2a confirmed that the majority of hooning offenders are young males, a group known to be at-risk of crash involvement. The results of this study revealed that the driving and crash histories of the hooning offender sample did demonstrate evidence of general on-road risk, as they had significantly more traffic infringements, licence sanctions, and crashes as a driver in the three years prior to their hooning offence relative to the comparison group. Further, the histories of drivers in the offender sample were fairly consistent with their hooning behaviour, as vehicle defect and speeding infringements were common among this sample. Hooning behaviours 207
The following chapter reports on Study 3, which describes the driving behaviour of these two samples in the three year period following the hooning offence or reference date in order to explore the second research aim of this thesis: to assess the effectiveness of current approaches to dealing with the problem. 208 Hooning behaviours
Hooning behaviours 209
CHAPTER 7: STUDY 3 – THE POST-IMPOUNDMENT DRIVING BEHAVIOUR OF HOONING OFFENDERS
7.1 Introduction
One of the research aims of this thesis was to investigate the effectiveness of current approaches to dealing with illegal street racing and associated hooning behaviours. Study 3 addressed this research aim by examining the driving behaviour of a sample of hooning offenders in the three year period after the vehicle was impounded. Three years was selected as the follow-up period as this is the prescribed period for an offender to be considered a “repeat” offender and be eligible to receive the longer impoundment or forfeiture periods in Queensland. Similar to Study 2b, a comparison group of similar aged drivers was used to control for potential age effects. Specifically, given the youthfulness of the Study 2 sample, it was possible for the younger drivers in particular to have more driving exposure in the ‘post’ impoundment period than in the ‘pre’ period, simply because they were not old enough to drive (legally) for the full three years prior to their index hooning offence, but they were more likely to drive for the full three years of the ‘post’ period. Thus these younger drivers may have had more opportunity to offend in the ‘post’ period than in the ‘pre’, and a significant increase in traffic infringements, licence sanctions and crashes may be observed that is unrelated to the vehicle impoundment penalty. The use of a same-aged comparison group to control for this potential increase in infringements due to driving exposure enables a more precise estimate of the true effect of the vehicle impoundment penalty on offenders’ driving behaviour, without the age-related bias. The general purpose of this study was to explore the second research aim of the program of research, and determine whether the vehicle impoundment penalty applied for the index hooning offence was associated with a change in driving behaviour of hooning offenders, controlling for any effects of age.
7.1.1 Research questions and hypotheses
This study addressed the fifth research question in the program of research. 210 Hooning behaviours
As noted in section 7.1, the youthfulness of the sample may result in higher numbers of traffic infringements, licence sanctions and crashes in the post-offence period compared to the pre-offence period due to exposure. Thus in order to control for this age-related effect and address the research question without bias, the traffic behaviour and crash involvement of a sample of hooning offenders were compared to the same comparison group of drivers used in Study 2b. Study 2b found that the sample of hooning offenders had significantly more traffic infringements, licence sanctions, and crashes in the three years prior to their index hooning offence compared to the group of comparison drivers. As evaluations of vehicle impoundment programs reviewed in section 2.5.3 have found that these programs are effective in reducing offending both during and after the penalty period, it was hypothesised that there would be significant group x period interactions for the relevant dependent measure. The first two hypotheses tested for this study related to the effectiveness of Queensland’s vehicle impoundment and forfeiture program in reducing future hooning behaviour. If it is an effective countermeasure for reducing hooning, then it follows that hooning infringements will be reduced, and the time between hooning infringements will be increased. As such, it was predicted that:
H1: Drivers in the hooning offender sample will have significantly less hooning infringements in the ‘post’ period compared to the ‘pre’ period; and H2: For drivers in the hooning offender sample with hooning infringements in both the ‘pre’ and ‘post’ periods, the time between hooning infringements will be significantly increased
To explore whether the effects of Queensland’s vehicle impoundment and forfeiture program extend beyond hooning behaviours, the third hypothesis was that:
H3: Drivers in the hooning offender sample will have significantly less traffic infringements of any type in the ‘post’ period compared to the ‘pre’ period
If hypothesis three is supported, it follows that the time between traffic infringements should also be increased in the ‘post’ period:
H4: For drivers in the hooning offender sample with traffic infringements of any type in both the ‘pre’ and ‘post’ periods, the time between infringements will be significantly increased Although licence sanctions and crashes during the ‘post’ period were Hooning behaviours 211 included in the data request for this study, no hypotheses were tested relating to these dependent measures. Further analyses with licence sanctions was considered inappropriate based on the results of Study 2b, where it was found that the most common sanctions were those related to exceeding the maximum demerit points on the individual’s licence. As points accrue over a period of up to three years in Queensland, this would mean that sanctions of this type were more likely in the ‘post’ period due to behaviour that occurred in the ‘pre’ period, and therefore were not sufficiently sensitive to evaluate the effectiveness of vehicle impoundment and forfeiture programs for hooning. Changes to the Graduated Driver Licensing system in Queensland during the ‘post’ period also meant there was an additional type of licence sanction (Late Night Driving Restriction) in the ‘post’ data that was not possible in the ‘pre’ data. Further, due to delays in finalising15 crash data, a full three-year ‘post’ period was not available for analysis for all drivers. The end date for the follow-up period for the offender group varied between July 1, 2008 and September 30, 2009, while the end date for all drivers in the comparison group was February 12, 2009. The crash information was finalised up to September 30, 2008 at the time this thesis was finalised. Although the index date (and therefore length of the follow-up period) for the comparison group was the same for all drivers (961 days), the length of the follow-up period differed amongst the offender group (range 732 – 1095 days), and the ‘post’ period was a full three years for only 138 of the offenders, as their index offence date was between July 1 and September 30, 2005. Although crashes could have been recoded as a rate variable (i.e., crashes per year), analyses were not performed on crash data in this study as statistical power was inadequate.
7.2 Method
7.2.1 Samples
7.2.1.1 Hooning offenders
The group of 802 drivers with a hooning infringement in Queensland between July 1, 2005 and September 20, 2006 that formed the sample for Study 2b were the
15 There can be delays of 12-18 months verifying (finalising) crash details. 212 Hooning behaviours
sampling population for this study. However, as the purpose of this study was to examine the effectiveness of vehicle impoundment as a countermeasure for hooning, only those drivers for whom there was evidence that vehicle impoundment was applied were retained. As noted in section 5.3.3 of this thesis, where Study 2a was described, 10 of the 848 infringements did not result in vehicle impoundment, and the modus operandi field did not include any information regarding vehicle impoundment for a further 198 infringements. In order to be certain that all of drivers in the offender sample in this study had experienced vehicle impoundment, offenders whose vehicles were not impounded for their hooning infringement (n = 10) or for whom information about vehicle impoundment was not available (n = 182) were excluded from this study, leaving a sample of 610 hooning offenders.
7.2.1.2 Comparison group
The comparison group for this study consisted of 610 male drivers from the Study 2b comparison group sample. The 192 drivers deleted from this sample were randomly selected based on their age so that the age distributions of the two samples remained statistically equivalent.
7.2.2 Design
Similar to Study 2b, this study involved a case / comparison design, where the independent variables were group (hooning offender vs. comparison group) and time (three years pre-impoundment [or pre-index date for the comparison group] vs. post-impoundment [or post-index date for the comparison group]). Although the focus of this study was on the effects of vehicle impoundment, and therefore the offender sample, the comparison group sample were included to control for the age- related effects described in section 7.1. As was the case in Study 2b, the reference date for the hooning offender group was their hooning offence date (or first hooning offence date for those with more than one hooning offence during the study period). As the comparison group did not have an offence date to use as a reference, the date used for all drivers in the comparison sample was February 12, 2006, as this was the median reference date for the hooning offender sample. Thus for all drivers in the comparison group sample, Hooning behaviours 213 the ‘pre’ period was from February 12, 2003 – February 11, 2006, and the ‘post’ period was from February 13, 2006 – February 12, 2009. The dates of the ‘pre’ and ‘post’ periods varied for the offenders.
7.2.3 Data sources
The data sources for this study were the same as those used in Study 2b, as the Queensland Government’s Department of Transport and Main Roads provided information about the traffic and crash behaviour of drivers in both samples. However, as noted in section 7.1.1, licence sanction and crash datasets were not analysed in this study, and are therefore not described here. The data analysed in this study included descriptions of all traffic infringements that occurred in Queensland included in the TRAILS database. However, only infringements that occurred in the three years following the reference date were included in the analyses for this study. As per Study 2b, only infringements that were upheld were included in the analyses, as all those that were waived on appeal were deleted.
7.2.4 Procedure
This study was included in the Queensland Police Service, University Ethics Committee and Health and Safety applications described in Chapters 5 and 6. One month after the latest end date (September 30, 2009), the licence, traffic and crash histories for the hooning offender and comparison group samples were requested. As noted in section 7.2.3, this information was available for the traffic infringement and licence sanction data, but crash information was only complete up until September 30, 2008. All of the available data were provided, and the crash data request remains open so these data will be provided when available, and can be analysed at a later date16.
7.2.4.1 Data coding
Following the same procedure as described in section 6.2.4.1, the de-
16 At the time this thesis was finalised, the remaining data required was expected in 6-9 months. 214 Hooning behaviours
identified traffic infringement data files that were provided to the researcher in the form of Excel spreadsheets were coded and transformed into a numerical dataset that could be analysed using SPSS. Prior to coding, any infringements that were waived on appeal were deleted from the datasets so only upheld convictions remained. Further, any infringements where the driver was not in control of a motor vehicle or motorcycle on a public road were also deleted. Traffic infringements were recoded according to their text descriptions, and grouped into nine main offence groups and further divided into the sub-groups of offences used in Study 2b (described in Appendix D.1). Date calculations were also performed on a number of variables to facilitate hypothesis testing. For example, the number of days between the index offence (or reference date) and the most recent hooning infringement and infringement of any type in the ‘pre’ period, and number of days between the index offence (or reference) date and the next hooning infringement and infringement of any type in the ‘post’ period were calculated.
7.2.4.2 Statistical analyses
The alpha level adopted for all statistical tests was p < .05, and statistical tests were selected based on the nature of the distributions of data. While the traffic infringement data violated the assumptions of parametric tests due to heavy positive skew to the distributions, there is no non-parametric equivalent to the two-way mixed ANOVA required to test the hypotheses. Section 7.3.3 describes attempts to deal with this, including transforming the data so that it met the assumptions of the test, and performing other one-way non-parametric analyses. Further, while survival analysis is normally used to compare recidivism, this was not considered appropriate in this study as the comparison group were not offenders, as was the case in other evaluations of effectiveness of countermeasures where offenders who experienced the countermeasure were compared to offenders who did not (see Voas & DeYoung, 2002). Thus the number of days between the index hooning offence and the most recent infringement in the ‘pre’ period or subsequent offence in the ‘post’ period for the hooning offender sample were compared. Hooning behaviours 215
7.3 Results
7.3.1 Demographic characteristics of drivers
Both samples in Study 3 consisted entirely of males, with 610 drivers in each sample. The age distributions were identical, with ages at the index offence (or reference) date ranging from 16 to 49, with a median of 20 years for each sample.
7.3.2 Post-impoundment driving behaviour of hooning offenders
Of the 610 drivers in the hooning offender sample, 175 (28.7%) had at least one hooning infringement in the ‘post’ period, while 537 (88.0%) had at least traffic infringement of any type in the ‘post’ period. For both hooning infringements and traffic infringements generally, the distributions were positively skewed. The number of hooning infringements generally ranged from 0 – 5, with one driver being detected for 15 hooning infringements. The number of traffic infringements of any type ranged from 0 – 32, with only 8.0% of offenders being detected for more than 10 traffic infringements in the ‘post’ period. Table 7.1 reports the descriptive statistics for the pre- and post-impoundment driving behaviour of hooning offenders. As noted above, the distributions were heavily positively skewed, thus medians and inter-quartile ranges are reported in the table, along with means.
Table 7.1 Pre- and post-impoundment driving behaviour of hooning offenders (N = 610)
Pre-impoundment Post-impoundment Mdn IQR M Mdn IQR M Hooning infringements* 0 1 0.53 0 1 0.43 Noise and smoke-related*** 0 1 0.45 0 0 0.30 Illegal street racing 0 1 0.01 0 0 0.01 Traffic infringements*** 3 5 4.55 3 5 4.65 * p < .05; ** p < .01; *** p < .001
As shown in the table, there was a reduction in hooning-related infringements in the post-impoundment period, and noise and smoke-related hooning 216 Hooning behaviours
infringements, but no change in the number of illegal street racing infringements. There was also an increase in the number of traffic infringements of any type in the post-impoundment period. However, these tests were not interpreted in terms of the study hypotheses, as it was necessary to control for potential age effects.
7.3.3 Hypothesis testing
As discussed in section 7.1, it is necessary to test study hypotheses while controlling for age effects rather than interpreting the one-way analyses reported in Table 7.1. That is, in order to control for the age-related effect of the possibility of increased driving exposure in the post-impoundment period, the comparison sample were included in the hypothesis testing analyses. Rather than the one-way analyses, two-way analyses with independent variables of time (‘pre’ vs. ‘post’ period) and group (hooning offender vs. comparison group) were performed. In this regard, the comparison group served as a control for the potential age effects. Thus, rather than interpreting the main effect of time, two-way analyses were conducted, where the study hypotheses predicted that significant group x time interactions would be observed. Further, according to the hypotheses, the effect of time should be significantly less for the hooning offender group than for the comparison group.
7.3.3.1 Hooning infringements
As noted in section 7.3.2, the data for all measures was positively skewed, and there is no non-parametric equivalent to the two-way mixed ANOVA required to test the study hypotheses. However, ANOVA is robust to violations of assumptions when the distributions are skewed in the same direction, and the sample size in each group exceeds 30 and is roughly equal (Tabacknick & Fidell, 2001). Further, the results for the first hypothesis regarding hooning infringements were similar irrespective of whether the analyses were performed on the original data or transformed data. Thus for ease of interpretation and description, the results of the two-way mixed group x time ANOVA conducted using the original (i.e., untransformed data) are reported. There was a small but significant group x time interaction for hooning infringements, Wilks’ Lambda = 1.00, F (1, 1218) = 4.79, p = .029, η2 = .00. As Hooning behaviours 217 shown in Figure 7.1, analysis of the simple main effects of time revealed that only the offender group showed a significant reduction in the number of hooning infringements in the ‘post’ period (Wilks’ Lambda = .99, F [1, 1218] = 7.37, p = .007), representing a small effect (η2 = .01), while there was no significant change in the number of hooning infringements for the comparison group.
0.6
0.5
0.4
0.3 Offender Comparison 0.2
0.1
Mean number of hooning infringements Mean number 0 Pre Post Period
Figure 7.1. Mean number of hooning infringements in ‘pre’ and ‘post’ periods as a function of group
The second hypothesis related to the time (number of days) between the index hooning offence date and the most recent hooning infringement in the ‘pre’ period and subsequent offence in the ‘post’ period. Thus only hooning offenders with a hooning infringement in both ‘pre’ and ‘post’ periods (n = 73) were able to be included in the analysis. The Wilcoxon Signed Rank test comparing the number of days between hooning infringements was not significant (z = -1.229, p = .219, r = .10 [small effect]), as the number of days between the index hooning offence and the most recent infringement in the ‘pre’ period (Mdn = 187 days, IQR = 377) was not significantly longer than the number of days between the index hooning offence date and the next hooning infringement (Mdn = 204 days, IQR = 400). This hypothesis should be re-examined in future research, as there was an increase in the time between hooning infringements of 17 days, and although the effect size was small, 218 Hooning behaviours
increasing the sample size and therefore statistical power will allow for a more reliable test of this hypothesis.
7.3.3.2 Traffic infringements of any type
When the two-way mixed ANOVA was performed on raw (i.e., untransformed) number of traffic infringements of any type data, to test the third hypothesis, power was low for the interaction term (.24) and main effect of time (.50). Results revealed a non-significant interaction term (p = .206), although simple main effects of time revealed that there was a significant increase in traffic infringements in the ‘post’ period for the comparison group (p = .023). The analyses were repeated using the (square root) transformed data, and power was improved to .69 for the interaction term and .99 for the main effect of time. Analyses of the transformed data revealed that the group x time interaction for the number of traffic infringements of any type was significant, Wilks’ Lambda = 1.00, F (1, 1218) = 5.99, p = .015, although the effect size was small (η2 = .02). As shown in Figure 7.2, tests for the simple main effect of time revealed that only the comparison group showed a significant difference in the total number of infringements, as the number of infringements in the ‘post’ period was significantly greater than the total number of infringements in the ‘pre’ period, Wilks’ Lambda = .98, F (1, 1218) = 23.05, p < .001, representing a small effect (η2 = .02). Hypothesis 4 was tested by comparing the number of days between the most recent, and subsequent, traffic infringement of any type and the index offence date for the hooning offenders with at least one infringement in each period (n = 465) using a Wilcoxon Signed Rank test. The number of days between offences was significantly greater in the ‘post’ period (Mdn = 178, IQR = 342) compared to the ‘pre’ period (Mdn = 102, IQR = 232), z = -4.75, p < .001. Although this indicates a small effect (r = .16), it reflects an average delay of more than two months (76 days).
Hooning behaviours 219
2 1.8 1.6 Offender 1.4 Comparison 1.2 1 0.8 0.6
Mean number of traffic Mean number 0.4 0.2 infringements (transformed data) 0 Pre Post Period
Figure 7.2. Mean number of (square root transformed) traffic infringements in ‘pre’ and ‘post’ periods as a function of group
7.4 Discussion
The purpose of this study was to analyse the post-impoundment driving behaviour of the hooning offender sample in order to address the fifth research question, concerning the effectiveness of Queensland’s vehicle impoundment and forfeiture program as a countermeasure for hooning.
7.4.1 Status of hypotheses
The first two hypotheses tested in this study related to hooning infringements. Consistent with hypothesis 1, it was found that there was a significant reduction in hooning infringements for the hooning offender sample in the post-impoundment period relative to the ‘pre’-impoundment period. This may be because vehicle impoundment was an effective specific deterrent of hooning behaviour, or because the offenders became more proficient at avoiding detection and punishment. There is also the possibility that their exposure was reduced in the post-impoundment period. For example, hooning offenders may have been denied access to a vehicle even after the vehicle impoundment period ended, or had periods where they were not driving 220 Hooning behaviours
while complying with a licence sanction. It was not possible to control for these potential biases in this study with the data available. While the data relating to the number of days between the index offence date and the most recent hooning infringement in the ‘pre’-impoundment period, and subsequent hooning infringement in the post-impoundment period were trending in the direction of hypothesis 2, it was not supported. Low sample size may have resulted in inadequate power for this analysis. As noted above, there are a number of possible explanations for this effect, including an effective specific deterrent effect of vehicle impoundment, or reduced exposure to driving during the post-impoundment period. When traffic infringements of any type were explored to determine whether vehicle impoundment had a flow-on effect to other infringement types in hypotheses 3 and 4, there was no significant difference in the number of infringements of any type between the two time periods for drivers in the offender sample. That is, hypothesis 3 was not supported by the results. However, when this finding was interpreted in light of the significant increase in traffic infringements for the comparison group, then hypothesis 3 was supported by the results, as vehicle impoundment appears to have functioned as a “protective” factor, as the offender sample did not show the same increase in traffic infringements as the comparison group. Hypothesis 4 was supported, as results revealed that, among drivers who had traffic infringements in both ‘pre’ and ‘post’ periods, the time to the next traffic infringement of any type after vehicle impoundment was significantly longer (i.e., delayed) in the post-impoundment period compared to the pre-impoundment period, representing a delay of 76 days. Taken together, these results suggest that vehicle impoundment reduces the overall number of hooning infringements, and perhaps the time until the next hooning infringement. There also appears to be a significant flow-on effect to the number of traffic infringements of any type, as offenders did not show the same increase in traffic infringements as the comparison group in the ‘post’ period, and vehicle impoundment was associated with a significant delay of (on average) more than two months until the next infringement. Hooning behaviours 221
7.4.2 Implications for policy and practice
The results of this study suggest that vehicle impoundment is an effective countermeasure for reducing hooning behaviour within this sample, as the number of hooning infringements in the post-impoundment was significantly less than the pre- impoundment period, whereas there was no difference in hooning infringements for the comparison group. Thus, it cannot be argued that the reduction was due to maturation, or the hooning offenders ‘growing out’ of the behaviour, as age-related effects were controlled by the use of the comparison group in a factorial analysis. Further, the time to the next hooning infringement was trending towards providing evidence of the effectiveness of vehicle impoundment, and it was suggested that this hypothesis should be re-examined in an analysis with adequate statistical power. Although not a specific component of the research question addressed in this study, it appears that vehicle impoundment does have a flow-on effect to other driving behaviours, as the offender group did not show an increase in traffic infringements in the ‘post’ period, and there was a significant delay in the number of days until the next traffic infringement of any type compared to the number of days since the most recent infringement prior to the index hooning infringement for the offender sample. What remains unclear is whether these effects are due to a specific deterrent effect of vehicle impoundment, or a constraint effect, where the driving of the offender sample was reduced in the ‘post’ period, and this reduction in exposure has contributed to the results. Disentangling these effects is not possible with the data collected in this study, although collecting driving data from offenders (e.g., in the form of a driving diary) should be considered in future research.
7.4.3 Study strengths and limitations
This study represents the first attempt to evaluate the effectiveness of vehicle impoundment and forfeiture laws for hooning. Prior to this study, the only indicators of effectiveness were the low rates of repeat offending (Queensland Transport, 2006); however, it was argued in section 2.5.3 of this thesis that when compared to the relatively stable numbers of vehicles impounded for first hooning infringements (Queensland Police Service, unpublished data), the general deterrent effect of the 222 Hooning behaviours
laws appears weak. An additional strength of this study was the exploration of the effects of vehicle impoundment on traffic infringements other than hooning. In addition to the limitations with the sampling method discussed in section 6.4.3, there were limitations related to the data and samples available for this study. Previous evaluations of vehicle impoundment programs described in section 2.5.3 of this thesis were able to compare the post-offence driving behaviour of drivers whose vehicle was impounded with a sample of drivers who committed the same offence but did not lose their vehicles. No such comparison group was available in this research, as only 10 of the drivers in the sample did not lose their vehicles as a result of their hooning offence. Further, it was not possible to reliably explore the relative effectiveness of the differing vehicle impoundment and forfeiture periods due to small samples of offenders experiencing impoundment periods of more than 48 hours, and lack of reliable information regarding the outcome of applications for these longer impoundment periods17. While there are limitations to the use of a non-equivalent comparison group, the comparison sample of males with the same age distribution of the offender sample allowed the effect of age to be controlled in the analyses. This was important, as the data showed that there was some sort of age effect, as the number of traffic infringements of any type increased in the ‘post’ period for the comparison group, while there was no significant effect of time for the offender sample. If there was no comparison group, based on the data it would have been concluded that there was no apparent effect of vehicle impoundment on traffic infringements generally. However, the finding that there was no significant increase over time for the offender sample while one was observed for the comparison suggests that vehicle impoundment does have a flow-on effect to driving behaviour more generally than hooning, which would not otherwise have been detected. Despite the use of a comparison group in this study, it was not possible to completely control for any effect of statistical regression to the mean. This may have been a problem given that the hooning offenders in this study were a group with a high frequency of traffic offences. As such, a reduction in offences in the ‘post’ period may be expected, if the offenders were sampled at a period of peak offending.
17 Although not available for the sample of hooning offenders used in this program of research, the Queensland Department of Justice and Attorney-General has maintained details of all applications for vehicle impoundment and forfeiture orders since legislative amendments extended the application of vehicle impoundment to Type 2 offences in 2007. Hooning behaviours 223
No such regression would be expected for the comparison group. However, as it was impossible to determine that the offenders were high frequency offenders at the peak of their offending trajectory prior to this study, any regression to the mean effect could not be assessed or controlled. A method of control that may be possible in future research would be to randomly allocate hooning offenders to receiving or not receiving vehicle impoundment and comparing their post-offence driving behaviour, rather than comparing the driving behaviour of hooning offenders to that of drivers without such an offence. However, this approach could compromise the vehicle impoundment program in Queensland by affecting perceptions of the certainty of punishment, and increasing drivers’ experience with punishment avoidance even when detected by police. An additional limitation of this study was the reliance on official data. Future research would benefit from the collection of self-report driving data in addition to collecting data from official sources, assuming it is possible to recruit and retain a representative sample of offenders for an adequate follow-up period. While it is not possible to collect the same data ‘pre’ a hooning offence that has not yet occurred, the self-report data could give depth to the description of the post-impoundment driving behaviour of hooning offenders. This approach has the additional benefit of being able to collect data that is otherwise unavailable in official data sources. For example, data regarding the access to other vehicles during the impoundment period, when the vehicle was collected after the impoundment period had ceased, whether non-legal restrictions were placed on driving (i.e., a parent not allowing their child to use the family car), or whether the driver was subject to (and compliant with) a licence sanction that may influence evaluations of the effectiveness of vehicle impoundment programs by influencing driving exposure.
7.5 Chapter summary
The purpose of this study was to evaluate the effectiveness of Queensland’s vehicle impoundment laws for hooning. It was found that vehicle impoundment was associated with significant reductions in the number of hooning infringements post- impoundment, that could not be considered a maturation effect where the change in behaviour can be attributed to an individual ‘growing out’ of hooning. Given greater statistical power, it is also possible that vehicle impoundment will be associated with 224 Hooning behaviours
significant delays in the time until the next hooning infringement. Vehicle impoundment was also associated with increasing the time until the next traffic infringement of any type. This represents the final study in the current program of research. The following chapter draws together the results of this and the other studies in this program in terms of the key research questions and research aims of this thesis. Hooning behaviours 225
CHAPTER 8: DISCUSSION
8.1 Introduction
This thesis described a program of research concerning illegal street racing and associated (hooning) behaviours. Three research aims were developed based on a review of the relevant literature:
RA1. To investigate the road safety implications of illegal street racing and associated (hooning) behaviours, in terms of the risks associated with the specific behaviours, and the drivers who engage in these behaviours; RA2. To assess the effectiveness of current approaches to dealing with the problem; and RA3. To inform policy and practice in the area of illegal street racing and associated hooning behaviour.
In addition, five key research questions were identified to guide the program of research:
RQ1. Who engages in hooning in an Australian context?; RQ2. What are the psychological, social and legal factors that contribute to hooning behaviours?; RQ3. What are the road safety implications of hooning behaviours?; RQ4. Do drivers who engage in hooning also engage in other risky driving behaviours?; and RQ5. How effective are vehicle impoundment and forfeiture programs at reducing hooning behaviour?
This program of research involved three complementary studies designed to explore the key research questions and overall research aims, as presented in Table 8.1. Study 1a was described in Chapter 3, and explored all of the key research questions using qualitative methodology. It was designed to provide a foundation for the program of research, and inform the development of Study 1b. Study 1b (reported in Chapter 4) also explored all of the research questions from the perspective of the hooning driver, using quantitative methodology. The focus then shifted from involved drivers to drivers with a hooning offence in Queensland for the remaining two studies. 226 Hooning behaviours
Table 8.1 Key research questions of program of research by Study and thesis chapter
RQ1 RQ2 RQ3 RQ4 RQ5 Ch. Who engages Contributing Road safety Other risky Effectiveness of in hooning? factors implications behaviours impoundment Study 1a: 3 Qualitative research with drivers who engage in hooning; Self-report data Study 1b: 4 Quantitative research with drivers who engage in hooning; Self-report data Study 2a: Study 2a: Hooning Hooning 5 offenders; offenders; Official data Official data
Study 2b: Hooning offenders & 6 comparison group; Official data
Study 3: Hooning offenders 7 & comparison gp.; Official data
Study 2a was described in Chapter 5, and involved an in-depth profile of hooning offenders and their offences over a 15-month period. This study addressed research questions one and three, and underpinned Studies 2b and 3. However, Study 2a was also useful in that trends in the data allowed additional avenues of inquiry to be identified and explored in the other studies in the program of research18. Chapter 6 described Study 2b, which was designed to explore research questions three and four using the Study 2a sample. This study explored the general risk of the drivers detected and punished for a hooning offence (as opposed to hooning behaviours), and whether the official driving and crash history data for hooning offenders suggested that they engaged in other risky driving behaviours. The official driving and crash histories of hooning offenders was compared to the same data for a random sample of drivers of the same age to determine whether the evidence of road safety risk for these drivers was greater than that for age-matched drivers. Finally, Chapter 7 reported Study 3, where the post-impoundment driving
18 Although Studies 1a and 1b are reported first in this thesis, they were conducted at the same time that data collection and analysis was occurring for Study 2a. Hooning behaviours 227 and crash behaviour of the Study 2 sample was examined in order to explore research question five. This chapter discusses the findings of each of these studies together in order to draw more general conclusions about the status of the key research questions (section 8.2) and research aims (section 8.3) of this thesis.
8.2 Review of findings
8.2.1 RQ1: Who engages in hooning in an Australian context?
The findings of Study 1 and Study 2a indicate that, consistent with the illegal street racing literature reviewed in section 2.2 of this thesis, drivers involved in hooning (including those who are detected and not detected) are typically young males. However, that is not to say that women and drivers over 25 do not participate in hooning behaviours. Among the participants in Study 1 and offenders in Study 2a, up to 25% of people did not meet the profile of the typical hooning driver. While the results relating to who engages in hooning behaviours suggest that hooning may be viewed as part of the broader young driver problem, it is important that enforcement and prevention strategies focus on the whole problem, and are not limited in focus to young male drivers alone. The finding that predominantly young male drivers engage in the behaviour also had implications for the selection of an appropriate comparison group for Studies 2b and 3. Using a comparison group from the general driving population would have been problematic, given the over-representation of young males in the Study 2a sample. In this case it was important that the demographic characteristics of the comparison sample matched those of the offender sample in an attempt to control for the known higher driving risk associated with young male drivers.
8.2.2 RQ2: What are the legal, social and psychological factors that contribute to hooning behaviours?
The findings of Studies 1a and 1b indicate that there are a number of legal, social and psychological factors that contribute to hooning behaviours. While some of the legal factors encapsulated in expanded deterrence theory were related to 228 Hooning behaviours
hooning behaviours in Study 1b, the relationships were weak (although this is the case for many road user behaviour studies), and sometimes in the opposite direction to that predicted by the theory. The finding that perceptions of the severity of vehicle impoundment was not related to any of the dependent measures in Study 1b is important, as it suggests that increases in penalties are not necessarily going to be effective in reducing target behaviour in isolation. However, the finding that perceptions of the likelihood of detection is negatively related to hooning is promising, and may suggest that increasing these perceptions via visible enforcement and public education campaigns about enforcement and successful operations may have an impact on hooning behaviour. The strongest deterrence predictors were punishment avoidance, which is consistent with other road safety research discussed in this thesis. Further, the additional social learning theory variables explained significant variance in frequency of hooning behaviours and intentions to engage in hooning in the next month, highlighting the utility of incorporating non-legal perspectives to better understand hooning behaviours. Other psychological factors such as driver thrill-seeking were also related to future intentions regarding hooning behaviours at the bivariate level, although these relationships were weak. Further, when entered into the regression analyses after accounting for the predictive utility of other variables, these scores only contributed to the explanation of future intentions regarding illegal street racing, and the variance explained was very small. It was concluded that consistent with Akers’ description of the theory, this finding highlights the broad spectrum of factors incorporated by the social learning perspective.
8.2.3 RQ3: What are the road safety implications of hooning behaviours?
As noted in section 2.4, the road safety implications of hooning behaviour can be conceived in terms of three indicators: the riskiness of hooning behaviour; the involvement of hooning behaviour in crashes; and the general risk associated with drivers who engage in hooning. Study 2a found that only a small percentage of hooning offences result in crashes, and these crashes tended to be single-vehicle, involving the offender losing control of the vehicle and hitting a fixed object. While this may suggest that the crash Hooning behaviours 229 risk associated with hooning behaviours per se is low, it is important to note that only crashes witnessed by police and noted in the CRISP database were able to be identified, and so may not be an accurate reflection of the true proportion of hooning offences, or hooning behaviour, that result in crashes. Although based on a small sample, the demographic survey used in Study 1a revealed that one fifth of crash-involved participants reported being involved in at least one crash each where hooning was involved. Among the larger Study 1b sample, similar results were obtained, as it was found that slightly less than one fifth of respondents reported being involved in at least one hooning-related crash as a driver in the previous three years. These hooning-related crashes tended to be non- injury crashes, lower in severity than crashes generally for this sample. It was also found that Study 1b respondents were less likely to have reported hooning-related crashes than crashes generally. However, the proportion of participants involved in hooning-related crashes in Study 1 was consistent with the general crash involvement of drivers in general population studies (Centre for Accident Research & Road Safety - Queensland, 2008; Fleiter, 2010) highlighting the risk associated with hooning. It also highlighted that official data sources are likely to underestimate the true involvement of hooning in crashes. In terms of the crash risk associated with the hooning driver, Study 2b found that (male) hooning offenders were significantly more likely to have been involved in a crash previously than the age and gender matched comparison group. Study 1b found that almost half of the participants were involved in a crash in the previous three years, which is more than double the crash involvement rate of other studies in Queensland conducted at a similar time (Centre for Accident Research & Road Safety - Queensland, 2008; Fleiter, 2010). Taken together, these results suggest that the main road safety implications of hooning behaviour may be associated with the drivers likely to engage in these behaviours. Thus, it could be argued that the driver represents a more appropriate target for intervention (i.e., through the demerit point system) than hooning behaviours per se. However, it was acknowledged in this thesis that it is difficult to objectively assess the road safety implications of hooning behaviour given the limitations in official data sources and the willingness of drivers to confess to the attending police officer that hooning was a contributing factor to their crash. 230 Hooning behaviours
8.2.4 RQ4: Do drivers who engage in hooning also engage in other risky driving behaviours?
This research question was explored using self-report data in Studies 1a and 1b, and official data in Study 2b. In all studies, it was found that drivers who engage in hooning behaviours are likely to engage in other risky (i.e., illegal) driving behaviours. The most common behaviours and related infringements were speeding and driving a vehicle with defects or illegal modifications, which appear to be related to hooning behaviours. For example, speeding is a component of racing, and some of the speeding offences (and behaviours) reported by participants may have occurred as part of an illegal street race or speed trial. While the evidence of the crash risk of hooning is limited, there is considerable evidence that speeding is related to crash involvement, and increased crash severity (e.g., Kloeden et al., 1997). Further, enforcing vehicle defects and illegal modifications is a common method of dealing with hooning in Australia when there is insufficient evidence to substantiate a hooning offence (Crang, 2006). Vehicle defects may be common in vehicles used to perform behaviours such as burn outs, where tyre tread is burned and the tyres no longer meet regulatory standards. Additionally, some drivers modify their vehicles to increase acceleration and speed capacity for racing without seeking the required approvals. When compared to the age and gender matched comparison group in Study 2b, it was found that the traffic histories of male hooning offenders were significantly greater than those of the comparison group. These results suggest that drivers who engage in hooning also engage in other risky driving behaviours, and to a greater extent than other similarly aged (male) drivers. While it was beyond the scope of this study to determine whether this indicates that hooning behaviours are a sub-set of risky driving behaviour or a unique road safety issue, the results do suggest that the group of drivers who engage in hooning behaviours warrant specific attention. Further, the number of traffic infringements and licence sanctions in their official driving histories may indicate that this group routinely fail to comply with traffic laws, and do not appear to have been sufficiently deterred by the penalties they have received. Although it is acknowledged that it is not possible to determine what their driving behaviour and therefore official driving histories would have been like without experiencing these sanctions. Hooning behaviours 231
8.2.5 RQ5: How effective are vehicle impoundment and forfeiture programs at reducing hooning behaviour?
This research question was explored using both self-report data (Studies 1a and 1b) and official data sources (Study 3). The focus group discussions in Study 1a revealed that drivers who engage in hooning behaviours are critical of Queensland’s vehicle impoundment and forfeiture laws for hooning, as they argue that it is an over- reaction to a behaviour that represents little risk, or at least less risk than other driving behaviours that attract less severe penalties. Their responses indicated that although the laws are perceived as severe (mainly for the second and subsequent offence impoundment / forfeiture periods), the main effect the laws had had on their behaviour was to push them further from public view in an attempt to avoid detection, rather than a reduction in hooning behaviour. When these issues were explored with a larger sample and quantitative methodology in Study 1b, similar results were obtained. Participants did perceive the various penalty periods as severe, and severity ratings significantly increased with each increase in the penalty period. When asked about their behaviour since the laws had been implemented, more than half of participants reported that they avoided punishment for hooning by doing it less often, which suggests a deterrent effect had been achieved. However, consistent with the results of Study 1a, the participants were more likely to report changing the location where they engaging in hooning to avoid detection. These results suggest that while the vehicle impoundment and forfeiture laws are perceived as severe, these perceptions have not necessarily translated to a reduction in hooning behaviour for all drivers, as a displacement of hooning behaviour to locations where they are less likely to attract the attention of police was a more common method of punishment avoidance than reducing hooning behaviour. However, the relocation of hooning to less populated areas can be considered an improvement in safety, as the risk to others is minimised. Further, this displacement is likely to be associated with a reduction in public nuisance. Study 3 examined official data to determine whether there had been a measurable change in driving behaviour among hooning offenders who had experienced vehicle impoundment as a penalty. While small numbers of drivers receiving the longer impoundment and forfeiture periods precluded an analysis of the differing effects of the length of the penalty, results for the whole sample indicated 232 Hooning behaviours
that there was a significant reduction in hooning behaviour in the post-impoundment period, both in terms of the number of hooning infringements, and an increase in the time between hooning infringements among those offenders who had been detected and punished for hooning infringements in both the ‘pre’ and ‘post’ periods. The reduction in the number of hooning infringements in the ‘post’ period cannot be attributed to a maturation effect (i.e., the offenders having ‘grown out’ of hooning), as this reduction was significantly greater than that observed for the comparison group, who served as a control for the effect of age in this study. However, effect sizes were small, and the reliance on official data does not allow these results to be examined for evidence of detection and punishment evasion strategies reflected in the self-report data analysed in Studies 1a and 1b. Therefore, the extent to which this reflects a specific deterrent effect remains unclear, and should be explored in future research with offenders. In addition to suggesting that vehicle impoundment and forfeiture is an effective specific deterrent for hooning behaviour, this study also found evidence of a flow-on effect to traffic infringements generally. While there was no change in the total number of infringements for the hooning offender sample, there was a significant increase in infringements over time for the comparison sample. As such, it was concluded that vehicle impoundment programs could also affect other driving behaviour by preventing a similar increase occurring within the offender sample. Further, a significant delay to the next traffic infringement of any type was also observed for the hooning offender sample. However, as this delay was not associated with a reduction in the total number of infringements for this group, this finding may have limited practical significance. Rather, it is likely an indication that the flow-on effect for traffic infringements generally was due to an effect of constraint (i.e., offenders were driving less during the post-impoundment period and, therefore, had reduced opportunity to offend and be detected and punished for traffic infringements), but they ‘caught up’ with their pre-impoundment levels of offending once their driving exposure increased after the return of the vehicle. This constraint may have been due to a number of factors, such as: not having access to an alternative vehicle during the impoundment period; being denied access to the vehicle once the impoundment period was completed; or compliance with a licence sanction. Hooning behaviours 233
8.3 Contribution to theory
Although it was not the purpose of this thesis to specifically test the relative utility of different theoretical perspectives, this research has provided further evidence of the application of these theories to risky driving behaviours such as hooning. While some of the expanded deterrence theory variables were significantly associated with frequency of current hooning behaviour and intentions regarding future hooning behaviour, the relationships were not always in the direction expected according to the theory. For example, punishment experience, perceptions of severity and the additional exploratory variable of willingness to flee were all positively related to hooning behaviours. This may suggest that rather than being useful predictors of hooning behaviours, these components of expanded deterrence theory are in some way an additional measure of frequency or intentions. For example, drivers who engage in hooning frequently, and intend to continue doing so, are more at-risk of experiencing vehicle impoundment, and so report a higher perception of severity and willingness to flee to avoid the penalty. In comparison, drivers who engage in hooning less and are less likely to continue doing so in the future may perceive less risk of punishment and, therefore, rate severity as lower, and are less likely to report willingness to flee. These results are similar to those obtained in other studies, and may reflect what Piquero and Pogarsky (2002) refer to as an “emboldening effect”. There is an increasing amount of literature in the road safety field supporting the application of social learning theory to road safety issues (e.g., Armstrong et al., 2005; DiBlasio, 1988; Fleiter, 2004, 2010; Fleiter et al., 2006; Gee Kee, 2006; Watson, 2004c). This study has contributed to that literature by demonstrating that social learning theory variables are significantly associated with hooning behaviours, and in the expected directions. That is, people who perceive that the significant others in their lives have positive attitudes towards hooning (differential association), are exposed to models of hooning behaviour (imitation), perceive that more rewards are likely to result from engaging in hooning than punishments (differential reinforcement) and hold positive attitudes towards hooning behaviour (definitions) are likely to engage in hooning behaviours more frequently, and report intentions to continue engaging in the behaviour in the future. Further, this study found that the additional social learning theory variables explained significant variability in 234 Hooning behaviours
hooning behaviours after the deterrence variables had been entered into the regression model, consistent with Akers’ (1990) assertions regarding the comprehensiveness of the theory, and the findings of other road safety research that also utilised expanded deterrence and social learning perspectives (Fleiter, 2010; Watson, 2004c). This study also found that the addition of driver thrill-seeking to the regression model after expanded deterrence theory variables and the remaining social learning theory variables have been entered does not add significantly to the prediction of hooning behaviour (with the exception of a significant but small [1%] increase in explained variance for future intentions to have an illegal street race in the next month), supporting the comprehensiveness of social learning theory. This finding was also consistent with other recent research examining the applicability of social learning theory to illegal road user behaviours, such as speeding (Fleiter, 2010). The findings of this program of research also have important practical implications for road safety, described in section 8.4 below.
8.4 Implications for road safety
The research questions described in section 8.3 above were designed to address the three research aims of this thesis. This section describes how the results have addressed the first two research aims, leading to a discussion of the practical implications for road safety (RA3).
8.4.1 RA1: The road safety implications of hooning behaviours
The review of the relevant literature in section 2.4 suggested that the crash risk associated with illegal street racing is low. The results of this thesis, specifically those relating to research question three, are consistent with this literature, as there was limited evidence of the road safety implications of hooning behaviours per se, as only a small percentage of hooning offences resulted in a crash. However, there was evidence that drivers who engage in hooning behaviours, specifically male hooning offenders, represent a significant road safety concern over and above the general young (male) driver problem. Further, self-report data from drivers who engage in Hooning behaviours 235 hooning behaviours indicated that almost half of these drivers have been involved in a crash in the previous three years, and approximately one-fifth had been involved in a hooning-related crash. Compared to existing literature reporting self-reported crash involvement in a similar period (Centre for Accident Research & Road Safety - Queensland, 2008; Fleiter, 2010), these findings suggest that hooning behaviours represent a crash risk. While there are limitations in official data sources and other factors that mean it is difficult to obtain objective evidence of the road safety implications of hooning behaviours, the small proportion of hooning offences that resulted in a crash in this study is consistent with the international illegal street racing literature, where illegal street racing was associated with few fatal crashes (Knight et al., 2004), and drivers involved in “cruising clubs” in Helsinki had extensive traffic and crash histories (Vaaranen, 2004; Vaaranen & Wieloch, 2002). The most important practical implication of the results relating to this research aim is that it raises the question of whether it is appropriate to use vehicle impoundment and forfeiture programs as a penalty for an offence for which there is limited official evidence of an associated crash risk. Specifically, it appears that the use of one of the most severe penalties in use in Australian jurisdictions is being applied to a behaviour that may not warrant such a severe response, at least from a road safety perspective, as the difference in results between the proportion of hooning offences that result in a crash and the proportion of hooning drivers reporting involvement in hooning-related crashes suggests that most hooning-related crashes are minor and do not meet inclusion criteria for road crash databases. However, it could be argued that the risk associated with the drivers involved in hooning behaviours provides evidence that the use of vehicle impoundment and forfeiture programs is justified. Although given that traffic sanctions typically apply to specific instances of behaviour rather than an individual’s pattern of behaviour, it may be more appropriate for vehicle impoundment and forfeiture laws to be applied to drivers who demonstrate a pattern of persistent risky driving behaviour (i.e., the accrual of a large number of traffic infringements and licence sanctions, and non- compliance with licence sanctions), rather than to drivers who commit a particular traffic offence, such as hooning. In this regard, vehicle impoundment and forfeiture programs could function in a similar way to demerit point systems currently in place in Australian jurisdictions, and the broader group of hooning-related behaviours in 236 Hooning behaviours
some jurisdictions. If the driving and crash histories of drivers involved in hooning behaviours are the only evidence of the significant risk associated with hooning, then this approach is more justified than the current approach that focuses on a behaviour with limited objective evidence of road safety risk. However, it is acknowledged that since this program of research commenced, the implementation of vehicle impoundment for Type 2 offences has partially addressed this recommendation, by applying vehicle impoundment to a broader group of repeat offenders, including drink drivers and unlicensed drivers. Nonetheless, the findings of this research suggest that the definition of Type 2 offenders could perhaps be expanded to include other high-risk groups, such as repeat and/or high-range speeding offenders, as is the case in Victoria, South Australia and Western Australia. Over and above these considerations, it should be acknowledged that the public nuisance aspects of hooning behaviours were a major impetus behind the introduction of vehicle impoundment for this group. As this issue was not addressed by this program of research, it is not possible to assess the success or otherwise of vehicle impoundment as a strategy to reduce public nuisance concerns about hooning behaviour. However, the displacement effects discussed throughout these thesis are likely to have reduced public nuisance.
8.4.2 RA2: The effectiveness of current approaches to dealing with the problem
This research aim was addressed by research question five. The previous literature reviewed in section 2.5.3 of this thesis concluded that vehicle impoundment programs have been generally effective in reducing drink driving, driving while unlicensed and driving while disqualified across a number of jurisdictions. These effects were also found to persist, albeit to a lesser extent, once the offenders were eligible to reclaim the vehicles, indicating that vehicle impoundment serves as a constraint during the impoundment period and has a specific deterrent impact on the future driving behaviour of drivers who experience the penalty. Although similar analysis techniques were not possible in this study, due to an insufficient sample of offenders who did not experience the penalty, the results of this study found that hooning behaviour was reduced in the post-impoundment period of offenders, and there was also a flow-on effect to traffic infringements generally. However, it was not possible to control for the exposure reducing effect of Hooning behaviours 237 the vehicle impoundment period in this study, as data relating to the specific dates and, therefore, the length of time the offender was without the vehicle was not available. Further, it is possible that the licence sanctions imposed on the offenders during the study could have resulted in reduced exposure in the post-impoundment period. Once again, it was not possible to control for this in Study 3, due to data constraints. Regardless, the effect size was small, so although there was a significant reduction in hooning infringements in the ‘post’ period, after controlling for effects of reduced exposure during impoundment (or during compliance with a licence sanction), this reduction may have limited practical significance. Finally, it is likely that the reason for the marked differences in the evidence of the effectiveness of vehicle impoundment for hooning offences in this research compared to vehicle impoundment programs evaluated in North American jurisdictions is differences in the length of applicable impoundment periods. Thus the effectiveness of the 3 month impoundment period and vehicle forfeiture for hooning should be explored within a larger sample in future research.
8.4.3 RA3: Implications for hooning-related policy and practice
Consistent with the published illegal street racing literature, the results of this program of research indicate that the road safety implications of hooning behaviours may be small, given that only a small proportion of hooning offences result in a crash. However, a large proportion of hooning drivers report hooning-related crash involvement when compared to samples of the general driver, indicating that hooning may lead to low severity crashes that are not recorded in official databases. As noted above, the implications of these results may be that the use of vehicle impoundment and forfeiture programs for hooning behaviours is not warranted, and it may be more appropriate to use vehicle impoundment and forfeiture programs to deal with drivers with high numbers of traffic infringements, licence sanctions (particularly where there is evidence that they do not comply with the sanctions) and crashes. In this regard, the next logical step in the management of these high-risk drivers is to constrain and ideally deter illegal and high risk behaviour by removing the vehicle. To some extent, this is already occurring in Queensland with the broader application of vehicle impoundment as a penalty for Type 2 offences. As already 238 Hooning behaviours
noted, however, the findings may suggest that there is a need for a broader perspective to hooning legislation, such as the inclusion of excessive speed as a hooning-related offence, which is included in the equivalent legislation in Victoria, South Australia and Western Australia. This research has also found that vehicle impoundment and forfeiture programs do appear to be somewhat effective in reducing the future hooning behaviour (and general traffic infringements) of drivers who experience the sanction, although there were uncontrolled factors that may have contributed to this reduction, and it was small. Data collection practices in Queensland have been recently enhanced by a centralised vehicle impoundment database (maintained by the Department of Justice and the Attorney-General), which includes information about the length of the impoundment period. Further, it is possible to measure the driving exposure of offenders during and post-impoundment via self-report and / or observational data collection techniques. Thus, more sensitive evaluations of the effectiveness of vehicle impoundment laws for hooning could be conducted in future research if these techniques were adopted. As noted previously, any effects of vehicle impoundment and forfeiture programs as a countermeasure for hooning should be compared against the operational and resource costs of managing such programs to justify the continued use of traffic policing resources. The evaluation of vehicle impoundment undertaken in this research did not assess the costs involved in implementing and managing the countermeasure and, hence, did not attempt to calculate a benefit:cost ratio for the measure. Given that the road safety benefits of the countermeasure appear limited, any future attempts to calculate a benefit:cost ratio from a “whole-of-government” perspective would need to include some estimate of the public nuisance management benefits of applying vehicle impoundment to hooning offenders. Finally, it is acknowledged that there have been changes in policy and practice in Queensland that may have influenced the results obtained in this thesis (e.g., Graduated Driver Licensing and Type 2 offences for vehicle impoundment that were introduced during the post-impoundment period), or that address some of the concerns raised about access to data (e.g., enhancements to vehicle impoundment period data collection by the Queensland Department of Justice and Attorney-General). The results of this program of research may be useful in the design phase of interventions that aim to reduce or prevent hooning behaviours. For example, the use Hooning behaviours 239 of multiple approaches may be warranted, given that the studies reported in this thesis and previous research (Armstrong & Steinhardt, 2006) indicate that drivers who engage in hooning are not a homogenous group. In addition, further consideration should be given to the influence of significant others on hooning behaviour. For example, education campaigns could encourage friends to protect their friends by discouraging (or at least not encouraging) hooning behaviour. Given that most people who engage in hooning behaviours are young, and a significant proportion of hooning offenders in this research were driving a vehicle that was not registered to them at the time of the hooning offence, the possibility of targeting the registered owner of these vehicles (such as parents) could be a useful strategy to address hooning. Current legislative provisions allow registered owners to appeal impoundment for a hooning offence if they can successfully establish that they were not the driver, nor were they aware of the hooning behaviour. However, if the vehicle is used in a subsequent hooning offence, the non-involved registered owner cannot appeal (Folkman, 2005). While such provisions are important for protecting the rights of non-involved owners, particularly those whose vehicles are stolen and then used in an offence, they may also facilitate the avoidance of punishment by hooning offenders, and even encourage risky drivers to avoid registering a vehicle in their name. A non-legal approach to this issue may include education campaigns that encourage parents to carefully monitor the driving behaviour of their teenagers, as suggested by Smart et al. (2010), or to deny the risky driver access to the vehicle. A more controversial legal approach would be to impose sanctions on registered owners who allow hooning drivers to use their vehicles. Future research is required into the likely effectiveness of these strategies.
8.5 Strengths and limitations of the research
The strengths and limitations of each particular study were discussed in the relevant chapters in this thesis. As a whole, the most important limitations across the studies related to the samples used, and the limitations of official data sources. Although attempts were made to recruit a representative sample of drivers who engaged in hooning, it was not possible to assess the representativeness of the samples used in Studies 1a and 1b beyond comparing the age and gender characteristics of the participants to those of the offender sample used in Studies 2a, 240 Hooning behaviours
2b and 3, and it was noted in these chapters that other key variables such as attitudes, motivations and personality would be useful in order to assess the representativeness of samples used in this research. The sample of offenders used in Studies 2a, 2b and 3 included all hooning offenders during the study period, and can therefore be considered an unbiased representation of hooning offenders. What remains unclear is whether hooning offenders are representative of the population of drivers who engage in hooning behaviours (i.e., those who are detected and punished and those who are not). Further, it was noted that the comparison group used in Studies 2 and 3 of this program of research may have introduced a bias, as these drivers were sourced from the Queensland licensing database and, therefore, this group may have been more likely than the offender sample to reside in Queensland and have increased exposure to traffic policing. However, it was not possible to use a comparison group of hooning offenders who did not experience impoundment as has been done in previous research. Finally, it was argued that any bias relating to this comparison group was in the opposite direction to hypotheses, and so this represented a power problem rather than a Type I error problem, and so does not represent a rival explanation for the results. In addition, the use of an age and gender-matched comparison group may have reduced external validity due to the sample being limited to males; however, this was also a design strength in that this represented a more appropriate comparison group than the general driving population, as it meant that the risk associated with young males could be controlled for in the analyses. Had a comparison group of general drivers been used, given the youthfulness of the hooning offender sample, it would not have been possible to determine whether any differences between the groups (i.e., evidence of risk) were due to age, a known risk factor for crashes, or the fact that these drivers engage in hooning behaviours. An additional limitation was the reliance on official data in some of the studies, which precluded control of potential extraneous variables that presented rival explanations for the results. For example, the inability to measure and, therefore, control for differences in driving exposure in the ‘pre’ and ‘post’ periods in Study 3 (particularly likely reductions in exposure in the ‘post’ period due to vehicle impoundment or restricted access to others’ vehicles for the hooning offender sample), represented a problem for assessing the effectiveness of vehicle impoundment for this group. This limitation could be addressed in the future by the Hooning behaviours 241 use of multiple methods within a single study, although it is unclear how successful attempts to recruit hooning offenders would be relative to a comparison group, which may represent a selection bias. The limitations in the official data available for analysis meant that some research questions of interest were unable to be fully investigated, and alternative strategies for addressing the research aims were developed. It was this attempt to explore the research aims from different perspectives, using a variety of methodological approaches and sampling populations, that was a major strength of this program of research, as more confidence can be placed in results that are observed in multiple populations using a variety of methodologies. While this research was limited in that it was not intended to be a comparative test of different theoretical perspectives, the use of a multi-disciplinary theoretical approach to guide the program of research could still be considered a strength. First, this approach guided the manner in which the research aims were addressed, and the results relating to particular research questions were interpreted. Second, the use of theories that have been applied to other deviant behaviours, and a number of other road safety issues, facilitated a comprehensive analysis of the factors contributing to hooning behaviours, thereby enhancing the likely applied benefits of the research. Finally, this program of research represents the first attempt to objectively explore the road safety implications of hooning behaviour, and the effectiveness of vehicle impoundment and forfeiture laws as a countermeasure for these behaviours in Australia, despite the implementation of varying forms of these laws in all jurisdictions. Given the similarity in approaches across jurisdictions, the results of this program of research may be useful to other Australian jurisdictions. In addition, given that vehicle impoundment programs exist in a range of other countries, this research may be relevant to those jurisdictions considering the broadening of vehicle impoundment programs to illegal street racers and other similar groups of drivers.
8.6 Suggestions for future research
Suggestions for improvements to data collection practices were made throughout this thesis, and it was acknowledged that some (e.g., a vehicle impoundment database) have already been implemented in Queensland. While the 242 Hooning behaviours
addition of “hooning”, or even the prescribed behaviours considered hooning in Queensland, as a specific factor/s contributing to crashes does not address the issue of drivers being unlikely to spontaneously confess the involvement of hooning in a crash to police, it may improve the quality of the data collected, and facilitate the extraction of information relating to hooning-related crashes where the involvement of hooning was known to police (e.g., in situations such as the hooning offences in Study 2a where hooning behaviours that led to a crash that was witnessed by police). The collection and analysis of additional information about the vehicle impoundment period and the driving behaviour of offenders during this time will enhance future evaluations of vehicle impoundment and forfeiture programs for hooning, and control for some of the rival explanations for reductions in hooning and general traffic infringements in the post-impoundment period that was not possible in this study. This will allow a more sensitive estimate of the effect of vehicle impoundment and forfeiture programs for hooning to be calculated, and used in cost- benefit analyses to inform the ongoing use of these countermeasures for hooning. There were some power issues in this study that could be addressed in future research by using a larger sample of offenders, and perhaps a longer follow-up period. These approaches were not possible in this program of research due to time constraints. Of particular concern was the low power relating to analyses involving crashes. Given that crashes are relatively rare events, it would be necessary to collect data from a larger sample over a longer time period to obtain sufficient data for analysis. Further, sufficient time post-crash is required to allow the crash data to be finalised by the relevant agency and provided for analysis. A limitation of relying on official data alone to evaluate the effectiveness of countermeasures is that researchers must make assumptions about why an effect has occurred. For example, when offending is reduced in the post-sanction period, it is assumed that this is the result of a deterrent effect. However, it is possible that there are other reasons for this effect that are not apparent in official data. For example, Study 1a and 1b participants reported a shift rather than a reduction in their hooning behaviour in response to the introduction of vehicle impoundment and forfeiture laws. To enhance the quality of future evaluations of vehicle impoundment programs, the analysis of official data should be complemented by self-report research with the group. While this approach was beyond the scope of this thesis in terms of both time and budget, it would be beneficial in that researchers could Hooning behaviours 243 improve their understanding of the true effects of vehicle impoundment on offenders, and their driving behaviour during the penalty period. Such research should be conducted independently of government agencies (although the only method of recruitment would be via these agencies), and it may be necessary to compensate participants for their time. To monitor any effects of volunteer bias, the characteristics of offenders who agree to participate must be compared to those of offenders who refuse. Evaluations of the effectiveness of vehicle impoundment and forfeiture programs for hooning should be conducted periodically over time to determine whether there are any changes in effectiveness, or whether amendments to the program are required to enhance road safety outcomes. It will also allow researchers to monitor whether other initiatives (e.g., Graduated Driver Licensing programs) that are implemented over time have an indirect influence on hooning behaviour. Given that vehicle impoundment is also used for Type 2 offences in Queensland, it may be useful to explore whether there are differential effects of vehicle impoundment on the different types of offences to which is it applied. It will also be important to consider the potential combined effects of vehicle impoundment for Type 1 and Type 2 offences in Queensland, and how these programs act together to affect driver behaviour. Finally, as the body of knowledge regarding the factors contributing to hooning behaviours evolves, it will be useful to use this evidence to focus on the design and implementation of additional countermeasures designed to reduce hooning behaviours. For example, it may be beneficial to explore whether education or other reformative practices can reduce hooning behaviour. Such programs could be general in the focus (i.e., designed to deter drivers from commencing hooning behaviour), or more specific, and form part of the penalty process for drivers detected and punished for hooning. Similar approaches are used for other offences in Queensland. For example, drink driving offenders in Queensland can opt to participate in the rehabilitative program “Under the Limit” as part of their punishment. While the evidence relating to the effectiveness of driver improvement programs for traffic offenders is not particularly encouraging, more promising results have been obtained for drink driving rehabilitation programs (Wells-Parker, Bangert- Downs, McMillen, & Williams, 1995). Future research could develop and evaluate a program targeting hooning behaviours, drawing on the effective features of drink 244 Hooning behaviours
driving rehabilitative programs. Further, future research could explore whether the increased availability of legal racing venues and skid pans is associated with a reduction in hooning behaviours on public roads.
8.7 Conclusion
This program of research aimed to investigate the road safety implications of hooning behaviours, and the effectiveness of vehicle impoundment and forfeiture programs at reducing these behaviours, in order to inform policy and practice in the area. It was found that there is limited evidence of the road safety risk of hooning behaviours; although drivers who engage in these behaviours have driving and crash histories that indicate they are risky drivers warranting specific attention, and the self-reported hooning-related crash involvement of hooning drivers suggests that official data underestimates the true involvement of hooning in crashes. Queensland’s vehicle impoundment and forfeiture laws for hooning appear to have been effective in reducing both hooning infringements and traffic infringements generally; however, these effects are small, meaning that they may be of little practical significance. Self-report data also suggests that the vehicle impoundment laws for hooning are more likely to have displaced the hooning problem to locations where they are less likely to attract the attention of police than reduced the behaviour. Further, it was not possible to control for the effects of reduced exposure in this study, and should these effects be controlled in future research, it is possible that the effects of the laws on future driving behaviour observed in this study are no longer statistically (or practically) significant. On the basis of the results of this research, and issues relating to official data, recommendations were made regarding enhancements to data collection and management practices that would facilitate future hooning research. It was also recommended that evaluations of vehicle impoundment and forfeiture laws be periodically undertaken to inform the management of the countermeasure, and provide evidence that the costs of such a program do not exceed the road safety benefits. However, on the basis of the low proportion of hooning offences that result in a crash, it appears that hooning behaviours per se do not represent a significant road safety problem and, therefore, do not necessarily warrant the use of road safety Hooning behaviours 245 resources or such a severe traffic penalty. However, hooning may still warrant the use of policing resources, as it appears to represent a public nuisance problem for the community, and a relatively large proportion of hooning drivers self-report hooning- related crash involvement. Furthermore, drivers who engage in hooning behaviours show evidence of being a road safety problem due to lengthy traffic and crash histories. Therefore, drivers with such histories (who may or may not have been detected for a hooning offence) may represent a more appropriate target for intervention, which to some extent is being addressed by the application of vehicle impoundment for additional (Type 2) offences in Queensland. Thus, there is a need to continue to monitor the management and effectiveness of vehicle impoundment and forfeiture laws for both hooning (Type 1) and Type 2 offences in Queensland. 246 Hooning behaviours
Hooning behaviours 247
REFERENCES
AAP. (2010, January 18). Death of five sparks call to crush hoons' cars. www.news.com.au, from http://www.news.com.au/breaking-news/death-of- five-sparks-call-to-crush-hoons-cars/story-e6frfku0-1225820701421 Akers, R. L. (1977). Deviant behaviour: A social learning approach (2nd ed.). Belmont, CA: Wadsworth Publishing Company. Akers, R. L. (1990). Rational choice, deterrence and social learning theory in criminology: The path not taken. The Journal of Criminal Law & Criminology, 81(3), 653-676. Akers, R. L. (1994). Criminological theories: Introduction and evaluation. Los Angeles, CA: Roxbury Publishing Company. Akers, R. L. (1998). Social learning and social structure: A general theory of crime and deviance. Boston, MA: Northeastern University Press. Akers, R. L., Krohn, M. D., Lanza-Kaduce, L., & Radosevich, M. (1979). Social learning and deviant behavior: A specific test of a general theory. American Sociological Review, 44, 636-655. Akers, R. L., & Lee, G. (1996). A longitudinal test of social learning theory: Adolescent smoking. Journal of Drug Issues, 26(2), 317-343. Altman, C. (2006, January 15). Top up the tank with testosterone, mate. Independent Weekly, p. 3. Armstrong, K. A., & Steinhardt, D. A. (2006). Understanding street racing and "hoon" culture: An exploratory investigation of perceptions and experiences. Journal of the Australasian College of Road Safety, 17, 38-44. Armstrong, K. A., Wills, A. R., & Watson, B. C. (2005). Psychosocial influences on drug driving in young Australian drivers. Paper presented at the 2005 Australasian Road Safety Research, Policing and Education Conference, Wellington, New Zealand. Arnett, J. J., Offer, D., & Fine, M. A. (1997). Reckless driving in adolescence: 'State' and 'trait' factors. Accident Analysis & Prevention, 29, 57-63. Australian Bureau of Statistics. (1997). Australian Standard Classification of Occupations (2nd edition). Canberra: Australian Bureau of Statistics. Retrieved August 8, 2007 from http://www.ausstats.abs.gov.au/ausstats/free.nsf/0/A86A0162E6F672DFCA2 56ADB001D10D4/$File/asco.pdf. Australian Bureau of Statistics. (2006). Motor Vehicle Census. Retrieved January 5, 2010, from http://www.ausstats.abs.gov.au/Ausstats/subscriber.nsf/0/61D1D30E79B4AF 3BCA257234001C2654/$File/93090_31%20mar%202006.pdf Australian Bureau of Statistics. (2009). Regional Wage and Salary Earner Statistics, Australia - Data Cubes, 2005-06. Retrieved January 5, 2010, from http://abs.gov.au/ausstats/[email protected]/mf/5673.0.55.003#PARALINK6 Begg, D. J., & Langley, J. (2001). Changes in risky driving behavior from age 21 to 26 years. Journal of Safety Research, 32, 491-499. Beirness, D. J., Mayhew, D. R., Simpson, H. M., & Desmond, K. (2004). The Road Safety Monitor 2004: Young Drivers. Ontario, Canada: Traffic Injury Research Foundation. Beirness, D. J., Simpson, H. M., & Mayhew, D. R. (1997). Evaluation of 248 Hooning behaviours
administrative licence suspension and vehicle impoundment programs in Manitoba. (TP-13096 E). Ottawa, Canada: Transport Canada. Beirness, D. J., Simpson, H. M., Mayhew, D. R., & Jonah, B. (1997). The impact of administrative licence suspension and vehicle impoundment for DWI in Manitoba. Paper presented at the 14th International Conference on Alcohol, Drugs and Traffic Safety, Annecy, France. Briscoe, S. (2004). Raising the bar: Can increased statutory penalties deter drink drivers? Accident Analysis & Prevention, 36, 919-929. Cameron, M., Cavallo, A., & Gilbert, A. (1992). Crash-based evaluation of the speed camera program in Victoria 1990-1991, Phase 1: General Effects, Phase 2: Effects of program mechanisms. (Report No. 42). Melbourne: Monash University Accident Research Centre. Carrabine, E., & Longhurst, B. (2002). Consuming the car: Anticipation, use and meaning in contemporary youth culture. The Sociological Review, 50(2), 181- 196. Cavallo, A. (2006). Victoria's new Graduated Driver Licensing System. Retrieved July 16, 2007, from http://www.carrsq.qut.edu.au/documents/cavallo.pdf Centre for Accident Research & Road Safety - Queensland. (2008). Rural and remote road safety study: Final report [Electronic Version]. Retrieved October 12, 2010, from http://eprints.qut.edu.au/26539/ Chandraratna, S., Stamatiadis, N., & Stromberg, A. (2005). Potential crash involvement of young novice drivers with previous crash and citation records. Transportation Research Record: Journal of the Transportation Research Board, 1937, 1-2. Chen, W., Cooper, P., & Pinili, M. (1995). Driver accident risk in relation to the penalty point system in British Columbia. Journal of Safety Research, 26, 9- 18. Christensen, L. B. (2007). Experimental methodology (10th ed.). Boston: Pearson Education, Inc. Cox, N. (2007, February 2). WA a state of driving hoons. Perth Now, from http://www.perthnow.com.au/wa-a-state-of-driving-hoons/story-e6frg4iu- 1111112937371 Crang, I. (2006). Personal communication, May 22. Queensland Police Service. Dawes, G. (2000). The culture of joyriding in Queensland: The offenders perspective. Paper presented at the Australasian Road Safety Research, Policing and Education Conference, Brisbane, Australia. Dawes, G. (2001). Time to ride: Youth and the culture of joyriding in rural Queensland. Paper presented at the Character, Impact and Prevention of Crime in Regional Australia Conference, Townsville, Australia. Dawes, G. (2002). Figure eights, spin outs and power slides: Aboriginal and Torres Strait Islander youth and the culture of joyriding. Journal of Youth Studies, 5(2), 195-208. Deery, H. A., & Fildes, B. N. (1999). Young novice driver subtypes: Relationship to high-risk behavior, traffic accident record, and simulator driving performance. Human Factors, 41, 628-643. Department of Transport and Main Roads. (2009). Queensland Current Driver Licences as at 30 June, 1993 to 2009. Retrieved January 5, 2010, from http://www.transport.qld.gov.au/resources/file/eb86254b7b17b4e/Pdf_stats_li cences_on_record_queensland.pdf DeYoung, D. J. (1997). An evaluation of the specific deterrent effect of vehicle Hooning behaviours 249
impoundment on suspended, revoked and unlicensed drivers in California. (CAL-DMV-RSS-97-171). Sacramento, CA: California Department of Motor Vehicles. DeYoung, D. J. (1998). An evaluation of the general deterrent effect of vehicle impoundment on suspended and revoked drivers in California. (CAL-DMV- RSS-98-180). Sacramento, CA: California Department of Motor Vehicles. DeYoung, D. J. (1999). An evaluation of the specific deterrent effects of vehicle impoundment on suspended, revoked, and unlicensed drivers in California. Accident Analysis & Prevention, 31, 45-53. DeYoung, D. J. (2000). An evaluation of the general deterrent effect of vehicle impoundment on suspended and revoked drivers in California. Journal of Safety Research, 31, 51-59. DiBlasio, F. A. (1988). Predriving riders and drinking drivers. Journal of Studies on Alcohol, 49(1), 11-15. Farley, R. (2006). Helping keep our kids safe on Western Australia's roads: Novice driver review. Retrieved July 16, 2007, from http://www.carrsq.qut.edu.au/documents/farley.pdf Fergusson, D., Swain-Campbell, N., & Horwood, J. (2003). Risky driving behaviour in young people: Prevalence, personal characteristics and traffic accidents. Australian and New Zealand Journal of Public Health, 27, 337-342. Field, A. (2005). Discovering statistics using SPSS (2nd ed.). London: Sage Publications. Fleiter, J. (2004). The role of legal, social, and personal factors in speeding behaviour: A comparison of deterrence theory. Unpublished Honours dissertation, Queensland University of Technology, Brisbane. Fleiter, J. (2010). Examining psychosocial influences on speeding in Australian and Chinese contexts: A social learning approach. Unpublished Doctoral dissertation, Queensland University of Technology, Brisbane. Fleiter, J., & Watson, B. C. (2006). The speed paradox: The misalignment between driver attitudes and speeding behaviour. Journal of the Australasian College of Road Safety, 17(2), 23-30. Fleiter, J., Watson, B. C., Lennon, A., King, M., & Shi, K. (2009). Speeding in Australia and China: A comparison of the influence of legal sanctions and enforcement practices on car drivers. Paper presented at the Australasian Road Safety Research, Policing & Education Conference. Fleiter, J., Watson, B. C., Lennon, A., & Lewis, I. (2006). Significant others, who are they? Examining normative influences on speeding. Paper presented at the Australasian Road Safety Research, Policing & Education Conference, Gold Coast, Australia. Folkman, L.-M. (2005). Queensland's anti-hoon legislation and policing methods used to prevent hooning behaviour. Paper presented at the Australasian Road Safety Research, Policing & Education Conference, Wellington, New Zealand. Freeman, J., & Watson, B. C. (2006). An application of Stafford and Warr's reconceptualisation of deterrence to a group of recidivist drink drivers. Accident Analysis & Prevention, 38, 462-471. Gee Kee, A. (2006). Comparing the utility of social learning theory and deterrence theory to predict "hooning" related driving behaviour. Unpublished Honours dissertation, Queensland University of Technology, Brisbane. Gee Kee, A., Steinhardt, D., & Palk, G. (2007). Hoon driving: Predicting 250 Hooning behaviours
involvement from social learning and deterrence perspectives. Paper presented at the Australasian Road Safety Research, Policing & Education Conference, Melbourne, Australia. Grayson, G. B. (1997). Theory and models in traffic psychology: A contrary view. In T. Rothengatter & E. Carbonell Vaya (Eds.), Traffic and transport psychology: Theory and application. Amsterdam: Pergamon. Harré, N., Brandt, T., & Dawe, M. (2000). The development of risky driving in adolescence. Journal of Safety Research, 31, 185-194. Hochstetler, A., Copes, H., & DeLisi, M. (2002). Differential association in group and solo offending. Journal of Criminal Justice, 30, 559-566. Homel, R. (1988). Policing and punishing the drinking driver: A study of specific and general deterrence. New York: Springer-Verlag. Horswill, M. S., & Coster, M. E. (2002). The effect of vehicle characteristics on drivers' risk-taking behaviour. Ergonomics, 45, 85-104. Huguenin, R. D. (1997). Do we need traffic psychology models? In T. Rothengatter & E. Carbonell Vaya (Eds.), Traffic and transport psychology: Theory and application. Amsterdam: Pergamon. Jarred, W. (2002). Police Powers and Responsibilities and Another Act Amendment Bill 2002: Confronting bad and nuisance road user behaviour (No. 2002/18). Brisbane: Queensland Parliamentary Libraryo. Document Number) Johnson, L. (2007, August 1). Hoons invited to have a say. Townsville Bulletin, p. 7, Jonah, B. A. (1997). Sensation seeking and risky driving: A review and synthesis of the literature. Accident Analysis & Prevention, 29, 651-665. Kloeden, C. N., McLean, A. J., Moore, V. M., & Ponte, G. (1997). Travelling Speed and the Risk of Crash Involvement. (Report No. CR172). Canberra: Federal Office of Road Safety. Knight, S., Cook, L. J., & Olson, L. M. (2004). The fast and the fatal: Street racing fatal crashes in the United States. Injury Prevention, 10, 53-55. Lam, L. T., Norton, R., Woodward, M., Connor, J., & Ameratunga, S. (2003). Passenger carriage and car crash injury: A comparison between younger and older drivers. Accident Analysis & Prevention, 35, 861-867. Leal, N. L., Watson, B. C., & King, M. (2007). Hooning offenders and offences: Who and what are we dealing with? Paper presented at the Australasian Road Safety Research Policing and Education Conference, Melbourne, Australia. Leigh, A. (1996). Youth and street racing. Current Issues in Criminal Justice, 7(3), 388-393. Levy, M. M., & Frank, J. F. (2000). A review of research on vehicle sanctions in the USA. Paper presented at the 15th International Conference on Alcohol, Drugs and Traffic Safety, Stockholm, Sweden. Matthews, G., Desmond, P. A., Joyner, L., Carcary, B., & Gilliland, K. (1997). A comprehensive questionnaire measure of driver stress and affect. In T. Rothengatter & E. C. Vaya (Eds.), Traffic and transport psychology: Theory and application (pp. 317-324). New York: Elsevier. McDonagh, E., Wortley, R., & Homel, R. (2002). Perceptions of physical, psychological, social and legal deterrents to joyriding. Crime Prevention and Community Safety, 4(1), 11-25. Mirrlees-Black, C. (1993). Disqualification from driving: An effective penalty? (Research and Planning Unit Report No. 74). London, Great Britain: Home Office. Mitchell, M., & Jolley, J. (2001). Research design explained (4th ed.). Orlando: Hooning behaviours 251
Harcourt, Inc. Morgan, D. L. (1998a). Planning focus groups (Book 2). Focus Group Kit. Thousand Oaks, CA: Sage. Morgan, D. L. (1998b). Practical strategies for combining qualitative and quantitative methods: Applications to health research. Qualitative Health Research, 8, 362-376. Nichols, J. L., & Ross, H. L. (1990). The effectiveness of legal sanctions in dealing with drinking drivers. Alcohol, Drugs and Driving, 6(2), 33-60. Bill 203 - Safer Roads for a Safer Ontario Act, (2007). Organisation for Economic Co-operation and Development. (2006). Young drivers: The road to safety [Electronic Version]. Retrieved March 20, 2010, from http://www.internationaltransportforum.org/jtrc/safety/YDpolicyBrief.pdf Peak, K. J., & Glensor, R. W. (2004). Street racing. (Report No. 28). Washington, D.C.: U.S. Department of Justice. Peck, R., & Voas, R. B. (2002). Forfeiture programs in California: Why so few? Journal of Safety Research, 33, 245-258. Penberthy, D. (2004, November 29). Another smashing day with hoons. Daily Telegraph, p. 25. Piquero, A., & Paternoster, R. (1998). An application of Stafford and Warr's reconceptualization of deterrence to drinking and driving. Journal of Research in Crime and Delinquency, 35(1), 3-39. Piquero, A., & Pogarsky, G. (2002). Beyond Stafford and Warr's reconceptualization of deterrence: Personal and vicarious experiences, impulsivity and offending behaviour. Journal of Research in Crime and Delinquency, 39, 153-186. Popkin, C. L. (1994). The deterrent effect of education on DWI recidivism. Alcohol, Drugs and Driving, 10, 287-294. Preusser, D. F., Ferguson, S. A., & Williams, A. F. (1998). The effect of teenage passengers on the fatal crash risk of teenage drivers. Accident Analysis & Prevention, 30, 217-222. Queensland Parliamentary Travelsafe Committee. (2003). Reducing the road toll for young drivers - Is education enough? . Retrieved July 2, 2007, from http://www.parliament.qld.gov.au/TSAFE/view/committees/documents/TSA FE/inquiry/noviceDrivers/FINAL%20REPORT%20No%2040%20(SR).pdf Queensland Transport. (2006). 2006 Queensland Road Safety Summit (Transcript of Proceedings) - Wednesday, 22 February 2006. Retrieved June 26, 2006, from http://www.roadsafety.qld.gov.au/qt/LTASinfo.nsf/index/rs_summit. Queensland Transport. (2007a). Fact sheet: Learner licence changes. Retrieved June 29, 2007, from http://www.transport.qld.gov.au/resources/file/eb2bb609446f579/Pdf_young_ drivers_factsheet_learner_V3.pdf Queensland Transport. (2007b). Fact sheet: Provisional licence changes. Retrieved June 29, 2007, from http://www.transport.qld.gov.au/resources/file/eb2b860943b22ae/Pdf_young _drivers_factsheet_provisional_V3.pdf Queensland Transport. (2007c). New licensing laws for young drivers in Queensland. Retrieved June 29, 2007, from http://www.transport.qld.gov.au/resources/file/eb06f708d8a801b/Pdf_New_li censing_laws_for_young_drivers_in_Queensland.pdf Ross, H. L. (1992). Are DWI sanctions effective? Alcohol, Drugs and Driving, 8, 61- 69. 252 Hooning behaviours
Ross, H. L., & Gonzales, P. (1988). Effects of license revocation on drunk-driving offenders. Accident Analysis & Prevention, 20, 379-391. Russell, M., & Cooke, D. (2006, January 15). Drag racers rule the streets as we wait for tough new laws. Sunday Age, p. 5. Safir, H., Grasso, G., & Messner, R. (2000). The New York City Police Department DWI Forfeiture Initiative. Paper presented at the 15th International Conference on Alcohol, Drugs and Traffic Safety, Stockholm, Sweden. Simpson, H. M. (2003). The evolution and effectiveness of graduated licensing. Journal of Safety Research, 34, 25-34. Singhal, D., Simpson, H. M., Vanlaar, W., & Mayhew, D. R. (2006). The Road Safety Monitor: Public Awareness and Concern About Road Safety. Ontario, Canada: Traffic Injury Research Foundation. Smart, R. G., Mann, R. E., Stoduto, G., & Vingilis, E. R. (2010). Preventing street racing: Should we concentrate on changing the driver or the car? Paper presented at the 20th Canadian Multidisciplinary Road Safety Conference, Niagara Falls, ON. Stafford, M. C., & Warr, M. (1993). A reconceptualization of general and specific deterrence. Journal of Research in Crime and Delinquency, 30(2), 123-135. Stradling, S., Meadows, M., & Beatty, S. (2004). Characteristics and crash- involvement of speeding, violating and thrill-seeking drivers. In T. Rothengatter & R. D. Huguenin (Eds.), Traffic and Transport Psychology: Theory and Application (pp. 177-192). Oxford: Elsevier. Sweedler, B. M., & Stewart, K. (2000). Vehicle sanctions: An effective means to reduce impaired driving. Paper presented at the 15th International Conference on Alcohol, Drugs and Traffic Safety, Stockholm, Sweden. Tabacknick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Needham Heights, MA.: Allyn & Bacon. Thake, C. L. (2009). The Role of Personality in Predicting “Hooning” Related Driving Behaviour. Unpublished Honours dissertation, Queensland University of Technology, Brisbane. The Motor Report. (2010, January 22). Victoria to crush cars of repeat offending hoons. www.themotorreport.com.au, from http://www.themotorreport.com.au/49029/victoria-to-crush-cars-of-repeat- offending-hoons Tippetts, A. S., & Voas, R. B. (1997). The effectiveness of the West Virginia interlock program on second drunk-driving offenders. Paper presented at the 14th International Conference on Alcohol, Drugs and Traffic Safety, Annecy, France. Tunnicliff, D. (2006). Psychosocial factors contributing to motorcyclists' intended riding style: An application of an extended version of the theory of planned behaviour. Unpublished Masters dissertation, Queensland University of Technology, Brisbane. Vaaranen, H. (2004). The emotional experience of class: Interpreting working-class kids' street racing in Helsinki. The Annals of the American Academy of Political and Social Science, 595, 91-107. Vaaranen, H., & Wieloch, N. (2002). Car crashes and dead end careers: Leisure pursuits of the Finnish subculture of the kortteliralli street racing. Young: Nordic Journal of Youth Research, 10, 42-58. Vingilis, E. R. (1990). A New Look at Deterrence. In R. J. Wilson & R. E. Mann (Eds.), Drinking and Driving: Advances in Research and Prevention. New Hooning behaviours 253
York: Guilford Press. Vingilis, E. R., & Smart, R. G. (2009). Street racing: A neglected research area? Traffic Injury Prevention, 10, 148-156. Voas, R. B. (1992). Assessment of impoundment and forfeiture laws for drivers convicted of repeat DWI, Phase I report: Review of state laws and their application. (DOT-HS-807 870). Washington, DC: National Highway Traffic Safety Administration. Voas, R. B., & DeYoung, D. J. (2002). Vehicle action: Effective policy for controlling drunk and other high-risk drivers? Accident Analysis & Prevention, 34, 263-270. Voas, R. B., Fell, J. C., McKnight, A. S., & Sweedler, B. M. (2004). Controlling impaired driving through vehicle programs: An overview. Traffic Injury Prevention, 5, 292-298. Voas, R. B., Tippetts, A. S., & Taylor, E. (1996). The effect of vehicle impoundment and immobilization on driving offenses of suspended and repeat DWI offenders. Paper presented at the 40th Annual Conference of the Association for the Advancement of Automotive Medicine, Vancouver, Canada. Voas, R. B., Tippetts, A. S., & Taylor, E. (1997). Temporary vehicle immobilization: Evaluation of a program in Ohio. Accident Analysis & Prevention, 29, 635- 642. Voas, R. B., Tippetts, A. S., & Taylor, E. (1998). Temporary vehicle impoundment in Ohio: A replication and confirmation. Accident Analysis & Prevention, 30, 651-655. von Hirsch, A., Bottoms, A. E., Burney, E., & Wikstrom, P. O. (2000). Criminal deterrence and sentence severity. Oxford: Hart Publishing. Warn, J. R., Tranter, P. J., & Kingham, S. (2004). Fast and furious 3: Illegal street racing, sensation seeking and risky driving behaviours in New Zealand. Paper presented at the 27th Australasian Transport Research Forum, Adelaide, Australia. Watling, C., Palk, G., Freeman, J., & Davey, J. (2010). Applying Stafford and Warr's reconceptualization of deterrence theory to drug driving: Can it predict those likely to offend? Accident Analysis and Prevention, 42, 452-458. Watson, B. C. (1998). The effectiveness of drink driving licence actions, remedial programs and vehicle-based sanctions. Paper presented at the 19th ARRB Research Conference, Sydney, Australia. Watson, B. C. (2002). A survey of unlicensed driving offenders. Paper presented at the Australasian Road Safety Research, Policing and Education Conference, Adelaide, Australia. Watson, B. C. (2003). The road safety implications of unlicensed driving: A survey of unlicensed drivers. Canberra, Australia: Australian Transport Safety Bureau. Watson, B. C. (2004a). The crash risk of disqualified/suspended and other unlicensed drivers. Paper presented at the 17th International Conference on Alcohol, Drugs and Traffic Safety, Glasgow, UK. Watson, B. C. (2004b). How effective is deterrence theory in explaining driver behaviour?: A case study of unlicensed driving. Paper presented at the Australasian Road Safety Research, Policing & Education Conference. Watson, B. C. (2004c). The psychosocial characteristics and on-road behaviour of unlicensed drivers. Unpublished Doctoral dissertation, Queensland University of Technology, Brisbane. Watson, B. C., Tunnicliff, D., White, K. M., Schonfeld, C., & Wishart, D. (2007). 254 Hooning behaviours
Psychological and social factors influencing motorcycle rider intentions and behaviour. ATSB Road Safety Research Grant Report 2007-04. Canberra: Australian Transport Safety Bureau. Weinstein, N. D. (1980). Unrealistic optimism about future life events. Journal of Personality and Social Psychology, 39, 806-820. Wells-Parker, E., Bangert-Downs, R., McMillen, R., & Williams, M. (1995). Final results from a meta-analysis of remedial interventions with drink/drive offenders. Addiction, 90, 907-926. Woodward, L. J., Fergusson, D. M., & Horwood, L. J. (2000). Driving outcomes of young people with attentional difficulties in adolescence. Journal of the Academy of Child and Adolescent Psychiatry, 39(5), 627-634. Zaal, D. (1994). Traffic law enforcement: A review of the literature. (Report No. 53). Canberra: Federal Office of Road Safety.
Hooning behaviours 255
APPENDICES
Appendix A.1 Description of Queensland’s Graduated Driver Licensing system, implemented July 1, 2007 ...... 257 Appendix B.1 Example media release calling for focus group (Study 1a) participants ...... 259 Appendix B.2 Study 1a information sheet and consent form ...... 261 Appendix B.3 Study 1a participant demographic survey ...... 263 Appendix C.1 Study 1b variable table ...... 265 Appendix C.2 Study 1b online survey ...... 281 Appendix C.3 Study 1b information sheet and consent item ...... 305 Appendix C.4 Correlation matrices for Study 1b hierarchical regression analyses ...... 307 Appendix D.1 Study 2b offence groups and subgroups ...... 309
256 Hooning behaviours
Hooning behaviours 257
APPENDIX A.1
DESCRIPTION OF QUEENSLAND’S GRADUATED DRIVER LICENSING SYSTEM, IMPLEMENTED JULY 1, 2007
The minimum age for obtaining a Learner Licence in Queensland was reduced from 16 and a half years to 16 years, while the minimum period of time the licence must be held was increased from six to 12 months. Learner licence holders must display L plates, carry their licence while driving, and have a BAC of zero percent. If the Learner is under 25, neither they nor any occupants of the vehicle may use a mobile phone (hands-free or not) while the Learner is driving. Similar restrictions apply in Victoria (Cavallo, 2006). The Learner licence has only four demerit points, as is also the case in Western Australia (Farley, 2006), and accumulation of four or more points in a 12 month period will result in a three month suspension or “Good Driving Behaviour (GDB)” option19 for 12 months. Learners must keep a log book20 of their driving to demonstrate 100 hours of experience prior to attempting the practical driving test to obtain their P121 licence (Queensland Transport, 2007a, 2007c). Similarly, the new licensing systems in Victoria and Western Australia include a requirement of 120 hours driving experience for Learners (Cavallo, 2006; Farley, 2006). The P1 licence phase in Queensland lasts for a minimum of one year. P1 licence holders must display red P plates, carry their licence while driving, and have a BAC of zero percent. As per the Learner licence, the P1 licence has only four demerit points, and accumulation of four or more points in a 12 month period will result in a three month suspension or GDB option for 12 months. Restrictions on the P1 licence include peer-aged passenger restrictions between 11pm and 5am (one non-family member only), mobile phone restrictions (no mobile phone use by the driver [including hands-free kits], and no loudspeaker
19 During the 12 month GDB period, no more than one demerit point can be accumulated. If two or more demerit points are accrued, the original licence suspension period is doubled to six months. 20 Learner drivers aged 25 and over can volunteer to complete a logbook. 21 Learner drivers aged 25 and over progress to a P licence upon passing the practical driving test. 258 Hooning behaviours
mobile phone use by passengers), and restrictions on vehicle power22. In addition to these restrictions, P1 licence holders who accumulate more than four demerit points will have a late night (11pm to 5am) driving restriction imposed. P1 licence holders must pass a Hazard Perception Test (HPT) in order to graduate to the P2 licence23 (Queensland Transport, 2007b, 2007c). The Provisional phase of Western Australia’s new licensing system also includes night driving restrictions, peer-aged passenger restrictions and a zero percent BAC limit (Farley, 2006). Victoria’s new licensing system also includes P1 and P2 phases, where restrictions on vehicle power apply, and progression from P1 to P2 requires a good driving record (Cavallo, 2006). The P2 licence phase in Queensland lasts for a minimum of two years for drivers under 23, or 12 months for drivers aged 23 years. P and P2 licence holders must display green P plates, and carry their licence while driving. P2 licence holders must have a BAC of zero percent, while the maximum is 0.05 percent for the P licence. As per the Learner and P1 licence phases, the P and P2 licences have only four demerit points, and accumulation of four or more points in a 12 month period will result in a three month suspension or GDB option for 12 months. The vehicle power restrictions for P1 licence holders also apply to P2 licence holders. In addition, P2 licence holders who accumulate more than four demerit points will have a late night (11pm to 5am) driving restriction imposed. Once the minimum time period has elapsed (cumulatively), drivers graduate to an Open licence (Queensland Transport, 2007b, 2007c). Regardless of driver age, the Open licence in Queensland has a maximum BAC of 0.05 percent, and accumulation of 12 or more demerit points in a three year period results in a three month suspension or GDB option for 12 months (Queensland Transport, 2007c).
22 P1 licence holders may not drive: eight cylinder vehicles; turbo- or super-charged vehicles (except diesel); vehicles with an engine output of more than 200kw; vehicles with a rotary engine above 1146cc; or vehicles with an engine performance modification that is not standard to the original manufacturer’s vehicle specifications and requires approval from an approved person. 23 P1 licence holders aged 24 years progress to an Open licence upon successful completion of the HPT. Hooning behaviours 259
APPENDIX B.1
EXAMPLE MEDIA RELEASE CALLING FOR FOCUS GROUP (STUDY 1A) PARTICIPANTS
Volunteers wanted for hooning study
Could your driving style be considered hooning? If so, Queensland University of Technology researcher Nerida Leal wants to hear from you.
As part of a research project by QUT’s Centre for Accident Research & Road Safety – Queensland (CARRS‐Q), volunteers are being sought for a study to find out what drivers think about hooning and their views on current “anti‐hoon” legislation.
Ms Leal is looking for drivers across Queensland, who have performed a behaviour that could be construed as hooning such as racing, speed trials, burn outs, fish tails or donuts, to take part in focus groups.
“Hooning receives a considerable amount of attention in the media but there is limited research on the topic, particularly from the perspective of drivers likely to be labelled as hoons by police,” Ms Leal said.
“I am interested in finding out what these drivers think about hooning and the current police response – the ‘anti‐hooning’ legislation.”
Since the introduction of “anti‐hoon” legislation in Queensland more than 3200 vehicles have been impounded.
“The aim of my research is to establish the risk associated with both street racing and street racers, which can inform the development of prevention strategies,” she said. 260 Hooning behaviours
“Ultimately we want to make the state’s roads safer.”
Ms Leal said participants would not be asked to provide any identifying information, and all comments would be treated as confidential.
“The findings of the study will contribute to my PhD research, and may be presented at conferences or in scholarly journals,” she said.
If you are interested in taking part or want to find out more about the research, contact Nerida Leal on 3138 4545, or email [email protected]
Ms Leal’s research is supported by the Queensland Government’s Growing the Smart State PhD Funding Program.
Hooning behaviours 261
APPENDIX B.2
STUDY 1A INFORMATION SHEET AND CONSENT FORM
262 Hooning behaviours
Hooning behaviours 263
APPENDIX B.3
STUDY 1A PARTICIPANT DEMOGRAPHIC SURVEY
264 Hooning behaviours
Hooning behaviours 265
APPENDIX C.1
STUDY 1B VARIABLE TABLE
Variable Question/s Response scale Demographic characteristics Gender 3. What is your gender? 1 = Male, 2 = Female Age 4. What is your age? In years Education 5. What is the highest level of education you have completed? 1 = Primary school, 2 = Secondary school, 3 = TAFE / Technical college, 4 = Trade apprenticeship, 5 = University (undergraduate), 6 = University (postgraduate). 6. Are you currently studying? 1 = No, 2 = Secondary school, 3 = TAFE / Technical college, 4 = Trade apprenticeship, 5 = University (undergraduate), 6 = University (postgraduate). Employment 7. What is your current employment status? 1 = Not working, 2 = Studying, 3 = Employed (casual), 4 = Employed (part- 8. If you are working, what is your usual job? If you have more than one time), 5 = Employed (full-time), 6 = job, answer for your main job where you work the most hours. If you are Self-employed not working, leave blank or type N/A Driving 9. Do you need to drive for your job? 1 = No, 2 = Yes 10. What type of driver’s licence do you currently hold? 1 = Learner, 2 = P1, 3 = P2, 4 = Provisional, 5 = Open, 6 = Restricted, 7 11. How many years has it been since you first obtained a Provisional = Unlicensed licence? In years 12. On average, how many hours per week do you spend driving? In hours / week 266 Hooning behaviours
Main dependent variables Current (previous month) 2. In the last month, while driving, how many times have you: Number of times hooning frequency a) done things like burn outs, donuts, fish tails, drifting, or skids? b) taken part in street race (including time trials)? c) been part of a rolling road block, keeping back traffic while other cars raced? d) raced while others kept traffic back with a rolling road block? Future (next month) hooning 13. In the next month, how likely is it that while driving, you will: Likert scale intentions a) do things like burn outs, donuts, fish tails, drifting, or skids? 1 (very unlikely) – 7 (very likely) b) take part in street race? c) be part of a rolling road block, keeping back traffic while other cars raced? d) race while others kept traffic back with a rolling road block? Crash involvement (driver) 18. As a driver, how many times in the last 3 years have you been in an Number of times incident where: 1 = No, 2 = Yes a) you or someone else was injured? b) Did you report it (if you had more than one, please answer for the most recent crash)? c) no one was injured, but your car, or another car, needed to be towed? d) Did you report it (if you had more than one, please answer for the most recent crash)? e) no one was injured, but your car, or another car, was damaged, but didn’t need towing? f) Did you report it (if you had more than one, please answer for the most recent crash)? 19. While you were driving, how many times in the last 3 years has doing things like burn outs, donuts, fish tails, drifting, or skids led to an incident where: a) you or someone else was injured? b) Did you report it (if you had more than one, please answer for the most recent crash)? c) no one was injured, but your car, or another car, needed to be towed? Hooning behaviours 267
d) Did you report it (if you had more than one, please answer for the most recent crash)? e) no one was injured, but your car, or another car, was damaged, but didn’t need towing? f) Did you report it (if you had more than one, please answer for the most recent crash)? 20. While you were driving, how many times in the last 3 years has taking part in a street race (including time trials) led to an incident where: a) you or someone else was injured? b) Did you report it (if you had more than one, please answer for the most recent crash)? c) no one was injured, but your car, or another car, needed to be towed? d) Did you report it (if you had more than one, please answer for the most recent crash)? e) no one was injured, but your car, or another car, was damaged, but didn’t need towing? f) Did you report it (if you had more than one, please answer for the most recent crash)? Crash involvement 21. While you were a passenger, how many times in the last 3 years has Number of times (passenger) doing things like burn outs, donuts, fish tails, drifting, or skids led to an 1 = No, 2 = Yes incident where: a) you or someone else was injured? b) To the best of your knowledge, did they report it? c) no one was injured, but the car you were in, or another car, needed to be towed? d) To the best of your knowledge, did they report it? e) no one was injured, but their car, or another car, was damaged, but didn’t need towing? f) To the best of your knowledge, did they report it? 22. While you were a passenger, how many times in the last 3 years has taking part in a street race (including time trials) led to an incident where: a) you or someone else was injured? 268 Hooning behaviours
b) To the best of your knowledge, did they report it? c) no one was injured, but the car you were in, or another car, needed to be towed? d) To the best of your knowledge, did they report it? e) no one was injured, but their car, or another car, was damaged, but didn’t need towing? f) To the best of your knowledge, did they report it? Previous (last 3 years) 26. In the last 3 years, how many times have you been booked for doing Number of times hooning offences things like burn outs, donuts, fish tails, drifting, or skids in Queensland? 28. In the last 3 years, how many times have you been booked for street racing and doing time trials in Queensland? Driving history and vehicle type Previous (last 3 years) 36. In the last 3 years, how many times have you been booked for: Number of times offences a) a speeding offence? b) a drink driving offence? c) a drug driving offence? d) a seat belt offence? e) an unlicensed driving offence? f) having vehicle defects / illegal modifications? Current (last month) illegal / 37. In the last month, how often have you: Likert scale risky driving a) exceeded the posted speed limit? 1 (never) – 7 (every time I drive) b) driven when you thought you might be over the legal blood alcohol limit? c) driven under the influence of illegal drugs (e.g., marijuana, ecstasy)? d) driven while not wearing your seat belt? e) driven when you didn’t have a valid driver’s licence? f) driven a car that wasn’t roadworthy / had modifications that weren’t approved? Vehicle/s used 23. Thinking about the car you drive most often: a) What make is it? b) What model is it? c) What year was it manufactured? Hooning behaviours 269
d) Is it registered to you? 1 = No, 2 = Yes, 3 = It’s not registered 24.a) What car do you use to do things like burn outs, donuts, fish tails, 1 = Same as question 23, 2 = Different, drifting, or skids? 3 = N/A, I don’t do burn outs b) What make is it? c) What model is it? d) What year was it manufactured? e) Is it registered to you? 1 = No, 2 = Yes, 3 = It’s not registered 25.a) What car do you use in a street race or time trial? 1 = Same as question 23, 2 = Different, b) What make is it? 3 = N/A, I don’t race c) What model is it? d) What year was it manufactured? e) Is it registered to you? 1 = No, 2 = Yes, 3 = It’s not registered Expanded deterrence theory Punishment experience 26. In the last 3 years, how many times have you been booked for doing Number of times (direct) things like burn outs, donuts, fish tails, drifting, or skids in Queensland? 27. What was the longest period of time your car was impounded by 1 = Wasn’t impounded, 2 = 48 hours, 3 police for this offence type? = 3 months, 4 = Forfeited, 5 = Other 28. In the last 3 years, how many times have you been booked for street Number of times racing and doing time trials in Queensland? 29. What was the longest period of time your car was impounded by 1 = Wasn’t impounded, 2 = 48 hours, 3 police for this offence type? = 3 months, 4 = Forfeited, 5 = Other Punishment experience 30. How many people do you know that have been booked for doing things Number of friends (indirect) like burn outs, donuts, fish tails, drifting, or skids in Queensland in the last 3 years? 31. Did any of these people have their car impounded for this 1 = No, 2 = Yes, 3 = Don’t know offence? 32. What was the longest impoundment period applied? 1 = Not sure, 2 = 48 hrs, 3 = 3 months, 4 33. How many people do you know that have been booked for street racing = Forfeited, 5 = Other or doing time trials in Queensland in the last 3 years? Number of friends 34. Did any of them have their car impounded for this offence? 1 = No, 2 = Yes, 3 = Don’t know 35. What was the longest impoundment period applied? 1 = Not sure, 2 = 48 hrs, 3 = 3 months, 4 = Forfeited, 5 = Other 270 Hooning behaviours
Punishment avoidance 70. Thinking about things like burn outs, donuts, fish tails, drifting, or Likert scale (direct) skids, since police started impounded cars for “hooning” offences, how 1 (never) – 7 (all the time) often have you been able to avoid getting caught by: a) doing it less often? b) only doing it in places where the chances of getting caught are low (e.g., in back streets)? c) using mobile phones or police scanners to be alerted, or alert others, that police are in the area or on their way to your location? d) participating as a passenger in someone else’s car, rather than driving your own? e) only doing this while driving a car that’s not registered in your name? f) other 72. Thinking about street racing, since police started impounded cars for “hooning” offences, how often have you been able to avoid getting caught by: a) doing it less often? b) only doing it in places where the chances of getting caught are low (e.g., in back streets)? c) using mobile phones or police scanners to be alerted, or alert others, that police are in the area or on their way to your location? d) participating as a passenger in someone else’s car, rather than driving your own? e) only doing this while driving a car that’s not registered in your name? f) other Punishment avoidance 71. Thinking about things like burn outs, donuts, fish tails, drifting, or Likert scale (indirect) skids, since police started impounded cars for “hooning” offences, how 1 (never) – 7 (all the time) often have your friends been able to avoid getting caught by: a) doing it less often? b) only doing it in places where the chances of getting caught are low (e.g., in back streets)? c) using mobile phones or police scanners to be alerted, or alert others, that police are in the area or on their way to their location? Hooning behaviours 271
d) participating as a passenger in someone else’s car, rather than driving their own? e) only doing this while driving a car that’s not registered in their name? f) other 73. Thinking about street racing, since police started impounded cars for “hooning” offences, how often have your friends been able to avoid getting caught by: a) doing it less often? b) only doing it in places where the chances of getting caught are low (e.g., in back streets)? c) using mobile phones or police scanners to be alerted, or alert others, that police are in the area or on their way to their location? d) participating as a passenger in someone else’s car, rather than driving their own? e) only doing this while driving a car that’s not registered in their name? f) other Perceptions of likelihood of 40. If you were doing things like burn outs, donuts, fish tails, drifting or Likert scale detection (direct) skids, how likely is it that you would be caught by police if you were: 1 (very unlikely) – 7 (very likely) a) in a built-up suburban area? b) on a main street? c) on a highway? d) on a back street / industrial estate? 46. If you were having a street race, how likely is it that you would be caught by police if you were: a) in a built-up suburban area? b) on a main street? c) on a highway? d) on a back street / industrial estate? 99. The chances of getting caught street racing are over-rated Likert scale 100. The chances of getting caught doing things like burn outs, donuts, fish 1 (strongly disagree) – 7 (strongly agree) tails, drifting, or skids are over-rated 272 Hooning behaviours
Perceptions of likelihood of 54. People who do burn outs, donuts, fish tails, drifting, or skids are likely Likert scale detection (indirect) to be caught by police 1 (strongly disagree) – 7 (strongly agree) 58. People who take part in street races are likely to be caught by police Perceptions of certainty of 41. If you were caught doing things like burn outs, donuts, fish tails, Likert scale punishment (direct) drifting or skids, how likely is it that your car would be impounded? 1 (very unlikely) – 7 (very likely) 47. If you were caught having a street race, how likely is it that your car would be impounded? Perceptions of certainty of 55. If caught doing things like burn outs, [others] are likely to have their car Likert scale punishment (indirect) impounded 1 (strongly disagree) – 7 (strongly agree) 59. If caught racing, [others] are likely to have their car impounded Perceptions of swiftness of 42. If you were caught doing things like burn outs, donuts, fish tails, Likert scale punishment (direct) drifting or skids, how quickly do you think your car would be impounded? 1 (straight away) – 7 (in about a month) 48. If you were caught having a street race, how quickly do you think your * REVERSE SCORED * car would be impounded? Perceptions of swiftness of 57. If caught doing things like burn outs, [others’] car would be impounded Likert scale punishment (indirect) straight away 1 (strongly disagree) – 7 (strongly agree) 61. If caught racing, [others’] car would be impounded straight away Perceptions of severity of 43. If it was your first hooning offence for doing things like burn outs, and Likert scales punishment (direct) your car was impounded for 48 hours: a) how severe do you think that punishment is? 1 (not at all severe) – 7 (very severe) b) what difference would it make to your daily life? 1 (none at all) – 7 (major problem) 44. If it was your second hooning offence for doing things like burn outs, and your car was impounded for 3 months: a) how severe do you think that punishment is? 1 (not at all severe) – 7 (very severe) b) what difference would it make to your daily life? 1 (none at all) – 7 (major problem) 45. If it was your third hooning offence for doing things like burn outs, and your car was forfeited and you lost it permanently: a) how severe do you think that punishment is? 1 (not at all severe) – 7 (very severe) b) what difference would it make to your daily life? 1 (none at all) – 7 (major problem) 49. If it was your first hooning offence for having a street race, and your car was impounded for 48 hours: a) how severe do you think that punishment is? 1 (not at all severe) – 7 (very severe) Hooning behaviours 273
b) what difference would it make to your daily life? 1 (none at all) – 7 (major problem) 50. If it was your second hooning offence for having a street race, and your car was impounded for 3 months: a) how severe do you think that punishment is? 1 (not at all severe) – 7 (very severe) b) what difference would it make to your daily life? 1 (none at all) – 7 (major problem) 51. If it was your third hooning offence for having a street race, and your car was forfeited and you lost it permanently: a) how severe do you think that punishment is? 1 (not at all severe) – 7 (very severe) b) what difference would it make to your daily life? 1 (none at all) – 7 (major problem) Perceptions of severity of 56. If caught doing things like burn outs, [others’] punishment (i.e., having Likert scale punishment (indirect) their car impounded) would be severe 1 (strongly disagree) – 7 (strongly agree) 60. If caught racing, [others’] punishment (i.e., having their car impounded) would be severe Intentions regarding fleeing 43c. If it was your first hooning offence for doing things like burn outs, Likert scale from police to avoid how likely is it that you would flee from police to avoid losing your car for 1 (very unlikely) – 7 (very likely) punishment 48 hours? 44c. If it was your second hooning offence for doing things like burn outs, how likely is it that you would flee from police to avoid losing your car for 3 months? 45c. If it was your third hooning offence for doing things like burn outs, how likely is it that you would flee from police to avoid losing your car permanently? 49c. If it was your first hooning offence for having a street race, how likely is it that you would flee from police to avoid losing your car for 48 hours? 50c. If it was your second hooning offence for having a street race, how likely is it that you would flee from police to avoid losing your car for 3 months? 51c. If it was your third hooning offence for having a street race, how likely is it that you would flee from police to avoid losing your car permanently? Crushing vs. Forfeiture 52. Some US states crush cars as a penalty for street racing. Imagine that Likert scales rather than losing your car permanently for a 3rd hooning offence in Queensland, your car could be crushed: 274 Hooning behaviours
a) how severe do you think that punishment is? 1 (not at all severe) – 7 (very severe) b) how does that compare to the impact of permanently forfeiting your car? 1 (forfeiture is far worse) – 7 (crushing c) how likely is it that you would flee from police to avoid having your car is far worse) crushed? 1 (very unlikely) – 7 (very likely) Minimum length of 53. How long would the first impoundment period have to be to keep you Number of days impoundment period to from: prevent hooning behaviour a) taking part in a street race? b) doing things like burn outs, donuts, fish tails, drifting, or skids? Social learning theory Differential association 14. How many of your friends, while driving: Likert scale (behavioural) a) do things like burn outs, donuts, fish tails, drifting, or skids? 1 (none of them) – 7 (all of them) b) take part in street races? c) be part of a rolling road block? 15. How often do your friends: Likert scale a) do things like burn outs, donuts, fish tails, drifting, or skids? 1 (never) – 7 (every time they drive) b) take part in street races? c) be part of a rolling road block? Differential association 80. My friends think: Likert scale (normative) a) street racing is okay 1 (strongly disagree) – 7 (strongly agree) b) doing things like burn outs, donuts, fish tails, drifting, or skids is okay 81. My family think: a) street racing is okay b) doing things like burn outs, donuts, fish tails, drifting, or skids is okay 82. Other people generally think: a) street racing is okay b) doing things like burn outs, donuts, fish tails, drifting, or skids is okay Imitation 16. Part of the reason I started doing things like burn outs, donuts, fish tails, Likert scale drifting, or skids was because: 1 (strongly disagree) – 7 (strongly agree) a) my friends were doing it b) I’d been a passenger while someone else did it d) I wanted to do things I’d seen in person e) I wanted to do things I’d seen on TV, on the internet or in movies Hooning behaviours 275
17. Part of the reason I started street racing (including time trials) was because: a) my friends were doing it b) I’d been a passenger while someone else did it d) I wanted to do things I’d seen in person e) I wanted to do things I’d seen on TV, on the internet or in movies Differential reinforcement 83. My friends think it’s cool to: Likert scale (social rewards) a) have street races 1 (strongly disagree) – 7 (strongly agree) b) do things like burn outs, donuts, fish tails, drifting, or skids 84. My family think it’s cool to: a) have street races b) do things like burn outs, donuts, fish tails, drifting, or skids 87. My friends would respect me for: a) having a street race b) doing things like burn outs, donuts, fish tails, drifting, or skids 88. My family would respect me for: a) having a street race b) doing things like burn outs, donuts, fish tails, drifting, or skids 91. My friends would cheer me on for: a) having a street race b) doing things like burn outs, donuts, fish tails, drifting, or skids 92. My family would cheer me on for: a) having a street race b) doing things like burn outs, donuts, fish tails, drifting, or skids Differential reinforcement 85. My friends would criticise me for: Likert scale (social punishments) a) having a street race 1 (strongly disagree) – 7 (strongly agree) b) doing things like burn outs, donuts, fish tails, drifting, or skids 86. My family would criticise me for: a) having a street race b) doing things like burn outs, donuts, fish tails, drifting, or skids 89. My friends think it’s stupid to: a) have street races 276 Hooning behaviours
b) do things like burn outs, donuts, fish tails, drifting, or skids 90. My family think it’s stupid to: a) have street races b) do things like burn outs, donuts, fish tails, drifting, or skids 123. I would be embarrassed to tell my friends: a) if I was booked for a hooning offence and lost my car for 48 hours b) if I was booked for a second hooning offence and lost my car for 3 months c) if I was booked for a third hooning offence and lost my car permanently 124. I would be embarrassed to tell my family: a) if I was booked for a hooning offence and lost my car for 48 hours b) if I was booked for a second hooning offence and lost my car for 3 months c) if I was booked for a third hooning offence and lost my car permanently Differential reinforcement 74. Most of your friends don’t care if you take part in street racing: Likert scale (social absence of a) as long as you don’t get caught 1 (strongly disagree) – 7 (strongly agree) punishment) b) as long as no one gets hurt 75. Your family don’t care if you take part in street racing: a) as long as you don’t get caught b) as long as no one gets hurt 76. Other people generally don’t care if you take part in street racing: a) as long as you don’t get caught b) as long as no one gets hurt 77. Most of your friends don’t care if you do things like burn outs, donuts, fish tails, drifting or skids: a) as long as you don’t get caught b) as long as no one gets hurt 78. Your family don’t care if you do things like burn outs, donuts, fish tails, drifting or skids: a) as long as you don’t get caught b) as long as no one gets hurt
Hooning behaviours 277
79. Other people generally don’t care if you do things like burn outs, donuts, fish tails, drifting or skids: a) as long as you don’t get caught b) as long as no one gets hurt Differential reinforcement 121. Street racing: Likert scale (non-social rewards) a) gives me a thrill 1 (strongly disagree) – 7 (strongly agree) b) makes me feel like a good driver c) makes me feel powerful d) makes me feel in control of things 122. Doing things like burn outs, donuts, fish tails, drifting, or skids: a) gives me a thrill b) makes me feel like a good driver c) makes me feel powerful d) makes me feel in control of things Differential reinforcement 125. Street racing: Likert scale (non-social punishments) a) makes me feel bad 1 (strongly disagree) – 7 (strongly agree) b) makes me feel guilty c) frightens me d) makes me feel anxious f) could lead to serious injury 126. Doing things like burn outs, donuts, fish tails, drifting, or skids: a) makes me feel bad b) makes me feel guilty c) frightens me d) makes me feel anxious f) could lead to serious injury Differential reinforcement 125. Street racing: Likert scale (instrumental punishments) e) could damage my car 1 (strongly disagree) – 7 (strongly agree) g) could mean I’d lose my job 126. Doing things like burn outs, donuts, fish tails, drifting, or skids: e) could damage my car g) could mean I’d lose my job 278 Hooning behaviours
Differential reinforcement 127. Overall, more good things are likely to happen than bad while: Likert scale (overall balance) a) street racing 1 (strongly disagree) – 7 (strongly agree) b) doing things like burn outs, donuts, fish tails, drifting, or skids * 128 & 129 REVERSE SCORED * 128. Street racing isn’t worth the risks 129. Doing things like burn outs, donuts, fish tails, drifting, or skids isn’t worth the risks Definitions (specific context) 115. Street racing is not acceptable, even if it is done away from the general Likert scale public (i.e., not on main roads or in suburban streets) 1 (strongly disagree) – 7 (strongly agree) 116. Doing things like burn outs, donuts, fish tails, drifting or skids is not * 115 & 116 REVERSE SCORED * acceptable, even if it is done away from the general public (i.e., not on main roads or in suburban streets) 117. Doing things like burn outs, donuts, fish tails, drifting or skids is okay if it is done in a quiet area (e.g., industrial estate) and spectators are a safe distance from the cars 118. Street racing is okay if it is done in a quiet area (e.g., industrial estate) and spectators are a safe distance from the cars Definitions (specific 38. Compared to doing things like burn outs, donuts, fish tails, drifting, or Likert scale comparative) skids: 1 (less dangerous) – 7 (more dangerous) a) driving while over the legal alcohol limit is? b) driving while under the influence of illegal drugs (e.g., marijuana or ecstasy) is? c) exceeding the speed limit by more than 20km/hr is? d) driving without a valid licence is? e) driving a car that wouldn’t pass a roadworthy test is? 39. Compared to street racing: a) driving while over the legal alcohol limit is? b) driving while under the influence of illegal drugs (e.g., marijuana or ecstasy) is? c) exceeding the speed limit by more than 20km/hr is? d) driving without a valid licence is? e) driving a car that wouldn’t pass a roadworthy test is? Hooning behaviours 279
Definitions (favourable) 103. People who race other cars are generally better drivers Likert scale 104. People who do burn outs, donuts, fish tails, drifting or skids are 1 (strongly disagree) – 7 (strongly agree) generally better drivers 105. People who race other cars are generally more careful on the road 106. People who do things like burn outs, donuts, fish tails, drifting or skids are generally more careful on the road 113. The police spend too much time hassling people who race other cars 114. The police spend too much time hassling people who do things like burn outs, donuts, fish tails, drifting or skids Definitions (neutral) 93. I think it’s okay to race other cars, as long as you don’t get caught Likert scale 94. I think it’s okay to do things like burn outs, donuts, fish tails, drifting or 1 (strongly disagree) – 7 (strongly agree) skids, as long as you don’t get caught 97. Everybody has a street race once in a while 98. Everybody does burn outs, donuts, fish tails, drifting or skids once in a while 107. It’s okay to race other cars, as long as you don’t do it too much 108. It’s okay to do things like burn outs, donuts, fish tails, drifting or skids, as long as you don’t do it too much 109. It’s okay to race other cars, as long as no one gets hurt 110. It’s okay to do things like burn outs, donuts, fish tails, drifting or skids, as long as no one gets hurt Definitions (negative) 95. We need harsher penalties for street racing Likert scale 96. We need harsher penalties for burn outs, donuts, fish tails, drifting or 1 (strongly disagree) – 7 (strongly agree) skids 101. There is no excuse for street racing 102. There is no excuse for doing things like burn outs, donuts, fish tails, drifting or skids 111. Street racing is wrong 112. Doing things like burn outs, donuts, fish tails, drifting or skids is wrong 119. Doing things like burn outs, donuts, fish tails, drifting or skids is risky 120. Street racing is risky 280 Hooning behaviours
Driver thrill-seeking (Stradling et 62. I would enjoy driving a sports car on a road with no speed limit Likert scale al., 2004) 63. I enjoy the sensation of accelerating rapidly 1 (strongly disagree) – 11 (strongly 64. I enjoy listening to loud, exciting music while driving agree) 65. I get a real thrill out of driving fast 66. I enjoy cornering at high speed 67. I would like to risk my life as a racing driver 68. I like to raise my adrenaline levels while driving 69. I sometimes like to frighten myself a little while driving
Hooning behaviours 281
APPENDIX C.2
STUDY 1B ONLINE SURVEY
Your views on Queensland’s vehicle impoundment legislation
Thank you for taking part in this research!
This survey asks about your opinion of Queensland’s vehicle impoundment legislation that is applied to “hooning” offences such as driving your car in a public place in a way that makes noise or smoke (e.g., burn outs, donuts, fish tails, drifting, or skids); participating in a street race; or having time trials to test the ability of a driver and / or their car. There are no right or wrong answers, and your survey is confidential. Please read each question carefully and feel free to be honest about your opinions.
1. Do you drive in Queensland? No Yes
If they answer yes, continue to next question. If they answer no, display following message:
Unfortunately you do not meet the selection criteria for this research and do not need to complete the rest of the survey. Thank you for your interest. Then close the survey.
These questions are about 2 types of hooning behaviours. The first is doing things like burn outs, donuts, fish tails, drifting, or skids; and the second is participating in a street race, including having a time trial to test your driving ability, or the capability of your car:
2. IN THE LAST MONTH, while driving, how many times have you …
… done things like burn outs, donuts, fish tails, _____ times (please type drifting, or skids? a number) _____ times (please type … taken part in a street race (including time trials)? a number) … been part of a rolling road block, keeping back _____ times (please type traffic while other cars raced? a number)
… raced while others kept traffic back with a rolling _____ times (please type road block? a number)
If at least one of the four answers to Q2 is greater than 0, continue to Q3. If they are all 0, display the above error message and close the survey.
282 Hooning behaviours
The following questions are about your personal characteristics and your driving experience. This information will be used to describe the sample of people who completed the survey.
3. What is your gender? Male Female 4. What is your age? _____ years
Primary School Secondary School 5. What is the highest level of TAFE / Tech. College education you have completed? Trade Apprenticeship University (undergrad) University (postgrad) No Yes, Secondary School Yes, TAFE / Tech. College 6. Are you currently studying? Yes, Trade Apprenticeship Yes, University (undergrad) Yes, University (postgrad) Not working Studying 7. What is your current employment status? Employed – casual Employed – part-time (Tick all that apply) Employed – full-time Self-employed 8. If you are working, what is your usual job?
If you have more than one job, answer for your main job where you work the most hours.
If you are not working, type “N/A” 9. Do you need to drive for your job? No Yes Learner P1 P2 10. What type of driver’s licence do you currently hold? Provisional Open Restricted Unlicensed Hooning behaviours 283
11. How many years has it been since you first obtained a Provisional _____ years (please type a number) licence? 12. On average, how many hours per _____ hours / week (please type a week do you spend driving? number)
These questions are about 2 types of hooning behaviours. The first is doing things like burn outs, donuts, fish tails, drifting, or skids; and the second is participating in a street race, including having a time trial to test your driving ability, or the capability of your car:
13. IN THE NEXT MONTH, how Very Even Very likely is it that while Unlikel Chan Likel driving, you will … y ce y … do things like burn outs, donuts, fish tails, drifting, or 1 2 3 4 5 6 7 skids? … take part in a street race? 1 2 3 4 5 6 7 … be part of a rolling road block, keeping back traffic while other 1 2 3 4 5 6 7 cars race? … race while others keep traffic 1 2 3 4 5 6 7 back with a rolling road block?
These questions are about your friends’ driving behaviour:
None Half 14. How many of your FRIENDS, All of of of them while driving them them … do things like burn outs, donuts, fish tails, drifting, or 1 2 3 4 5 6 7 skids? … take part in street races? 1 2 3 4 5 6 7 … have been part of a rolling 1 2 3 4 5 6 7 road block? Every 15. How often do these Neve Sometimes time they r friends… drive … do things like burn outs, donuts, fish tails, drifting, or 1 2 3 4 5 6 7 skids? … take part in street races? 1 2 3 4 5 6 7
… be part of a rolling road block? 1 2 3 4 5 6 7
284 Hooning behaviours
These questions ask about the REASONS WHY you do certain things while driving:
16. Part of the reason I started Stron Stron doing things like burn outs, gly Neutr gly Disagr al donuts, fish tails, drifting, or Agree skids was because … ee … my friends were doing it 1 2 3 4 5 6 7
… I’d been a passenger while 1 2 3 4 5 6 7 someone else did it
… I wanted to see if I could do it 1 2 3 4 5 6 7 … I wanted to do things I’d seen in 1 2 3 4 5 6 7 person … I wanted to do things I’d seen on 1 2 3 4 5 6 7 TV, on the internet or in movies Stron 17. Part of the reason I started Stron gly Neutr gly street racing (including time Disagr al Agree trials) was because … ee … my friends were doing it 1 2 3 4 5 6 7
… I’d been a passenger while 1 2 3 4 5 6 7 someone else did it
… I wanted to see if I could do it 1 2 3 4 5 6 7 … I wanted to do things I’d seen in 1 2 3 4 5 6 7 person … I wanted to do things I’d seen on 1 2 3 4 5 6 7 TV, on the internet or in movies
Click here to submit responses and move to next page
The following questions are about on-road incidents or crashes when YOU WERE DRIVING, in the LAST 3 YEARS, whether you were at fault or not:
18. As a DRIVER, how many times in the last 3 years have you been in an incident where … … you, or someone else, was injured? _____ times (please type a number) Did you report it (if you had more than one, please answer for the most recent No Yes N/A crash)? … no one was injured, but your car, or _____ times (please type a number) another car, needed to be towed? Did you report it (if you had more than one, please answer for the most recent No Yes N/A crash)? … no one was injured, but your car, or another car, was damaged, but didn’t _____ (please type a number) need towing? Hooning behaviours 285
Did you report it (if you had more than one, please answer for the most recent No Yes N/A crash)? 19. While you were driving, how many times in the last 3 years has doing things like burn outs, donuts, fish tails, drifting, or skids led to an incident where …
… you, or someone else, was injured? _____ times (please type a number) Did you report it (if you had more than one, please answer for the most recent No Yes N/A crash)? … no one was injured, but your car, or _____ times (please type a number) another car, needed to be towed? Did you report it (if you had more than one, please answer for the most recent No Yes N/A crash)? … no one was injured, but your car, or another car, was damaged, but didn’t _____ times (please type a number) need towing? Did you report it (if you had more than one, please answer for the most recent No Yes N/A crash)? 20. While you were driving, how many times in the last 3 years has taking part in a street race (including time trials) led to an incident where …
… you, or someone else, was injured? _____ times (please type a number) Did you report it (if you had more than one, please answer for the most recent No Yes N/A crash)? … no one was injured, but your car, or _____ times (please type a number) another car, needed to be towed? Did you report it (if you had more than one, please answer for the most recent No Yes N/A crash)? … no one was injured, but your car, or another car, was damaged, but didn’t _____ times (please type a number) need towing? Did you report it (if you had more than one, please answer for the most recent No Yes N/A crash)?
Again thinking about the LAST 3 YEARS, but this time when you were a PASSENGER, whether the driver was at fault or not:
21. While you were a PASSENGER, how many times in the last 3 years has doing things like burn outs, donuts, fish tails, drifting, or skids led to an incident where … … you, or someone else, was _____ times (please type a number) injured? To the best of your knowledge, did they report it? No Yes N/A
286 Hooning behaviours
… no one was injured, but the car you were in, or another car, _____ times (please type a number) needed to be towed? To the best of your knowledge, did they report it? No Yes N/A … no one was injured, but their car, or another car, was _____ times (please type a number) damaged, but didn’t need towing? To the best of your knowledge, did they report it? No Yes N/A 22. While you were a PASSENGER, how many times in the last 3 years has taking part in a street race (including time trials) led to an incident where … … you, or someone else, was _____ times (please type a number) injured? To the best of your knowledge, did they report it? No Yes N/A … no one was injured, but the car you were in, or another car, _____ times (please type a number) needed to be towed? To the best of your knowledge, did they report it? No Yes N/A … no one was injured, but their car, or another car, was _____ times (please type a number) damaged, but didn’t need towing? To the best of your knowledge, did they report it? No Yes N/A
The following questions are about the car/s you drive:
23. Thinking about the car you drive MOST OFTEN:
What make is it? (e.g., Holden, Ford) Make = ______What model is it? (e.g., Commodore, Model = ______Falcon) What year was it manufactured? _____ Yes It’s not registered Is it registered to you? No 24. What car do you use to do things like burn outs, donuts, fish tails, drifting, or skids? Same as the car in Q23 Different to the car in N/A – I don’t do burn outs Q23 What make is it? (e.g., Holden, Ford) Make = ______What model is it? (e.g., Commodore, Model = ______Falcon) What year was it manufactured? _____ Hooning behaviours 287
Yes It’s not registered Is it registered to you? No 25. What car do you use in a street race or time trial? Same as the car in Q23 Different to the car in N/A – I don’t race Q23 What make is it? (e.g., Holden, Ford) Make = ______What model is it? (e.g., Commodore, Model = ______Falcon) What year was it manufactured? _____ Yes It’s not registered Is it registered to you? No
If answer to Q24a is Same as the car in Q23 or N/A – skip to Q25 If answer to Q25a is Same as the car in Q23 or N/A – skip to Q26
Click here to submit responses and move to next page
These questions are about “hooning” offences in Queensland:
26. In the last 3 years, how many times have YOU been booked for doing things like burn outs, 0 1 2 3 >3 donuts, fish tails, drifting, or skids in Queensland? 27. What was the longest period of Wasn’t 3 48 Forfeit impound month Other time your car was impounded by hours ed police for this offence type? ed s 28. In the last 3 years, how many times have you been booked for 0 1 2 3 >3 street racing or doing time trials in Queensland? 29. What was the longest period of Wasn’t 3 48 Forfeit impound month Other time your car was impounded by hours ed police for this offence type? ed s
If answer to Q26 is 0 – skip to Q28 If answer to Q28 is 0 – skip to Q30
30. How many people do you know that have been booked for doing things like burn outs, donuts, fish tails, 0 1 2 3 >3 drifting, or skids in Queensland in the last 3 years? 31. Did any of these people have Don’t know their car impounded for this No Yes offence?
288 Hooning behaviours
32. What was the longest Not 48 3 months Forfeited Other impoundment period applied? sure hours
If answer to Q30 is 0 – skip to Q33 If answer to Q31 is No or Don’t know – skip to Q33
33. How many people do you know that have been booked for street racing or doing 0 1 2 3 >3 time trials in Queensland in the last 3 years? 34. Did any of these people have Don’t know their car impounded for this No Yes offence?
35. What was the longest Not 48 3 months Forfeited Other impoundment period applied? sure hours
If answer to Q33 is 0 – skip to Q36 If answer to Q34 is No or Don’t know – skip to Q36
The following questions are about traffic offences other than “hooning”:
36. In the last 3 years, how many times have you been booked for …
… a speeding offence? _____ times
… a drink driving offence? _____ times
… a drug driving offence? _____ times
… a seat belt offence? _____ times
… an unlicensed driving offence? _____ times
… having vehicle defects / illegal modifications? _____ times
Only allow numerals for “times” responses
37. In the last month, how often Every Never Sometimes time I have you … drive … exceeded the posted speed limit? 1 2 3 4 5 6 7 … driven when you thought you might be over the legal blood alcohol 1 2 3 4 5 6 7 limit? … driven under the influence of illegal drugs (e.g., marijuana, 1 2 3 4 5 6 7 ecstasy)? … driven while not wearing your seat 1 2 3 4 5 6 7 belt? Hooning behaviours 289
… driven when you didn’t have a 1 2 3 4 5 6 7 valid driver’s licence? … driven a car that wasn’t roadworthy / had modifications that 1 2 3 4 5 6 7 weren’t approved?
The following questions ask you to compare how dangerous a number of traffic offences are compared to “hooning” behaviours:
38. Compared to doing things like burn outs, Less Equally More
donuts, fish tails, Dangerous Dangerous Dangerous drifting or skids … … driving while over the legal 1 2 3 4 5 6 7 alcohol limit is: … driving while under the influence of illegal drugs 1 2 3 4 5 6 7 (e.g., marijuana or ecstasy) is: … exceeding the speed limit 1 2 3 4 5 6 7 by more than 20km/hr is: … driving without a valid 1 2 3 4 5 6 7 licence is: … driving a car that wouldn’t 1 2 3 4 5 6 7 pass a roadworthy test is:
39. Compared to street Less Equally More
racing… Dangerous Dangerous Dangerous … driving while over the legal 1 2 3 4 5 6 7 alcohol limit is: … driving while under the influence of illegal drugs 1 2 3 4 5 6 7 (e.g., marijuana or ecstasy) is: … exceeding the speed limit 1 2 3 4 5 6 7 by more than 20km/hr is: … driving without a valid 1 2 3 4 5 6 7 licence is: … driving a car that wouldn’t 1 2 3 4 5 6 7 pass a roadworthy test is:
Click here to submit responses and move to next page
The following questions ask about your opinion of Queensland’s “anti-hooning” legislation, as it applies to YOU. It doesn’t matter whether or not you have had your car impounded, we are still interested in your opinions.
290 Hooning behaviours
Firstly, if you were doing things like BURN OUTS, DONUTS, FISH TAILS, DRIFTING OR SKIDS:
40. How likely is it that you Very Even Very would be caught by police Unlikely Chance Likely if you were… … in a built-up suburban area? 1 2 3 4 5 6 7
… on a main street? 1 2 3 4 5 6 7
… on a highway? 1 2 3 4 5 6 7 … on a back street / industrial 1 2 3 4 5 6 7 estate? 41. If you were caught, how likely is it that your car 1 2 3 4 5 6 7 would be impounded?
In 42. How quickly do you think your Straight In about about 2 3 5 6 car would be impounded? away 2 weeks a month
43. If it was your FIRST hooning offence, and your car was impounded for 48 hours, … Not at … how severe do you think that Very all 2 3 Neutral 5 6 severe punishment is? severe … what difference would it make None at Major 2 3 4 5 6 to your daily life? all problem … how likely is it that you would Very Even Very flee from police to avoid losing 2 3 5 6 Unlikely Chance Likely your car for 48 hours? 44. What if it was your SECOND offence, and your car was impounded for 3 months … Not at … how severe do you think that Very all 2 3 Neutral 5 6 severe punishment is? severe … what difference would it make None at Major 2 3 4 5 6 to your daily life? all problem … how likely is it that you would Very Even Very flee from police to avoid losing 2 3 5 6 Unlikely Chance Likely your car for 3 months? 45. Or your THIRD offence, and your car was forfeited and you lost it permanently … Not at … how severe do you think that Very all 2 3 Neutral 5 6 severe punishment is? severe … what difference would it make None at Major 2 3 4 5 6 to your daily life? all problem … how likely is it that you would Very Even Very flee from police to avoid losing 2 3 5 6 Unlikely Chance Likely your car permanently?
Hooning behaviours 291
What if you were having a STREET RACE with another car or cars?
46. How likely is it that you Very Even Very would be caught by police Unlikely Chance Likely if you were… … in a built-up suburban area? 1 2 3 4 5 6 7
… on a main street? 1 2 3 4 5 6 7
… on a highway? 1 2 3 4 5 6 7 … on a back street / industrial 1 2 3 4 5 6 7 estate? 47. If you were caught, how likely is it that your car 1 2 3 4 5 6 7 would be impounded?
48. How quickly do you think In Straight In about about your car would be 2 3 5 6 away 2 weeks a impounded? month
49. If it was your FIRST hooning offence, and your car was impounded for 48 hours, … Not at … how severe do you think that Very all 2 3 Neutral 5 6 severe punishment is? severe … what difference would it make None at Major 2 3 4 5 6 to your daily life? all problem … how likely is it that you would Very Even Very flee from police to avoid losing 2 3 5 6 Unlikely Chance Likely your car for 48 hours? 50. What if it was your SECOND offence, and your car was impounded for 3 months … Not at … how severe do you think that Very all 2 3 Neutral 5 6 severe punishment is? severe … what difference would it make None at Major 2 3 4 5 6 to your daily life? all problem … how likely is it that you would Very Even Very flee from police to avoid losing 2 3 5 6 Unlikely Chance Likely your car for 3 months? 51. Or your THIRD offence, and your car was forfeited and you lost it permanently … Not at … how severe do you think that Very all 2 3 Neutral 5 6 severe punishment is? severe … what difference would it make None at Major 2 3 4 5 6 to your daily life? all problem … how likely is it that you would Very Even Very flee from police to avoid losing 2 3 5 6 Unlikely Chance Likely your car permanently?
292 Hooning behaviours
52. Some US states crush cars as a penalty for street racing. Imagine that rather than losing your car permanently for a 3rd hooning offence in Queensland, your car could be crushed … … how severe do you think Not at all Very 2 3 Neutral 5 6 that punishment is? severe severe … how does that compare to Forfeiture Much Crushing the impact of permanently is far 2 3 the 5 6 is far forfeiting your car? worse same worse … how likely is it that you Very Even Very would flee from police to avoid 2 3 5 6 Unlikely Chance Likely having your car crushed? 53. How long would the first impoundment period have to be to keep you from … ______(please type number of … taking part in a street race? days) … doing things like burn outs, donuts, ______(please type number of fish tails, drifting, or skids? days)
Click here to submit responses and move to next page
The following questions ask about your opinion of Queensland’s “anti- hooning” legislation, as it applies to OTHERS. Please indicate your agreement with the following statements:
Strongly Strongly Neutral Disagree Agree 54. People who do burn outs, donuts, fish tails, 1 2 3 4 5 6 7 drifting, or skids are likely to be caught by police 55. If caught doing these sorts of things, they are likely to 1 2 3 4 5 6 7 have their car impounded 56. Their punishment (i.e., having their car 1 2 3 4 5 6 7 impounded) would be severe 57. Their car would be 1 2 3 4 5 6 7 impounded straight away 58. People who take part in street races are likely to 1 2 3 4 5 6 7 be caught by police 59. If caught racing, they are likely to have their car 1 2 3 4 5 6 7 impounded 60. Their punishment (i.e., having their car 1 2 3 4 5 6 7 impounded) would be severe 61. Their car would be 1 2 3 4 5 6 7 impounded straight away Hooning behaviours 293
To answer these questions, think about how you typically feel while out driving …
Strongly Strongly Neutral Disagree Agree 62. I would enjoy driving a sports car on a road with no 1 2 3 4 5 6 7 8 9 10 11 speed limit 63. I enjoy the sensation of 1 2 3 4 5 6 7 8 9 10 11 accelerating rapidly 64. I enjoy listening to loud, 1 2 3 4 5 6 7 8 9 10 11 exciting music while driving 65. I get a real thrill out of 1 2 3 4 5 6 7 8 9 10 11 driving fast 66. I enjoy cornering at high 1 2 3 4 5 6 7 8 9 10 11 speed 67. I would like to risk my life as 1 2 3 4 5 6 7 8 9 10 11 a racing driver 68. I like to raise my adrenaline 1 2 3 4 5 6 7 8 9 10 11 levels while driving
69. I sometimes like to frighten 1 2 3 4 5 6 7 8 9 10 11 myself a little while driving
The following questions ask about times when you or your friends have been out doing something considered “hooning” in Queensland, but have managed to avoid being caught and / or having your car impounded by police.
Firstly, thinking about things like burn outs, donuts, fish tails, drifting, or skids …
70. Since police started impounding cars for All “hooning” offences, how often have YOU Never Sometimes the been able to avoid getting caught by … time
… doing it less often? 1 2 3 4 5 6 7
… only doing it in places where the chances of 1 2 3 4 5 6 7 getting caught are low (e.g., in back streets)?
… using mobile phones or police scanners to be alerted, or alert others, that police are in 1 2 3 4 5 6 7 the area or on their way to your location?
… participating as a passenger in someone 1 2 3 4 5 6 7 else’s car only, rather than driving your own?
… only doing this while driving a car that’s 1 2 3 4 5 6 7 not registered in your name?
Other:
______
294 Hooning behaviours
71. How often have YOUR FRIENDS been All Never Sometimes the able to avoid getting caught by … time … doing it less often? 1 2 3 4 5 6 7
… only doing it in places where the chances of 1 2 3 4 5 6 7 getting caught are low (e.g., in back streets)?
… using mobile phones or police scanners to be alerted, or alert others, that police are in 1 2 3 4 5 6 7 the area or on their way to their location?
… participating as a passenger in someone 1 2 3 4 5 6 7 else’s car only, rather than driving their own?
… only doing this while driving a car that’s 1 2 3 4 5 6 7 not registered in their name?
Other:
______
Now thinking about street racing …
72. Since police started impounding cars for All “hooning” offences, how often have YOU Never Sometimes the been able to avoid getting caught by … time
… doing it less often? 1 2 3 4 5 6 7
… only doing it in places where the chances of 1 2 3 4 5 6 7 getting caught are low (e.g., in back streets)?
… using mobile phones or police scanners to be alerted, or alert others, that police are in 1 2 3 4 5 6 7 the area or on their way to your location?
… participating as a passenger in someone 1 2 3 4 5 6 7 else’s car only, rather than driving your own?
… only doing this while driving a car that’s 1 2 3 4 5 6 7 not registered in your name?
Other:
______
73. How often have YOUR FRIENDS been All Never Sometimes the able to avoid getting caught by … time … doing it less often? 1 2 3 4 5 6 7
… only doing it in places where the chances of 1 2 3 4 5 6 7 getting caught are low (e.g., in back streets)? Hooning behaviours 295
… using mobile phones or police scanners to be alerted, or alert others, that police are in 1 2 3 4 5 6 7 the area or on their way to their location?
… participating as a passenger in someone 1 2 3 4 5 6 7 else’s car only, rather than driving their own?
… only doing this while driving a car that’s 1 2 3 4 5 6 7 not registered in their name?
Other:
______
Click here to submit responses and move to next page
These questions ask what you think your friends, family, and the general community think about hooning:
Strongly Strongly Neutral Disagree Agree 74. Most of your friends don’t care if you take part in street racing … … as long as you don’t get 1 2 3 4 5 6 7 caught … as long as no one gets hurt 1 2 3 4 5 6 7
75. Your family don’t care if you take part in street racing … … as long as you don’t get 1 2 3 4 5 6 7 caught … as long as no one gets hurt 1 2 3 4 5 6 7
76. Other people generally don’t care if you take part in street racing … … as long as you don’t get 1 2 3 4 5 6 7 caught … as long as no one gets hurt 1 2 3 4 5 6 7
Strongly Strongly Neutral Disagree Agree 77. Most of your friends don’t care if you do things like burn outs, donuts, fish tails, drifting or skids … … as long as you don’t get 1 2 3 4 5 6 7 caught … as long as no one gets hurt 1 2 3 4 5 6 7 78. Your family don’t care if you do things like burn outs, donuts, fish tails, drifting or skids … … as long as you don’t get 1 2 3 4 5 6 7 caught … as long as no one gets hurt 1 2 3 4 5 6 7
296 Hooning behaviours
79. Other people generally don’t care if you do things like burn outs, donuts, fish tails, drifting or skids … … as long as you don’t get 1 2 3 4 5 6 7 caught … as long as no one gets hurt 1 2 3 4 5 6 7
Strongly Strongly Neutral Disagree Agree 80. My friends think …
… street racing is okay 1 2 3 4 5 6 7 … doing things like burn outs, donuts, fish tails, drifting or 1 2 3 4 5 6 7 skids is okay 81. My family think …
… street racing is okay 1 2 3 4 5 6 7 … doing things like burn outs, donuts, fish tails, drifting or 1 2 3 4 5 6 7 skids is okay 82. Other people generally think …
… street racing is okay 1 2 3 4 5 6 7 … doing things like burn outs, donuts, fish tails, drifting or 1 2 3 4 5 6 7 skids is okay
Strongly Strongly Neutral Disagree Agree 83. My friends think it’s cool
to…
… have street races 1 2 3 4 5 6 7 … doing things like burn outs, donuts, fish tails, drifting or 1 2 3 4 5 6 7 skids 84. My family think it’s cool
to… … have street races 1 2 3 4 5 6 7 … doing things like burn outs, 1 2 3 4 5 6 7 etc 85. My friends would criticise
me for… … having a street race 1 2 3 4 5 6 7 … doing things like burn outs, 1 2 3 4 5 6 7 etc Hooning behaviours 297
86. My family would criticise
me for…
… having a street race 1 2 3 4 5 6 7 … doing things like burn outs, 1 2 3 4 5 6 7 etc
Strongly Strongly Neutral Disagree Agree 87. My friends would respect
me for… … having a street race 1 2 3 4 5 6 7 … doing things like burn outs, 1 2 3 4 5 6 7 etc 88. My family would respect
me for… … having a street race 1 2 3 4 5 6 7 … doing things like burn outs, 1 2 3 4 5 6 7 etc 89. My friends think it’s stupid
to…
… have street races 1 2 3 4 5 6 7 … doing things like burn outs, 1 2 3 4 5 6 7 etc 90. My family think it’s stupid
to…
… have street races 1 2 3 4 5 6 7 … doing things like burn outs, 1 2 3 4 5 6 7 etc 91. My friends would cheer
me on for…
… having a street race 1 2 3 4 5 6 7 … doing things like burn outs, 1 2 3 4 5 6 7 etc 92. My family would cheer me
on for… … having a street race 1 2 3 4 5 6 7 … doing things like burn outs, 1 2 3 4 5 6 7 etc
Click here to submit responses and move to next page
298 Hooning behaviours
The following questions relate to what YOU think about “hooning”:
Strongly Strongly Neutral Disagree Agree 93. I think it’s okay to race other cars, as long as you 1 2 3 4 5 6 7 don’t get caught 94. I think it’s okay to do things like burn outs, donuts, fish tails, drifting or 1 2 3 4 5 6 7 skids, as long as you don’t get caught 95. We need harsher penalties 1 2 3 4 5 6 7 for street racing
96. We need harsher penalties for burn outs, donuts, 1 2 3 4 5 6 7 fish tails, drifting or skids
97. Everybody has a street 1 2 3 4 5 6 7 race once in a while 98. Everybody does burn outs, donuts, fish tails, drifting 1 2 3 4 5 6 7 or skids once in a while 99. The chances of getting caught street racing are 1 2 3 4 5 6 7 over-rated 100. The chances of getting caught doing things like burn outs, donuts, fish 1 2 3 4 5 6 7 tails, drifting or skids are over-rated 101. There is no excuse for 1 2 3 4 5 6 7 street racing 102. There is no excuse for doing things like burn 1 2 3 4 5 6 7 outs, donuts, fish tails, drifting or skids 103. People who race other cars are generally better 1 2 3 4 5 6 7 drivers 104. People who do burn outs, donuts, fish tails, drifting 1 2 3 4 5 6 7 or skids are generally better drivers 105. People who race other cars are generally more 1 2 3 4 5 6 7 careful on the road 106. People who do things like burn outs, donuts, fish tails, drifting or skids are 1 2 3 4 5 6 7 generally more careful on the road Hooning behaviours 299
Strongly Strongly Neutral Disagree Agree 107. It’s okay to race other cars, as long as you don’t 1 2 3 4 5 6 7 do it too much 108. It’s okay to do things like burn outs, donuts, fish tails, drifting or skids, as 1 2 3 4 5 6 7 long as you don’t do it too much 109. It’s okay to race other cars, as long as no one 1 2 3 4 5 6 7 gets hurt 110. It’s okay to do things like burn outs, donuts, fish 1 2 3 4 5 6 7 tails, drifting or skids, as long as no one gets hurt 111. Street racing is wrong 1 2 3 4 5 6 7 112. Doing things like burn outs, donuts, fish tails, 1 2 3 4 5 6 7 drifting or skids is wrong 113. The police spend too much time hassling people who 1 2 3 4 5 6 7 race other cars 114. The police spend too much time hassling people who do things like burn outs, 1 2 3 4 5 6 7 donuts, fish tails, drifting or skids 115. Street racing is NOT acceptable, even if it is done away from the 1 2 3 4 5 6 7 general public (i.e., not on main roads or in suburban streets) 116. What about things like burn outs, donuts, fish tails, 1 2 3 4 5 6 7 drifting or skids? 117. Doing things like burn outs, donuts, fish tails, drifting or skids is okay if it is done in a quiet area 1 2 3 4 5 6 7 (e.g., industrial estate) and spectators are a safe distance from the cars 118. What about street racing? 1 2 3 4 5 6 7 119. Doing things like burn outs, donuts, fish tails, 1 2 3 4 5 6 7 drifting or skids is risky 120. What about street racing? 1 2 3 4 5 6 7
Click here to submit responses and move to next page
300 Hooning behaviours
The following questions relate to what YOU think about “hooning”:
Strongly Strongly Neutral Disagree Agree 121. Street racing…
… gives me a thrill 1 2 3 4 5 6 7 … makes me feel like a good 1 2 3 4 5 6 7 driver … makes me feel powerful 1 2 3 4 5 6 7 … makes me feel in control of 1 2 3 4 5 6 7 things 122. Doing things like burn outs, donuts, fish tails, drifting or skids…
… gives me a thrill 1 2 3 4 5 6 7 … makes me feel like a good 1 2 3 4 5 6 7 driver … makes me feel powerful 1 2 3 4 5 6 7 … makes me feel in control of 1 2 3 4 5 6 7 things
Strongly Strongly Neutral Disagree Agree 123. I would be embarrassed to tell my
friends… … if I was booked for a hooning offence and lost my car for 48 1 2 3 4 5 6 7 hours … if I was booked for a second hooning offence and lost my car 1 2 3 4 5 6 7 for 3 months … if I was booked for a third hooning offence and lost my car 1 2 3 4 5 6 7 permanently 124. I would be embarrassed to tell my
family… … if I was booked for a hooning offence and lost my car for 48 1 2 3 4 5 6 7 hours … if I was booked for a second hooning offence and lost my car for 1 2 3 4 5 6 7 3 months … if I was booked for a third hooning offence and lost my car 1 2 3 4 5 6 7 permanently
Hooning behaviours 301
Strongly Strongly Neutral 125. Street racing… Disagree Agree … makes me feel bad 1 2 3 4 5 6 7
… makes me feel guilty 1 2 3 4 5 6 7
… frightens me 1 2 3 4 5 6 7
… makes me feel anxious 1 2 3 4 5 6 7
… could damage my car 1 2 3 4 5 6 7
… could lead to serious injury 1 2 3 4 5 6 7
… could mean I’d lose my job 1 2 3 4 5 6 7 126. Doing things like burn Strongly Strongly Neutral outs, donuts, fish tails, Disagree Agree drifting or skids… … makes me feel bad 1 2 3 4 5 6 7
… makes me feel guilty 1 2 3 4 5 6 7
… frightens me 1 2 3 4 5 6 7
… makes me feel anxious 1 2 3 4 5 6 7
… could damage my car 1 2 3 4 5 6 7
… could lead to serious injury 1 2 3 4 5 6 7
… could mean I’d lose my job 1 2 3 4 5 6 7
127. Overall, more good Strongly Strongly Neutral things are likely to Disagree Agree happen than bad while… … street racing 1 2 3 4 5 6 7 … doing things like burn outs, donuts, fish tails, drifting or 1 2 3 4 5 6 7 skids Strongly Strongly Neutral Disagree Agree 128. Street racing isn’t worth 1 2 3 4 5 6 7 the risks 129. Doing things like burn outs, donuts, fish tails, 1 2 3 4 5 6 7 drifting or skids isn’t worth the risks
Click here to submit responses and move to next page
302 Hooning behaviours
The following questions ask about things like burn outs, donuts, fish tails, drifting, skids, street racing and time trials, which will be referred to as “hooning behaviours”:
Strongly Strongly Disagree Agree 130. I have a lot in common with other people who do “hooning 1 2 3 4 5 6 behaviours” 131. The fact that I am someone who does “hooning 1 2 3 4 5 6 behaviours” rarely enters my mind 132. In general, I’m glad to be someone who does “hooning 1 2 3 4 5 6 behaviours” 133. I find it difficult to form a bond with other people who do 1 2 3 4 5 6 “hooning behaviours” 134. I often think about the fact that I am someone who does 1 2 3 4 5 6 “hooning behaviours” 135. I often regret that I am someone who does “hooning 1 2 3 4 5 6 behaviours” 136. I feel strong ties to other people 1 2 3 4 5 6 who do “hooning behaviours” 137. Overall, being someone who does “hooning behaviours” has 1 2 3 4 5 6 very little to do with how I feel about myself 138. Generally, I feel good when I think about myself as someone 1 2 3 4 5 6 who does “hooning behaviours” 139. I don’t feel a sense of being “connected” with other people 1 2 3 4 5 6 who do “hooning behaviours” 140. In general, being someone who does “hooning behaviours” is 1 2 3 4 5 6 an important part of my self- image 141. I don’t feel good about doing 1 2 3 4 5 6 “hooning behaviours”
Hooning behaviours 303
These last few questions ask about driving generally:
Strongly Strongly
Disagree Agree 142. It’s fun to beat other drivers 1 2 3 4 when the light changes
143. It’s really satisfying to pass other 1 2 3 4 cars on the highway 144. It’s a thrill to out-manoeuvre 1 2 3 4 other drivers 145. It’s fun to weave through slower 1 2 3 4 traffic 146. Taking risks in traffic makes 1 2 3 4 driving more fun
147. While driving, how often do Very Never you… Often … take chances for the fun of it? 1 2 3 4 … see how fast you can drive out of 1 2 3 4 curiosity? … pass other cars because it’s 1 2 3 4 exciting? … out-manoeuvre other drivers for the 1 2 3 4 thrill of it? … drive dangerously because you 1 2 3 4 enjoy it? … test your skills in ways others might 1 2 3 4 find risky? … take some risks because it feels 1 2 3 4 good? … try and beat other drivers leaving a 1 2 3 4 stop light to impress someone?
Click here to submit responses and move to next page
If you have any other comments about the vehicle impoundment legislation not covered in the survey, please type them here:
Allow up to 1000 characters
Thank you for completing the whole survey!
Your time and assistance is much appreciated, and we would like to give you one movie ticket voucher as a small thank you gift.
Please enter your email address in the box below so a member of the research team can contact you in the next few days to discuss the best way to get your voucher to you.
304 Hooning behaviours
Please note that this information is stored in a separate database to your survey and cannot be matched back to your responses.
Allow up to 50 characters
Click to submit survey
Redirect to www.carrsq.qut.edu.au
Hooning behaviours 305
APPENDIX C.3
STUDY 1B INFORMATION SHEET AND CONSENT ITEM
PARTICIPANT INFORMATION for QUT
RESEARCH PROJECT
Your views on Queensland’s vehicle impoundment legislation
Research Team Contacts Nerida Leal Barry Watson Kerry Armstrong
[email protected] [email protected] [email protected]
Description
This project is being undertaken as part of a PhD project for Nerida Leal. While the project has received funding from the Growing the Smart State PhD Funding Program, only the research team will have access to project data. The purpose of this project is to better understand street racing and associated (“hooning”) behaviours, and determine what drivers think about Queensland’s “anti-hooning” legislation and its effectiveness. As a Queensland driver, you can provide unique insight into these issues.
Participation
Your participation in this project is voluntary. If you do agree to participate, you can withdraw from participation at any time during the project without comment or penalty. Your decision to participate will in no way impact upon your current or future relationship with QUT (for example your grades) or with the Queensland Government. However, as this project involves the submission of an anonymous (non-identifiable) survey, it will not be possible to withdraw once you have submitted it, as it will not be possible for the researchers to identify your submission. Your participation will involve completing a survey regarding street racing and associated (hooning) behaviours and Queensland’s “anti-hooning” legislation. Some items about demographic information and your driving history are also included. It is expected that completion of the survey will take approximately 15 – 20 minutes. Once you have completed the entire survey, you will be eligible to receive two movie ticket vouchers to reimburse you for your time.
Expected benefits
It is expected that this project will not directly benefit you. However, it may benefit researchers and policy makers, as there has been very little research conducted in this area to date.
306 Hooning behaviours
Risks
There are no risks beyond normal day-to-day living associated with your participation in this project. Although the behaviour under investigation is an illegal behaviour, your responses cannot be used in any prosecution as such information is not permitted under Queensland legislation, and no one other than the research team will have access to project data. QUT provides for limited free counselling for research participants of QUT projects, who may experience some distress as a result of their participation in the research. Should you wish to access this service please contact the QUT Psychology Clinic on 3138 4578. Please indicate to the receptionist that you are a research participant.
Confidentiality
All comments and responses are anonymous and will be treated confidentially. The names of individual persons are not required in any of the responses.
Consent to Participate
To preserve your anonymity, you will not be required to sign a consent form, as submission of the completed survey will be accepted as an indication of your consent to participate in this project.
Questions / further information about the project
Please contact the research team members named above to have any questions answered or if you require further information about the project.
Concerns / complaints regarding the conduct of the project
QUT is committed to researcher integrity and the ethical conduct of research projects. However, if you do have any concerns or complaints about the ethical conduct of the project you may contact the QUT Research Ethics Officer on 3138 2340 or [email protected]. The Research Ethics Officer is not connected with the research project and can facilitate a resolution to your concern in an impartial manner.
By clicking "submit" below you acknowledge the above information and consent to participate in the research
Submit I consent to participate
Hooning behaviours 307
APPENDIX C.4: CORRELATION MATRICES FOR STUDY 1B HIERARCHICAL REGRESSION ANALYSES
Table C4.1 Correlation matrix for hierarchical regression analyses for noise and smoke-related hooning behaviours (N = 228)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 DV1. Freq BO .222 .031 -.010 .087 .049 .234 .034 -.024 .057 .023 .003 -.041 .019 .121 .024 -.014 .023 .002 .140 .259 .074 .254 .216 .023 DV2. Intentions BO .207 .134 .073 .307 .114 .201 .033 .107 .096 .152 .137 -.042 -.122 .198 .054 .012 .104 -.066 .043 .422 .252 .397 .249 .240 1. Driving hrs/wk ~ 2. BO crashes .096 ~ 3. SR crashes .009 .172 ~ 4. Speeding freq .087 .074 .023 ~ 5. Veh defect freq .052 .054 .153 .246 ~ 6. Prev BO offences .238 .273 .114 -.062 .123 ~ 7. Impoundment (self) -.011 .146 -.050 -.057 .122 .491 ~ 8. Fr. w BO offences .125 .167 .147 -.025 .140 .284 .190 ~ 9. Avoidance score .070 .014 .176 .050 -.017 .282 -.558 .065 ~ 10. Avoid strat (self) .075 .069 .147 -.013 .124 .131 .059 .183 .066 ~ 11. Avoid strat (friend) .166 .051 .027 .051 .229 .185 .023 .188 .121 .723 ~ 12. Detection (self) .004 .064 .023 -.209 -.085 .117 .045 .154 .059 .078 .067 ~ 13. Detection (others) .146 -.020 .022 -.190 -.017 .076 .050 .108 -.007 .084 .021 .411 ~ 14. Certainty (self) .040 .010 -.005 .041 .106 .124 .165 .141 -.056 .085 .101 .304 .129 ~ 15. Certainty (others) .141 .073 -.081 -.045 .025 .067 .076 .093 -.028 .045 .023 .158 .350 .363 ~ 16. Swiftness (self) .063 .032 -.077 .035 .075 .034 .128 .073 -.105 -.042 -.041 .030 .098 .365 .227 ~ 17. Swiftness (others) .080 -.036 -.023 .079 .111 .097 .055 .085 .044 .08 .055 .029 .160 .254 .583 .374 ~ 18. Severity (self) -.043 .007 .032 -.072 .046 .044 .001 .062 .019 .047 .024 .176 .203 .157 .066 .120 .175 ~ 19. Severity (others) -.027 -.008 .003 .029 .108 .035 .009 -.095 .011 -.020 -.072 .068 .272 .222 .541 .227 .525 .325 ~ 20. Diff Association .188 .095 .005 .306 .120 .214 .106 .200 .067 .295 .219 .005 .022 .119 .178 .116 .136 .048 .163 ~ 21. Imitation -.023 .140 .086 .200 .067 .062 .131 .057 -.034 .152 .126 .033 -.106 .108 .007 -.037 -.020 -.066 .087 .224 ~ 22. Diff Reinforcement .152 -.089 .013 .316 .205 .173 .149 .169 .022 .255 .184 -.050 -.062 .159 .080 .062 .145 -.004 .205 .669 .221 ~ 23. Definitions .093 .073 -.019 .241 .204 .073 -.022 -.023 .077 .272 .143 .008 .055 .144 .161 .119 .183 .234 .296 .442 .142 .602 ~ 24. Thrill-seeking .021 .003 .026 .342 .209 .034 .042 .095 -.004 .096 .164 -.276 -.187 .069 -.061 .042 .008 .000 -.067 .153 .204 .182 .248 ~
* Blue font indicates significant Pearson’s r correlation coefficients (p < .05)
308 Hooning behaviours
Table C4.2 Correlation matrix for hierarchical regression analyses for illegal street racing (N = 228)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 DV3. Freq st racing .231 -.012 .154 .046 .099 .140 .027 .098 .173 .163 .107 -.162 -.075 -.012 -.067 .118 .032 .149 .106 .389 .115 .380 .420 .092 DV4. Intentions SR .205 .056 .142 .237 .165 .215 .096 .175 .183 .288 .205 -.182 -.221 -.069 -.109 .040 .042 .089 -.015 .523 .165 .453 .388 .271 1. Driving hrs/wk ~ 2. BO crashes .096 ~ 3. SR crashes .009 .172 ~ 4. Speeding freq .094 .074 .023 ~ 5. Veh defect freq .052 .054 .153 .246 ~ 6. Prev SR offences .224 .077 .067 .027 .051 ~ 7. Impoundment (self) -.016 .090 -.022 -.144 -.088 .263 ~ 8. Fr. w SR offences .102 .068 .126 -.019 .092 .289 .154 ~ 9. Avoidance score .218 -.033 .111 .141 .106 .624 -.391 .171 ~ 10. Avoid strat (self) .157 .049 .045 .019 .161 .107 .003 .126 .054 ~ 11. Avoid strat (friend) .150 .043 .088 .048 .207 .172 .050 .225 .064 .840 ~ 12. Detection (self) -.063 .026 -.045 -.174 -.044 -.027 -.057 .055 -.012 -.070 -.003 ~ 13. Detection (others) .010 -.071 -.008 -.175 -.084 .080 -.003 -.058 .062 -.092 -.077 .393 ~ 14. Certainty (self) -.011 -.031 -.103 -.009 .040 .014 .104 .081 -.094 .032 .080 .284 .237 ~ 15. Certainty (others) .054 -.004 -.046 -.075 .005 .032 .080 -.087 .002 -.047 -.003 .155 .406 .478 ~ 16. Swiftness (self) .034 .048 -.253 -.032 .025 .079 .050 .106 .024 .053 .065 -.073 .030 .305 .177 ~ 17. Swiftness (others) .094 .085 .009 .000 .101 .115 .095 .009 .048 .015 .017 .001 .264 .330 .745 .219 ~ 18. Severity (self) .020 .038 .058 -.058 .027 .079 .005 .114 .098 .049 .071 .075 .161 .143 .123 .118 .127 ~ 19. Severity (others) .009 .005 -.042 -.017 .080 -.028 .040 -.113 -.034 .001 .046 .074 .236 .267 .603 .151 .617 .282 ~ 20. Diff Association .243 .062 .094 .291 .086 .144 -.018 .184 .121 .294 .288 -.163 -.130 -.071 -.051 .104 .008 .107 .067 ~ 21. Imitation .017 .140 .090 .206 .087 -.062 -.061 .073 -.014 .162 .183 -.051 -.070 .033 .023 -.048 -.003 -.060 .115 .343 ~ 22. Diff Reinforcement .178 .062 .079 .312 .184 .094 -.015 .132 .099 .375 .306 -.260 -.211 -.094 -.039 .066 .050 .046 .126 .683 .238 ~ 23. Definitions .159 .023 .050 .253 .220 .062 -.033 .043 .097 .332 .263 -.204 -.106 .023 -.036 .128 .066 .247 .117 .531 .174 .683 ~ 24. Thrill-seeking .021 .003 .026 .342 .209 .102 -.033 .128 .115 .124 .162 -.238 -.151 -.062 -.169 .055 -.056 -.048 -.111 .192 .171 .247 .299 ~
* Blue font indicates significant Pearson’s r correlation coefficients (p < .05)
Hooning behaviours 309
APPENDIX D.1
STUDY 2B OFFENCE GROUPS AND SUBGROUPS
HOONING‐RELATED OFFENCES . Dangerous driving o DANGEROUS DRIVING . Driving without due care and attention o CARELESS DRIVING/DUE CARE AND ATTENTION . Racing and speed trials on roads o RACE BETWEEN VEHICLES ON ROAD o SPEED TRIAL ON A ROAD . Undue noise and smoke o START/DRIVE VEHICLE IN A WAY THAT MAKES UNNECESSARY NOISE OR SMOKE o WILFULLY START/DRIVE VEHICLE IN WAY THAT MAKE UNNECESSARY NOISE/SMOKE
IMPAIRED DRIVING OFFENCES . Alcohol o DRIVE UNDER INFLUENCE OF LIQUOR (0.150 AND OVER ) o DRIVE UNDER INFLUENCE OF LIQUOR (NO READING) o DRIVE UNDER INFLUENCE OF LIQUOR (UNDER 0.150) o DRIVE/ATTEMPT PUT IN MOTION/IN CHARGE M/V UNDER INFLUENCE LIQ (<0.150) o DRIVER DRINK LIQUOR WHILE DRIVING o PCA 0.070 LESS THAN 0.090 WHILE HOLDER OF P L OR UNLICENCED o PCA UNDER 0.050 LESS THAN 0.070 WHILE HOLDER OF OPEN LICENCE . Drugs o DRIVE UNDER INFLUENCE OF DRUGS . Fail to supply specimen o FAIL TO SUPPLY BLOOD SPECIMEN o FAIL TO SUPPLY ROADSIDE TEST
POLICE / GOVERNMENT INSTRUCTION OFFENCES . Administrative requirement o FAIL TO NOTIFY CHANGE OF NAME/ADDRESS WITHIN 28 DAYS o FAIL TO NOTIFY NAME/ADDRESS CHANGE WITHIN 28 DAYS o FAIL TO STATE NAME AND ADDRESS OR GIVE EVIDENCE OF CORRECTION
310 Hooning behaviours
o GIVE INFORMATION IN AN OFFICIAL DOCUMENT THAT IS FALSE OR MISLEADING o SUPPLY FALSE/MISLEADING INFORMATION IN OFFICIAL DOCUMENT . Crash duties o DRIVE INVOLVED IN CRASH FAIL TO FULFIL DUTIES o FAIL TO STOP AT ROAD ACCIDENT . Fail to stop o FAIL TO STOP VEHICLE FOR PRESCRIBED PURPOSE ‐ PRIVATE VEHICLE . Inspection o OWNER FAIL TO HAVE VEHICLE INSPECTED AS REQUIRED . Produce licence o FAIL TO PRODUCE DRIVER'S LICENCE o FAIL TO PRODUCE NON QLD OR DEFENCE FORCE LIC WITHOUT REASONABLE EXCUSE o FAIL PRODUCE PROVISIONAL DRIVER LICENCE AS REQUIRED o FAIL TO PRODUCE LEARNER DRIVER LICENCE AS REQUIRED o FAIL TO PRODUCE LEARNERS D/L AS REQUIRED BY POLICE OFFICER o FAIL TO PRODUCE PROVISIONAL D/L AS REQUIRED BY POLICE OFFICER . Provide information o DRIVER MUST GIVE DRIVER'S REQUIRED PARTICULARS TO A POLICE OFFICER o FAIL TO SUPPLY NAME AND ADDRESS
REGISTRATION OFFENCES . Registration plates / labels o MAKE/SELL/POSSESS SOMETHING RESEMBLING CERT/PLATE/LABEL/PERMIT o ALTER/DEFACE CERTIFICATE/PLATE/LABEL o OWNER FAILS TO AFFIX/DISPLAY SAFETY CERTIFICATE ON VEHICLE FOR SALE o P1 TYPE LICENCE HOLDER FAIL TO DISPLAY RED PLATES FRONT & REAR OF CAR o P2 TYPE LICENCE HOLDER FAIL DISPLAY GREEN PLATES FRONT & REAR OF CAR o PERSONALISED PLATE/S ATTACHED NOT IN ACCORDANCE WITH REGULATION o R/O FAIL ENSURE NUMBER PLATE IS ATTACHED AS REQUIRED UNDER SECT 24(1) o R/O FAIL TO ATTACH LABEL IN ACCORDANCE WITH REGULATION o R/O FAIL TO ATTACH LABEL WITHIN TIME SPECIFIED o R/O FAIL TO ENSURE NUMBER PLATES ATTACHED FRONT/REAR o R/O FAIL TO REMOVE OLD REGISTRATION LABEL o R/O FAIL TO RETURN NUMBER PLATE/S AFTER REGISTRATION EXPIRES Hooning behaviours 311
o USE/PERMIT USE CERT/PLATE/LABEL/PERMIT NOT LEGIBLE TO WRITE/MARK/COLOU o USE/PERMIT USE LABEL/PLATE ATTVEH RECORDED CANC/LOST/STOLEN/DESTR/DAMA o USE/PERMIT USE LABEL/PLATE/PERMIT FOR ANOTHER VEHICLE o USE/PERMIT USE OF DEALER PLATE FOR REASONS OTHER THAN REG PERMITS o USE/PERMIT USE W/O LABEL/NUMBER PLATE/PERMIT ATT OR NOT ATT AS REQ . Transfer of registration o ACQUIRER FAIL TO TRANSFER REGISTRATION . Uninsured (compulsory third party) o DRIVE AN UNINSURED CLASS 1, 2, 6, 8, 13, 16 OR 24 MOTOR VEH ON A ROAD o DRIVE AN UNINSURED CLASS 5, 12, 14, 15 OR 17 21 MOTOR VEH ON A ROAD . Unregistered o USE OF OR PERMIT USE OF UNREGISTERED VEHICLE o USE OR PERMIT USE OF UNREG 4 CYLINDER OR 2 ROTOR PASS MOTOR VEHICLE o USE OR PERMIT USE OF UNREG 5 0R 6 CYLINDER OR 3 ROTOR PASS MOTOR VEH o USE OR PERMIT USE OF UNREG 7 OR 8 CYLINDER PASSENGER MOTOR VEHICLE o USE OR PERMIT USE OF UNREGISTERED MOTORCYCLE
RESTRAINT OFFENCES . Helmet (self) o MOTOR BIKE RIDER FAIL TO WEAR HELMET . Helmet (passenger) o RIDE MOTOR BIKE WITH PASSENGER NOT WEARING HELMET . Seatbelt (self) o DRIVE FAIL TO WEAR SEAT BELT o DEMERIT POINT PENALTY FOR 2 OR MORE SEATBELT OFFENCES WITHIN 12 MTHS . Seatbelt (passenger) o DRIVE MOTOR VEHICLE WHILE PASSENGER < 1YO UNRESTRAINED o DRIVE MOTOR VEHICLE WHILE PASSENGER AT LEAST 1 BUT <16YRS UNRESTRAINED o PASSENGER =>16YO FAIL TO WEAR SEAT BELT o PASSENGER =>16YO OCCUPY POSITION WITHOUT SEAT BELT WHEN ONE AVAILABLE
312 Hooning behaviours
ROAD RULE / SIGN / MARKING OFFENCES . Body out of car o TRAVEL IN MOTOR VEHICLE WITH PART OF BODY OUTSIDE WINDOW/DOOR o DRIVE MOTOR VEHICLE WHILE PASSENGER HAS PART OF BODY OUT WINDOW/DOOR . Fail to give way o FAIL TO GIVE WAY AT T INTERSECTION AS REQUIRED o FAIL TO GIVE WAY TO VEHICLE WHEN ENTERING ROUNDABOUT o FAIL TO GIVE WAY WHEN CHANGING LANES ON MULTI LANE ROAD o FAIL TO GIVE WAY WHEN ENTERING A ROAD FROM ROAD RELATED AREA o FAIL TO GIVE WAY WHEN MAKING U‐TURN o FAIL TO GIVE WAY WHEN LINES OF TRAFFIC MERGING . Follow too closely o FOLLOW ANOTHER VEHICLE TOO CLOSELY . Headlights o DRIVE VEHICLE NIGHT/REDUCED VISIBILITY NO LIGHTS OPERATING OR VISIBLE o USE HIGH BEAM <200M FROM ONCOMING VEHICLE o USE HIGH BEAM <200M BEHIND ANOTHER VEHICLE o OPERATE REAR FOG LIGHT IN OTHER THAN REDUCED VISIBILITY . Horn o PERSON IN/ON VEHICLE USE BELL/HORN/WARNING DEVICE OTHER THAN PERMITTED o USE HORN OTHER THAN AS PERMITTED . Illegal manoeuvre o IMPROPER RIGHT TURN FROM 2 WAY ROAD o IMPROPER RIGHT TURN FROM 2 WAY ROAD WITH CENTRE LINE/MEDIAN o MAKE U‐TURN AT INTERSECTION CONTROLLED BY TRAFFIC LIGHTS (NO SIGN) . Lane-keeping o DRIVE IN BUS LANE (NOT EXEMPTED VEHICLE) o DRIVE IN TRANSIT LANE (NOT EXEMPTED VEHICLE) o FAIL TO KEEP LEFT OF CENTRE DIVIDING LINE o FAIL TO KEEP LEFT OF CENTRE OF ROAD o FAIL TO KEEP LEFT OF DOUBLE CONTINUOUS DIVIDING LINES o FAIL TO KEEP TO LEFT SIDE OF ROAD (NOT MULTI‐LANE) o DRIVE IN R/LANE ON MULTI‐LANE ROAD >80KM/H WITHOUT REASONABLE EXCUSE . Mobile phone o DRIVER USE HAND HELD MOBILE PHONE . Overtaking o OVERTAKE VEHICLE TO THE LEFT OF THAT VEHICLE o OVERTAKE WHEN NOT SAFE TO DO SO Hooning behaviours 313
o DISOBEY 'NO OVERTAKING OR PASSING' SIGN (OVERTAKING) . Radar detector o DRIVE VEHICLE FITTED WITH SPEED DETECTION DEVICE DETECTOR . Railway level crossing o CROSSING RAILWAY LINE WHILE SIGNAL OPERATING . Road marking o CROSS CONTINUOUS LINE DIVIDING LANES ON MULTI LANE ROAD o CROSS CONTINUOUS WHITE EDGE LINE o DISOBEY DIRECTIONAL ARROW ON ROAD . Sign o DISOBEY 'LEFT TURN ONLY' SIGN o DISOBEY 'NO LEFT TURN' SIGN o DISOBEY 'NO RIGHT TURN' SIGN o DISOBEY NO U‐TURN SIGN AT BREAK IN DIVIDING STRIP o FAIL TO STOP AT 'STOP' SIGN AT A PLACE . Signalling o FAIL TO SIGNAL INTENTION TO CHANGE DIRECTION LEFT o FAIL TO SIGNAL INTENTION TO CHANGE DIRECTION RIGHT o FAIL TO SIGNAL LEFT BEFORE LEAVING ROUNDABOUT . Traffic lights o DISOBEY OVERHEAD LANE CONTROL ‐ RED X o FAIL TO STOP AT RED LIGHT o FAIL TO STOP AT RED TRAFFIC ARROW o FAIL TO STOP AT YELLOW LIGHT o PROCEED CONTRARY TO TWIN RED LIGHTS . Other o DRIVE ON TRAFFIC ISLAND o DRIVE WITH TV/VDU OPERATING AND SCREEN VISIBLE TO DRIVER o DRIVER NOT HAVE PROPER CONTROL OF VEHICLE o UNLAWFUL USE OF MOTOR VEHICLE
SPEEDING OFFENCES . Low-range (up to 15km/hr over limit) o EXCEED 50 KM/H (LOWER DEFAULT SPEED LIMIT BUA)BY LESS THAN 13KM/H o EXCEED 60KM/H (DEFAULT SPEED LIMIT BUA) BY LESS THAN 15 KM/H o EXCEED SPEED LIMIT BY LESS THAN 15 KM/H . Mid-range (15 – 30km/hr over limit) o EXCEED 100KM/H (DEFAULT SPEED LIMIT) BY MORE THAN 20KMH NOT MORE 30KMH o EXCEED 50KMH(LOW DEFAULT SPD LT BUA)BY MORE THAN 20KMH NOT MORE 30KMH o EXCEED 100 KM/H (DEFAULT SPEED LIMIT) BY 15KM/H < 30KM/H
314 Hooning behaviours
. High-range (30+km/hr over limit) o EXCEED 100KM/H (DEFAULT SPEED LIMIT) BY MORE THAN 30KMH NOT MORE 40KMH o EXCEED 100KM/H (DEFAULT SPEED LIMIT) BY MORE THAN 40KM/H o EXCEED SPEED LIMIT IN SPEED LIMITED AREA BY MORE THAN 40KM/H o EXCEED SPEED LIMIT IN SPEED ZONE BY MORE THAN 30 KM/H NOT MORE 40 KM/H . Not specified o EXCEED GAZETTED SPEED LIMIT o EXCEED SPEED LIMIT
LICENCE‐RELATED DRIVING OFFENCES . Condition of licence o FAIL TO COMPLY WITH CONDITION ON LICENCE . Disqualified driving o DISQUALIFIED DRIVING o DRIVER DISQ BY COURT ORDER AND NOT OBTAINED LIC AT END OF DISQ PERIOD . Expired licence o DRIVER WITH LEARNER LICENCE RECENTLY EXPIRED NO MORE THAN 1 YEAR o DRIVER WITH OPEN LICENCE RECENTLY EXPIRED NO MORE THAN ONE YEAR o DRIVER WITH PROVISIONAL DRIVER LIC RECENTLY EXPIRED NO MORE THAN 1YR o DRIVER WITH LEARNER DRIVER LICENCE EXPIRED MORE THAN ONE YEAR o DRIVER WITH PROVISIONAL DRIVER LICENCE EXPIRED MORE THAN ONE YEAR o DRIVING WITH RECENTLY EXPIRED LEARNER DRIVER LICENCE o DRIVING WITH RECENTLY EXPIRED OPEN LICENCE . Inappropriate class of licence o DRIVER HOLDS DRIVER LIC BUT NOT AUTHORISED TO DRIVE CLASS OF VEHICLE o MASTER NOT APPROPRIATELY LICENSED . Learner plates o LEARNER FAIL TO DISPLAY L PLATES . Non-Queensland licence o DRIVER WITH NON‐QLD D/LIC (FOREIGN)(AUST CIT) 3 MTHS AFTER RESIDENCE o DRIVER WITH NON‐QLD D/LICENCE (I/STATE)3 MTHS AFTER TAKES UP RESIDENCE o DRIVER WITH NON‐QLD D/LIC(FOREIGN)(APPLIED RES VISA) 3M AFTER GET VISA
Hooning behaviours 315
. Suspended licence o DRIVE WHILE UNDER 24 HR SUSPENSION . Unaccompanied Learner driver o LEARNER DRIVE VEHICLE W/OUT PERSON OPEN/P LICENCE SEATED BESIDE DRIVER o LNR LIC H/DER RIDE M/BIKE UNDER DIRECTION PERSON NOT H/DER O TYPE >1YR o LRNR DRIVE VCLE W/OUT SEATING CAP. NOT UNDER DIRECT. PER WITH OPEN/P . Unlicensed driving o DRIVER NEVER HELD DRIVER LICENCE o POSSESS CANCELLED LICENCE o UNLICENSED DRIVING
VEHICLE DEFECT / MODIFICATION OFFENCES . Defective vehicle o DRIVE/PARK A DEFECTIVE VEHICLE o DRIVE/PARK VEH IF EQUIP DOES NOT COMPLY WITH VEHICLE STANDARDS o DRIVE/PARK VEH IF PARTS/EQUIP NOT IN SAFE CONDITION o DRIVE/PARK VEH NOT FITTED WITH EQUIP REQ BY VEHICLE STANDARDS . Ground clearance o DRIVE A VEHICLE EXCEEDS MAX GROUND CLEARANCE o DRIVE VEHICLE WITH GROUND CLEARANCE LESS THAN ALLOWED . Modifications o DRIVE/PARK VEH FITTED WITH OPTIONAL EQUIP NOT COMPLYING VEH STANDARDS o FIT LIGHT/REFLECTOR NOT COVERED UNDER SECT 5 OR GUIDELINE o OWNER NOT ENSURE MODIFICATION HAS BEEN APPROVED o PERSON MODIFIES A VEHICLE CHASSIS o R/O FAILS TO NOTIFY VEHICLE ALTERATION/S . Noisy o DRIVE VEHICLE WITH NOISY INSTRUMENT USED FROM OR ATTACHED o DVE/PARK/PERMIT DVE/PARK VEH WHEN STAT NOISE LVL 10DB(A) OR > STANDARD o DVE/PARK/PERMIT DVE/PARK VEH WHEN STAT NOISE LVL<10DB(A) ABVE STANDARD o PERSON IN/ON VEHICLE USE NOISY INSTRUMENT . Notice o PERSON FAILS TAKE ACTION IN RELATION TO VEH REQUIRED UNDER 124(1)(G) o PERSON FAILS TO COMPLY WITH DEFECT NOTICE . Silencer o DRIVE VEH WITH MODIFIED SILENCING DEVICE WHICH REDUCES EFFECTIVENESS
316 Hooning behaviours
o PERSON MODIFIES VEH SILENCING DEVICE WHICH REDUCES EFFECTIVENESS
OFFENCES DELETED FROM ANALYSES o BICYCLE RIDER CARRY PASSENGER NOT WEARING HELMET o BICYCLE RIDER FAIL TO WEAR HELMET o BUS GVM>5T/VEH GVM>12T EXCEED 100KMH BY AT LEAST 13KMH NOT MORE 20KM/H o BUS WITH GVM>5T OR VEH WITH GVM>12T EXCEED 100KM/H BY LESS THAN 13KM/H o CONSUMPTION OF ALCOHOL ON A RAILWAY o DISCHARGE FIREARM /THROW OR DISCHARGE STONE OR MISSILE ON A ROAD o DISOBEY PERMISSIVE PARKING SIGN (TIME) o DOUBLE PARK o DRIVE M/BIKE ON PUBLIC LAND CONTRAVENTION REG W/O REASONABLE EXCUSE o DRIVE M/V WITH PASS/GER IN/ON PART VEH NOT DESIGNED FOR PASSENGERS/GDS o DRIVE OR TOW VEHICLE WITH LOAD NOT PROPERLY SECURED o DRIVER FAIL REMOVE IGNITION KEY WITH NO‐ONE > 16YRS REMAINING IN VEHIC o DRIVER FAIL TO LOCK VEHICLE AFTER LEAVING VEHICLE o DRIVER USE HAND HELD MOBILE PHONE ‐ BICYCLE o FAIL TO PRODUCE TICKET o PARK IMPROPERLY IN PARKING BAY o PARK ON ROAD OTHER THAN IN DIRECTION OF TRAFFIC FLOW o PARK SO AS TO OBSTRUCT OTHER VEHICLES/PEDESTRIANS o PARK WITHIN 1M OF ANOTHER VEHICLE o PASSENGER EVADES PART/ALL OF LAWFUL FARE FOR TAXI OR LIMOUSINE o PASSENGER INTERFERE WITH DRIVERS CONTROL OF VEHICLE o PASSENGER ON MOTOR BIKE FAIL TO WEAR HELMET o PEDESTRIAN DISOBEY RED PEDESTRIAN LIGHT o PEDESTRIAN FAIL TO USE FOOTPATH o PEDESTRIAN HITCHHIKE ON A ROAD o PEDESTRIAN STAY ON ROAD LONGER THAN NECESSARY TO CROSS SAFELY o SMOKING ON RAILWAY o SPITTING ON PLATFORM/ROLLING STOCK/STRUCTURE o STATE FALSE OR MISLEADING INFORMATION TO A SHIPPING INSPECTOR o STOP CONTRARY TO CONTINUOUS YELLOW EDGE LINE o STOP CONTRARY TO DISABLED PARKING SIGN (NOT PERMITTED VEHICLE) o STOP CONTRARY TO NO PARKING SIGN Hooning behaviours 317
o STOP CONTRARY TO NO STOPPING SIGN o STOP ON BICYCLE PATH/FOOTPATH/SHARED PATH OR DIVID/NATURE STRIP IN BUA o STOP UNAUTHORISED VEHICLE IN BUS ZONE o STOP UNAUTHORISED VEHICLE IN TAXI ZONE STOP WITHIN 10M OF INTERSECTION WITHOUT TRAFFIC LIGHTS o o TAKE‐OFF AIRCRAFT FROM GOLD COAST WATERS WITHOUT APPROVAL o TOW BICYCLE/TRICYCLE/POWER ASSISTED CYCLE/TOY VEHICLE/WHEELCHAIR o TRAVEL IN OPEN PART OF MOTOR VEHICLE DESIGNED FOR CARRIAGE OF GOODS o TRAVEL IN OR ON PART OF MOTOR VEHICLE NOT DESIGNED FOR PASSENGER/GOODS o TRAVELLING WITHOUT PAYING CORRECT FARE o UNAUTHORISED PERSON FUNCTION AS TRAFFIC CONTROLLER WATERSKIER FAILS TO WEAR PFD TYPE 2 OR 3 o