Assessing the effectiveness of an education program for reducing the negative effects of pornography exposure
amongst young people
Marshall S. Ballantine-Jones
Discipline of Child & Adolescent Health,
Children's Hospital Westmead Clinical School, Faculty of Medicine and Health
University of Sydney
A thesis submitted to fulfil requirements for the degree of Doctor of Philosophy
2020
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Statement of Originality
I certify that the content of this thesis is original except as acknowledged in the text. No part of this thesis has been submitted for another degree at this or any other institution. Any assistance received has been appropriately acknowledged and any contributions to published studies are outlined.
31 July 2020 ______Marshall Ballantine-Jones Date
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Acknowledgements
I wish to express sincere gratitude and appreciation to the many people who enabled the completion of this thesis.
Emeritus Professor Kim Oates, who in teaching me how to research at the highest level, demonstrated humility, kindness and patience. I hope this work justified his coming out of supervision-retirement!
Professor Rachel Skinner, who provided insights and guidance at critical times. Dr Patricia Weerakoon, who planted the seeds for doctoral research in 2015.
Associate Professor Nicholas Wood and the staff of the Westmead Clinical School, for providing invaluable support and resources to advance this study, in an environment of wonderful people and high standards.
My wife Rebecca, whose love, support and friendship enabled me to complete this work, and who makes me a much better person. My children, Bronte, Oscar, Felix and Spencer, of whom I am very proud, and for whom I hope my research, and efforts as a dad, help them navigate life.
My father, Rev Dr Bruce Ballantine-Jones, and my stepmother Mrs Heather Ballantine-Jones, for their regular encouragement, love, interest and support.
My late mother Raema, who instilled a contagious love of knowledge, blended with wit and kindness, and demonstrated how to use superior talents to love and serve others.
My parents-in-law, Brian and Rhonda Eggert, for their constant support, encouragement, generosity, love, and patience enduring the son with a Peter Pan syndrome.
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My three best friends: Dr George Athas, who gave endless support, advice, editing and inspiration. Mr
Shan Joseph, for keeping me sane and fit. And Mr Robert Thomas, for being there whenever I need him.
Dr Bryan Cowling, for advice on developing the Education Intervention. Dr John Roodenberg, for the critique of the Chapter 4 baseline survey study, along with advice on thesis structure and content.
Mrs Cassandra Cassis, Mrs Kathryn Findlay and Mrs Tracey Mayo, who professionally edited the text.
The public and personal support of The Anglican Archbishop of Sydney, Dr Glenn Davies. The Anglican
Schools Corporation, for their financial and moral support. Mr Vanda Gould and the Anglo Australian
Christian & Charitable Fund, for their generous financial and moral support
Mr Russell Powell, Rev Andrew Nixon, Mr Greg Bridge, Rev David Milne and Panania Anglican Church
(who generously donated office space to use), for their friendship and support.
The principals, teachers, students and families of participating schools, who although anonymous, provided the resources and goodwill to conduct the various studies within this thesis.
Lastly, the many friends and supporters in the wider community, who have sent notes of support, assurances of prayers, and the encouragement to persevere through what were, on occasions, challenging times.
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Thesis Abstract
Introduction
A large body of research portrays pornography as having negative effects on adolescents, with limited research supporting a positive aspect. Exposure to pornography and sexualised social media may impact young people personally, relationally and socially. Despite this body of predominantly cross-sectional research, there is little evidence on how any negative effects may be countered or reduced.
Furthermore, there has only been a small number of school-based education programs seeking to address pornography and sexualised media, but they have not been empirically tested for effectiveness.
A small number of interventional studies related to adolescent behaviour change may provide limited guidance on addressing adolescent attitude and behaviour change if impacted by pornography. This gap in the literature justifies the conducting an interventional study on whether known negative effects can be reduced.
Objectives
Building on the available research, a theoretical framework is proposed, where three strategies are incorporated into a school program to reduce the personal, relational and social negative effects of pornography exposure. These strategies are: 1. didactic education; 2. peer-to-peer engagement; and 3. parental engagement.
Methods
In preparation for designing a program, an initial study was conducted to develop a baseline survey about pornography viewing and attitudes to pornography in a sample of 746 Year 10 high school students, aged 14–16 years, from NSW independent schools. The survey incorporated a number of previously validated instruments.
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The intervention was a six-lesson program, aligned with the Health and Physical Education strand of the
Australian National Curriculum, conducted on 347 Year 10 students from NSW independent schools, aged 14–16. The program was developed by the researcher, in consultation with school teachers, parents, and high school students.
Results
After successfully validating the baseline survey, further analysis demonstrated that the participating students were representative of wider studies, making it an appropriate instrument to evaluate an intervention, while also informing how the program should be developed. Some factors (e.g., self- esteem) were observed to behave differently than expected, raising additional questions about social media behaviours and narcissism, which the program could address.
Initial analysis of the intervention showed participants behaved typically of both the baseline study, and adolescents in wider research. Additionally, students exposed to social media computer applications were more likely to have narcissistic traits, which mediated the effect that pornography exposure or sexualised social media behaviours had on self-esteem.
Teacher feedback about the program was positive, with enthusiastic uptake of peer engagement activities. The activities involving parent-student engagement were not carefully monitored and may not have been implemented well.
The comparison of pre- and post-intervention data showed a significant increase in healthy attitudes related to pornography, positive views towards women, and responsible attitudes towards relationships. Additionally, students with regular viewing behaviours increased their efforts to reduce viewing, while increasing their unease about ongoing pornography viewing. Female students experienced mild reductions in self-promoting social media behaviours and pornography viewing
vi frequency. There was some evidence that the parental engagement strategy increased parent-student interactions, whilst peer-to-peer engagement helped reduce the influence of wider peer culture.
Students did not develop problematic behaviours or attitudes after doing the course.
Students who regularly viewed pornography had higher rates of compulsivity, which mediated their viewing behaviours such that, despite increases in attitudes opposed to pornography, unease about pornography viewing, or efforts to reduce undesirable behaviours, viewing prevalence did not reduce.
Additionally, there were trends of increased tensions in male parent-relationships after the home engagement activities, and female peer-relationships after the peer discussions or from the social media teaching content.
Conclusion
The program was effective at reducing a number of negative effects from pornography exposure, sexualised social media behaviours, and self-promoting social media behaviours, using the three strategies of didactic education, peer-to-peer engagement, and parental activities. Compulsive behaviours impeded efforts to reduce pornography viewing in some students, meaning additional therapeutic help may be required to support those struggling to produce behaviour change. Additionally, an adolescent’s engagement with social media may produce excess narcissistic traits, effecting self-esteem, and altering their interaction with pornography and sexualised social media behaviours.
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Authorship Attribution Statement
The candidate was responsible for coordinating the research under the supervision and guidance of
Primary Supervisor: Emeritus Professor Kim Oates MD DSc MHP FRACP FAFPHM, Discipline of Child and
Adolescent Health, Westmead Clinical School, University of Sydney. Secondary Supervisors: Professor
Rachel Skinner, Discipline of Child and Adolescent Health, Westmead Clinical School, University of
Sydney; Dr Patricia Weerakoon, honorary senior lecturer, Sydney Medical School - HIV, STIs and Sexual
Health Unit, University of Sydney.
The candidate took primary responsibility for all aspects of the research presented in this thesis, including the research of past literature, conceptualisation and design of research studies, data collection, quantitative and qualitative analyses, the interpretation and reporting of results.
Chapters 3 and 4 were reviewed by Dr Bryan Cowling and Dr John Roodenberg respectively.
Chapters 1-3 were edited by Mrs Casandra Cassis. Chapters 4-10 were edited by Mrs Tracey Mayo.
______30/7/2020 Marshall Ballantine-Jones Date
As supervisor for the candidate upon which this thesis is based, I can confirm that the authorship attribution statement above is correct.
______30/7/2020 Emeritus Professor Kim Oates Date
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Table of Contents
Chapter 1: Introduction and Literature Review 1
1.1 Background and Thesis Structure 1
1.1.1 Ethics approval 2
1.1.2 Definitions 3
1.1.3 Preliminary statistics 4
1.2 Literature Review Research Method 4
1.2.1 Data search method 4
1.2.2 Data search order 5
1.2.3 Data search key words 5
1.2.4 Limitations to search methodology 6
1.3 General Analysis of Research Data 7
1.3.1 Analysis of data sources 7
1.3.2 Cross-Sectional limitations and strengths 8
1.3.3 Longitudinal, interventional and controlled trial limitations and strengths 10
1.3.4 Conclusion 11
1.4 The Effects of Pornography on Young People 11
1.4.1 Positive personal effects of pornography 12
1.4.2 Negative personal effects of pornography 13
1.4.2.1 Objectification, sexual aggression, and negative gender attitudes 13
1.4.2.2 Mental Health and Behaviour changes 14
1.4.3 Neurological effects 15
1.4.4 Is compulsive pornography viewing a form of addictive behaviour? 17
1.4.5 Relational effects of pornography 19
1.4.6 The Social effects 21
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1.4.6.1 Is pornography production exploitative and harmful? 21
1.4.6.2 Pornography and popular culture 23
1.4.6.3 Pornography and Religion 24
1.4.7 Summary of the Effects of Pornography on Young People 25
1.5 Suggestions for reducing the negative effects of pornography 26
1.5.1 Education interventions 26
1.5.1.1 Pornography-related curriculum 26
1.5.1.2 Other education studies for avoidance and reduction of undesirable behaviours 27
1.5.1.3 General substance abuse curriculum 28
1.5.2 Parental interventions 29
1.5.3 Peer to peer relationships 32
1.5.4 Cognitive behavioural therapies and other responses to neurological harms 34
1.5.5 The neurological and behavioural effects of Abstinence 35
1.6 Chapter Summary 37
1.7 Chapter References 38
Chapter 2: Development of a Methodology 45
2.1 Introduction 45
2.2 An Absence of a Theoretical Framework for the Interventional Study 46
2.2.1 One Framework to Consider, the DSMM 46
2.3 Core Constructs for the Intervention 49
2.3.1 Negative Effects Constructs 49
2.3.2 Positive Solutions Constructs 50
2.3.3 Education 50
2.3.4 Parental engagement 50
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2.3.5 Peer engagement 50
2.3.6 Broader integration of community involvement 50
2.3.7 Behavioural therapies 50
2.4 Further Considerations for a School-Based Context? 51
2.4.1 Local Contexts for Program Frameworks 52
2.4.2 Limitations of some National Curricula 53
2.5 Need for an Assessment Instrument 55
2.6 Conclusion 55
2.7 Chapter References 57
Chapter 3: Design and Validation of Baseline Survey 58
3.1 Introduction 58
3.1.1 Important considerations for a school-based baseline survey 59
3.2 Aim 60
3.3 Method 60
3.3.1 Survey construction and implementation 60
3.3.2 Control Variable Selection 61
3.3 Survey Factors derived from Constructs 63
3.4 Results 69
3.4.1 Survey validation 69
3.4.2 Validating the constructs 71
3.4.2.1 The Super Wellbeing Scale 73
3.4.3 Limitations 76
3.5 Conclusion 76
3.6 Chapter References 78
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Chapter 4: Analysis of Survey Data 82
4.1 Introduction 82
4.2 Aims 83
4.3 Method 84
4.4 Results 85
4.4.1 Excluded control variables 85
4.4.2 Frequency results 86
4.4.3 Age of First-Time Viewing 87
4.4.4 Viewing Prevalence 87
4.4.5 Preferred Viewing Device 88
4.4.6 Viewing Intentionality 89
4.4.7 Sexualised Social Media Behaviours 89
4.4.8 Religion 90
4.4.9 Gender 91
4.5 Predictor Factor Results 97
4.5.1 Age of First-Time Exposure 97
4.5.2 Multiple and Simple Linear Regression on Viewing Prevalence 97
4.5.3 Gender 98
4.5.4 Parent Communication 98
4.5.5 Parental Rules 98
4.5.6 Peer Attitudes 98
4.5.7 Peer Behaviour 99
4.5.8 Religion 99
4.5.9 Viewing Intentionality 99
4.6 Outcome Factors influenced by Pornography Viewing 100
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4.6.1 Attitudes to Pornography 100
4.6.2 Women as Sex Objects 100
4.6.3 Uncommitted Sexual Exploration 100
4.6.4 Compulsivity 101
4.6.5 Distress from Viewing 101
4.6.6 Emotional Stability 101
4.6.7 Parent Relationships 101
4.6.8 Self-Esteem 102
4.6.9 Social Conduct 102
4.6.10 Peer Relationships 102
4.6.11 Social Empathy 102
4.6.12 Sexualised Social Media Behaviour (SSMB) 103
4.6.13 Super-Wellbeing 103
4.7 Discussion 106
4.7.1 Control variables 106
4.7.2 Predictor Factors 107
4.7.3 Outcome Factors 109
4.8 Conclusion 112
4.9 Chapter References 114
Chapter 5: Study Protocol for Education Pilot 116
5.1 Introduction 116
5.2 Chapter Synopsis 116
5.3 Background to Study 117
5.3.1 Prevalence data from a recent study 117
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5.4 Aims and Hypotheses 119
5.5 Development and Review Process for Pilot Program 120
5.5.1 Pedagogical Ethos 120
5.5.2 Teacher Feedback 122
5.5.3 Parent feedback 122
5.5.4 Student feedback 123
5.6 Recruitment and Implementation Process for the Pilot Program 124
5.6.1 Ethics Approval 124
5.6.2 Participant characteristics including sex, age range and inclusion/exclusion criteria 124
5.6.3 Study participation 125
5.6.4 Sample size and Cohan’s ‘d’ 125
5.6.5 Details of where the study will be undertaken (location/site/URL) 126
5.6.6 Details of how data will be collected and analysed 126
5.6.7 Risks associated with study 127
5.6.8 Invitation to Principals 127
5.6.9 Participation Information Statements to Students, Parents and Teachers 128
5.6.10 Teaching Content 128
5.6.11 Alternative teaching content 130
5.7 Data Analysis 130
5.7.1 Longitudinal Analysis 130
5.7.2 Qualitative Analysis 132
5.7.3 Potential significance of the study 133
5.8 Chapter References 135
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Chapter 6: Qualitative Analysis of Pilot Program 136
6.1 Introduction 136
6.2 Aims 137
6.3 Method 137
6.4 Results 138
6.4.1 Survey response 138
6.4.2 Teaching difficulty of lessons 138
6.4.3 Student engagement during the six lessons 139
6.4.4 Assessing the teaching experience of lessons 139
6.4.5 Peer Discussions 142
6.4.6 Parental diary home activity 142
6.4.7 Ideas for improving the program 142
6.4.8 Ad-hoc feedback 143
6.5 Discussion 143
6.5.1 Content and delivery of lessons 144
6.5.2 Peer discussions 145
6.5.3 Parental diary 145
6.6 Conclusion 146
6.7 Chapter References 147
Chapter 7: Data Integrity 148
7.1 Introduction 148
7.2 Aim 149
7.3 Method 149
7.4 Results 149
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7.4.1 2018 Survey and Pre-Intervention Data Comparison 150
7.4.2 Predictor Variable Comparison 155
7.4.3 Outcome Variable Comparison 160
7.5 Discussion 162
7.6 Conclusion 163
Chapter 8: Validating and exploring the Narcissism and Social Media Factors 164
8.1 Introduction 164
8.1.1 Why is narcissism in adolescents a concern? 164
8.1.2 The Present Study 165
8.2 Aim 166
8.3 Method 167
8.3.1 Measures 167
8.3.2 Validating the NPI-13 Scale 168
8.3.3 Social media behaviour items 168
8.3.4 Correlation analysis 169
8.3.5 Structural equation modelling (SEM) 169
8.4 Results 169
8.4.1 Validation of NPI-13 169
8.4.2 Factor analysis of social media items 170
8.4.3 Frequency Results 170
8.4.4 Correlation analysis 171
8.4.5 Path Analysis of Self-Esteem, Narcissism, pornography and 173
Sexualised Social Media Behaviours
8.4.6 Direct and Indirect Effect of Pornography Viewing on Self-Esteem 173
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8.4.7 Direct and Indirect Effect of Sexualised Social Media Behaviours on Self-Esteem 174
8.5 Discussion 176
8.6 Study Limitations 178
8.7 Conclusion 179
8.8 Chapter References 180
Chapter 9: Comparison of Pre- and Post-Intervention Data 181
9.1 Introduction 181
9.2 Aim 182
9.2.1 Chapter Hypotheses 182
9.3 Method 183
9.3.1 Prevalence Changes 183
9.3.2 Predictor Factor Changes 185
9.3.3 Outcome Factor Changes 185
9.3.4 Additional Observations 186
9.4 Results 186
9.4.1 Prevalence Variables 186
9.4.2 Preliminary Bivariate correlation matrix comparison 192
9.4.3 Predictor Variables 192
9.4.4 Outcome Variables 199
9.5 Discussion 210
9.5.1 The positive behaviour changes 210
9.5.2 Long-term effect of the intervention 211
9.5.3 The unsuccessful viewing behaviour change 212
9.5.4 Effectiveness of the three strategies 213
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9.5.5 Study Limitations 215
9.6 Conclusion 216
9.7 Chapter References 218
Chapter 10: Conclusion 219
10.1 Introduction 219
10.2 Study Summary 219
10.2.1 Development of Methodology 220
10.2.2 Baseline Study 220
10.2.3 Program Study Design and Implementation 222
10.3 Data Analysis of the Program 222
10.3.1 Qualitative Analysis of the Program 222
10.3.2 Preliminary Program Analysis 223
10.3.3 Narcissism and Social Media Analysis 223
10.3.4 Efficacy of Program for Knowledge, Attitude and Behaviour Change 224
10.4 Outcomes confirming the study hypotheses 224
10.5 Notable Unconfirmed Study Hypotheses 226
10.6 Outcomes Not Related to The Study Hypotheses 227
10.7 Study Limitations 228
10.8 Future Iterations of the Intervention Program 228
10.9 Conclusion 229
10.10 Chapter References 231
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Appendix A: Review of Some Current Pornography Curriculum 232
Appendix B: Baseline Survey Questionnaire 234
Appendix C: Letter to the Principal 239
Appendix D: Parental Participation Information Statement 241
Appendix E: Student Participation Information Statement 246
Appendix F: Teacher Participation Information Statement 249
Appendix G: Lesson Overview 254
Appendix H: Background Content for Lessons 258
Appendix I: Lesson Outlines 274
Appendix J: Parental Diary 292
Appendix K: New Baseline Instruments 294
Appendix L: Comparison between and DSM-5 Gambling Disorder Criteria and Compulsivity Scale 295
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List of Tables
Table 1.1 Literature Review Study Source 7
Table 1.2 Literature Review Study Type 7
Table 1.3 Literature Review Study Sample Size 8
Table 3.1 2018 Survey Construct Validation 75
Table 4.1 Baseline Survey Measures 83
Table 4.1.1 Parental Employment 86
Table 4.1.2 Parental Marital Status 86
Table 4.2 Viewing Prevalence Frequency 88
Table 4.3 Preferred Viewing Device 88
Table 4.4 Viewing Intentionality 89
Table 4.5 Sexualised Social Media Behaviour 90
Table 4.6 Religion 91
Table 4.7 Frequency and Outcome Factor Mean differences between Males and Females 95
Table 4.8.1 Predictor Factor Mean Differences between Males and Females 96
by Viewing Prevalence
Table 4.8.2 Outcome Factor Mean Differences between Males and Females by 96
by Viewing Prevalence
Table 4.9 Bivariate correlation matrix between all latent factors 104
Table 4.10 Predictor Factors that Contribute to Pornography Viewing Prevalence 105
Table 4.11 Outcome Factors affected by Pornography Viewing Prevalence 105
Table 5.1 Construct Themes for Baseline Survey Instruments 132
Table 6.1 Teacher Questionnaire for Pilot Intervention 140
Table 6.2 Lesson scores by each Teacher 141
Table 7.1 Proportions Comparison of Parental Marital Status between 151
Pre-Intervention and 2018 Surveys
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Table 7.2 Proportions Comparison of Parental Employment between 151
Pre-Intervention and 2018 Surveys
Table 7.3 Proportions Comparison of Pornography Viewing between 152
Pre-Intervention and 2018 Surveys
Table 7.4 Proportions Comparison of Religion Factor between 152
Pre-Intervention and 2018 Surveys
Table 7.5 Proportions Comparison of Preferred Viewing Device between 153
Pre-Intervention and 2018 Survey
Table 7.6 Proportions Comparison of Viewing Intentionality between 153
Pre-Intervention and 2018 Surveys
Table 7.7 Proportions Comparison of Sexualised Social Media Behaviours between 154
Pre-Intervention and 2018 Surveys
Table 7.8 Coefficient Comparisons of Predictor Regressors in Pornography Viewing 157
Multiple Regression Equation
Table 7.9 Simple Linear Regression of Predictor Variables on Pornography Viewing 158
Frequency
Table 7.10 Mean Comparisons of Predictor Variables between 2018 Survey 158
and Pre-Intervention Survey
Table 7.11 Pre-Intervention Bivariate Correlation Matrix 159
Table 7.12 Mean Comparisons of Outcome Variables between 2018 Survey 161
and Pre-Intervention Survey
Table 7.13 Mean Comparisons of Outcome Variables between 2018 Survey 161
and Pre-Intervention Survey
Table 8.1 Preferred Social Media App 171
Table 8.2 Followers, Following and Minutes Online 171
Table 8.3 Bivariate Correlation Matrix 172
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Table 8.4 SEM Pathway Analysis of the Effect of Pornography on Self-Esteem 175
with Narcissism as a Moderator with Latent Factors
Table 8.5 SEM Pathway Analysis of the Effect of Sexualised Social Media Behaviours 175
on Self-Esteem with Narcissism as a Moderator with Latent Factors
Table 9.1 Proportions Comparison of 6-Monthly Viewing Prevalence by Gender 188
Table 9.2 Pre and Post Intervention Comparisons of Frequency Variables 189
Table 9.3 Pre and Post Intervention Comparisons of Social Media Behaviours 190
Table 9.4 Proportion Comparison in Sexualised Social Media Behaviour 191
Attitude Questions
Table 9.5 Post-Intervention Bivariate Correlation Matrix 196
Table 9.6 Multiple Regression of Predictor Variables and Viewing Prevalence 197
(6-Monthly) Comparison
Table 9.7 Simple Linear Regression of Predictor Variables and Viewing Prevalence 197
(6-Monthly) Comparison
Table 9.8 One or Two-Tail T-Test Comparisons of Predictors Variables 198
Table 9.9 Exploratory Multiple Regression of Key Viewing Predictors on 198
2 Viewing Variables
Table 9.10 Ward Test for Coefficient Change in Simple Linear Regression Models 204
Table 9.11 Mean Change in Outcome Variables for All Students 205
Table 9.12 Mean Change in Outcome Variables for Low Pornography Users 206
Table 9.13 Mean Change in Outcome Variables for Regular Pornography Users 207
Table 9.14 Summary of Significant Results for Factor Mean Score Change 208
Table 9.15 Summary of Hypotheses Results 209
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List of Diagrams
Diagram 9.1 Post-Intervention Path Analysis for Attitudes to Pornography 201
and 6-Monthly Viewing Prevalence with Compulsivity as a
Mediator for Regular Users
Diagram 9.2 Post-Intervention Path Analysis for Attitudes to Pornography 201
and 14-Day Viewing Prevalence with Compulsivity as a
Mediator for Regular Users
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List of Abbreviations
ACT Acceptance and Commitment Therapy
APA American Psychiatric Association
ASAM American Society of Addiction Medicine
CBT Cognitive behavioural therapies
CFA Confirmatory factor analysis
CPUI-9 Cyber Pornography Use Inventory–9
CSB Compulsive sexual behaviour
DLPFC Dorsolateral prefrontal cortex
DSM-5 Diagnostic and Statistical Manual
DSMM Differential Susceptibility to Media Effects Model
EFA Exploratory factor analysis
HPE Health and Physical Education
KAB Knowledge, attitudes and behaviours
La Trobe La Trobe University
MAR Missing at Random
MCAR Missing Completely at Random
MI Multiple Imputation
NNFI Non-normed Fit Index
NPI-13 Narcissistic Personality Index 13
OLS Ordinary Least Squares
PCA Principle components analysis
PDHPE Personal Development, Health and Physical Education
PIS Participation Information Statements
PSHE Personal, Social, Health and Economic
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RCT Randomised Control Trial
RMSEA Root mean square error of approximation
SEM Structural Equation Modelling
SMA Social media apps
SRE Sex and Relationship Education
SSMB Sexualised Social Media Behaviour
STI Sexually transmitted infection
TF Tucker Lewis System
USD U.S. Dollar
VAW Violence against women
VIF Variance inflation factor
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Chapter 1: Introduction and Literature Review
1.1 Background and Thesis Structure
The aims of this study are to design, implement and assess a school education program for reducing
the negative effects of pornography exposure amongst young people. Despite there being ample
evidence for the negative impact pornography has on adolescents, there is a gap in the literature for
addressing these effects. In order to produce empirical data demonstrating a reduction in negative
effects, various processes are required, as outlined below:
1. In Chapter 1, a review of the literature is undertaken on pornography exposure in
adolescents and young people and the effects it may have on them, both positive and
negative.
2. Chapter 1 also reviews the research on education programs and other interventions
designed to prevent or reduce some of the negative effects of pornography. Since there is
minimal evidence for interventions that reduce the negative effects of pornography, it is
proposed that a pilot program is designed and an interventional study conducted.
3. In Chapter 2, consideration is given to how a theoretical framework may be developed to
instruct what key potential negative effects and interventional techniques should be
addressed by the program. The resulting proposal is a methodology that categorises key
negative effects into three broad domains: how pornography 1. affects the user; 2.
relationships; and 3. society. Additionally, 3 interventional strategies are nominated to
reduce those effects: 1. didactic education; 2. peer-to-peer engagement; and 3. parental
engagement. Consideration is also given to the school-based context for implementing a
program.
4. Chapters 3 and 4 describe a preliminary project where a baseline survey is designed,
validated and analysed amongst 746 year 10 students to assess changes in knowledge,
attitudes and behaviours. The survey combines elements about exposure prevalence, key
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predictor factors that influence pornography engagement, and measurable outcome factors.
The resulting analysis gives rise to further considerations about the relationships between
pornography exposure, social media behaviours, narcissism, and self-esteem, informing how
the survey should be expanded, and what content should go into the program.
5. In Chapters 5 and 6, a six-lesson school program is designed for year 10 students in
accordance with the Health and Physical Education (HPE) National Curriculum. Iterations of
the program were reviewed by teachers, parents and equivalent aged students, resulting in
a final program that was implemented in four independent schools in NSW. Qualitative
analysis of the program was performed with eight class teachers, describing the teaching
experience, what aspects appeared successful, plus areas that may have limited its
effectiveness.
6. In Chapters 7–9, quantitative analysis is performed between the baseline survey and the
post-intervention survey, providing various insights into the effectiveness of the program.
Chapter 7 is a preliminary analysis comparing the interventional data with the Chapter 4
survey data, to confirm that the intervention students were representative of the previous
cohort, from which the program’s design was based. Chapter 8 analyses the additional
research elements promoted from Chapter 4’s analysis, exploring the relationship between
self-promoting social media behaviours, narcissism, pornography exposure, and self-esteem.
Chapter 9 compares changes to the prevalence, predictor and outcome factors between pre-
and post-intervention surveys, providing insights into the effectiveness of the program,
whilst describing some challenges for achieving effective behaviour change.
Recommendations for further research follow this analysis.
1.1.1 Ethics approval
Approval for the baseline survey validation project was received from The University of Sydney
Human Research Ethics Committee (HREC) on 25 March 2018, Project no.: 2018/138.
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HREC approval to conduct the pilot program was received on 13 June 2019, Project no.: 2019/386.
1.1.2 Definitions
Two terms need to be defined from the outset: “pornography” and “young people”.
Pornography. In the literature, there are many terms used for pornography. Definitions range from
“Sexually Explicit Internet Materials” [1-9], “Sexually Explicit Media” [10], “Sexually Explicit Images”
[11], and “Pornography” itself. Most reviews limit these materials to pictures and videos found on
the internet [5, 11-13], because most pornography is currently accessed by the internet [14].
The word “pornography” comes from two ancient Greek words porneia (meaning “sexual
immorality”), and graphē (meaning “writing”) [15]. The iconic, universally cited 1964 definition of
pornography by United States Supreme Court Justice Potter Stewart “I know it when I see it” [16],
shows the difficulty in classifying subjective content, even though, in general, most people know
what is sexually arousing. Consistent with Owens [12], we will define pornography as any sexual
media intended to arouse (the Merriam-Webster Dictionary uses ‘causes sexual excitement’) [17]. In
the internet age this will commonly include explicit sexual pictures or videos, but also includes other
erotic materials, including sexual literature, erotic art, pop-music videos and even advertising. For
the purpose of this review, we will follow Flood’s lead, and declare ‘The terms pornographic and
sexually explicit are used interchangeably’, whilst also resisting moral judgement on these materials:
‘We do not assume that sexually explicit representations are necessarily offensive or harmful in
some way’ [13].
Young people. Many of the studies we review focus on adolescents in the age range of 10–17 [5],
but as old as 22 [12]. Additionally, there are significant variations of subject foci, with some studies
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only examining early, middle or older adolescents. In this review, we will use ‘adolescents’, ‘young
people’ and ‘youth’ interchangeably, following (for example) Springate [18].
1.1.3 Preliminary statistics
There have been many studies of varying qualities on the nature and prevalence of pornography use
by young people. The following provides a snapshot of the contemporary research:
a. 50–99% of adult men and 30–86% of women may regularly view pornography[19];
b. As many as 93% teen boys and 52% teen girls regularly watch porn [20];
c. The pornography industry is estimated to generate $12–$96 billion (USD) per annum, with
an estimate 78 billion page views per year (as of 2014) [21];
d. A 2017 Australian study found that the average first-time viewing age was 13 for boys, and
16 for girls. This study also found that 94% of men and 48% of women watch porn more than
once a month. 92% of users accessed their pornography over the internet (38% of users
viewed porn on their mobile phone, whilst 54% viewed on their computer) [22].
1.2 Literature Review Research Method
1.2.1 Data search method
The method for obtaining data for this literature review followed a quasi-systematic review process.
Two reasons that prevented this review from being formally ‘systematic’ were: 1. it became
apparent that many systematic reviews had already been conducted. For example, there have been
at least 65 empirical articles reviewing the impact of pornography on adolescents [5] — which is a
foundational element of this thesis. It was unnecessary to repeat such work. 2. on the other main
topics related to this thesis: the evaluation of education programs designed to address the negative
effects of pornography exposure; the development of assessment tools to measure an interventions
4
effectiveness; and other known methods for reducing the negative impact of pornography on
adolescents — a search of the literature yielded an inadequate number of studies for inclusion in a
systematic review. Thus, as outlined below, the process for reviewing the literature began with
similar process to a standard systematic review, but quickly developed into more ad hoc,
investigative methods for data collection.
The review of the literature was from January 1980 to December 2017, with 31 Dec 2017 being the
cut-off for peer-reviewed data.
1.2.2 Data search order
The sequence of journal/data lookup was:
a.
b. Database search using Medline, Embase, Cochrane, Web of Science
c. Google Scholar
d. Detailed search of journal bibliographies
e. General Google search, and ad-hoc scour of websites
f. The criteria for inclusion was broad, where studies that related to the effects of pornography
on young people and/or adults within their social context, and interventions or
methodologies related to reducing negative effects from pornography or improving
problematic adolescent behaviours, were included.
1.2.3 Data search key words
The initial database search combinations were:
a. pornography (OR sexually explicit materials OR sexually explicit media) AND adolescent
(OR young OR teenager)
b. pornography (OR sexually explicit materials OR sexually explicit media) AND effects
(OR impact OR health)
5
c. For interventions: pornography (OR sexually explicit materials OR sexually explicit media)
AND education program (OR intervention OR school-based program OR therapy OR
recovery program)
Other ad hoc terms used in the search engines included: SEIM (sexually explicit internet materials),
internet pornography, computer addiction, internet addictive behaviours, and problematic internet
behaviours.
1.2.4 Limitations to search methodology
Early in the research process, it became evident that a much wider search for data would be
required. This was because:
a. Many newer journals related to this project weren’t being captured by the above database
search process, including a few sexuality education program studies, neurological studies,
and broader studies on adolescent interventions aimed at broader problematic internet
behaviours or undesirable compulsive behaviours.
b. Some searches found identical studies.
c. Ad hoc use of Google scholar and Google searches were found to be useful, providing a
range of additional papers.
d. Some useful studies were only found from community-run websites, which although
themselves not scientific, had collated some peer-reviewed studies from China and other
non-Western countries which were not referenced anywhere else.
e. After eliminating the identical studies, approximately 350 unique articles were found
through this process.
After analysing and assessing the relevance of these articles for inclusion, 121 were incorporated
into this literature review chapter.
6
1.3 General Analysis of Research Data
Although many of the studies will receive individual analysis and critiquing in the body of this
chapter, the following section lays out the general analysis of study type and design of the 121 cited
articles. The quality, reliability, strengths and weaknesses are amplified when examined en masse.
1.3.1 Analysis of data sources
A breakdown of the article sources listed is found in Table 1.1, with peer-reviewed journals
comprising the bulk of data. These data were then sorted into study-type in Table 1.2, where the
first major weakness of the past research is revealed, namely that most studies are cross-sectional,
which comes with some limitations (discussed below). The systematic reviews, selected for this
chapter, also rely primarily on cross-sectional studies, as described by Valkenburg [5]. Lastly, a
further analysis of the respective sample sizes, by study type, is found in Table 1.3.
Table 1.1
Study Source Journal (Peer reviewed)* 106 Book [21, 23, 24] 3 Article/Report [25-27] 3 Education Program [26, 28-32] 6 Dissertation [25] 2 Total 120 Note: This is the total number of unique citations for this literature review. The six education programs did not contribute to the data analysis of the effects of pornography-exposure but are included for interest. * Some important peer-review journals include Owens [12], Peter and Valkenburg [5], Flood [11], Hald [19], and Bloom[33].
Table 1.2
Study Type Systematic Review 37 Cross-Sectional (CT) 45 Meta-Analysis 2 Randomised Control Trial (RCT) 8 Controlled Trial 3 Interventional 8 Longitudinal 10 Qualitative 1 Total 114 Note: Cross-sectional study designs account for most of the data, including the data analysed in the systematic reviews.
7
Table 1.3
Sample Size Range Study Type From To Median Average Cross-Sectional (CT) 16 29424 335.5 1631.3 Meta-Analysis 22 207 114.5 114.5 Randomised Control Trial (RCT) 22 1875 372.0 740.0 Controlled Trial 48 1950 92.0 696.7 Interventional 16 363 123.0 143.7 Longitudinal 123 2610 962.0 997.5 Qualitative 23 23 23.0 23.0 Note: Median figures are a better measure of the general sample size, since average sample size for cross-sectional, RCT and CT studies are heavily altered by outliers.
1.3.2 Cross-Sectional limitations and strengths
Approximately 40% of the studies are cross-sectional by design. A limitation to cross-sectional
studies is they only describe correlations between factors, but not cause and effect. Without some
form of intervention, it is not possible to confidently conclude why the correlations exist.
Furthermore, most of these studies depend on self-reporting instruments to gather data. This is true
for all the other interventional and control trials in this review. This self-report bias is openly
recognised as a limitation by most of the authors. It is worth noting Brener’s view here, that studies
have shown that confidential and anonymous self-report surveys are best suited for sensitive
matters (e.g. sexuality) with adolescents [34], and where there are a lot of questions within the
survey [35].
Other limitations mentioned in many of these studies include smaller sample sizes, particularly in the
case of the relatively new frontier research area of neurological studies (ranging from 19-66
subjects) [9, 36-41].
There are discrepancies between how questions are defined and put. Some studies do not specify
frequency of pornography viewing, while others do not differentiate between deliberate or
accidental viewing, why the viewing happened, or indeed what pornography is. As Valkenburg notes,
the measures and instruments in studies are not standardised, making comparative analysis difficult 8
[5]. Studies correlating pornography viewing and religion often fail to specify what religions are engaged in [42-44]. Some recruits are exclusively from more sexually permissive countries [1, 4, 45], whilst others are from conservative regions [46-48].
Many of the studies have self-selection bias—like Harakeh [49], where teens filled out surveys in front of parents—or selection bias limitations, where subjects were recruited by campus advertisements or from limited pools (e.g. Evans-DeCicco [50], Rasmussen [51], and Wilt [52]). Many are not generalisable, as they are from very specific locations (e.g. Grubbs [44], Siomos [53], and
Mechelmans [54]) or comprise non-representative ages (e.g. non-adolescents in Seok [40], Floros
[55]), or only one gender (e.g. Voon [56], Resch [57]). Additionally, there were widespread inconsistencies in the questions and instruments (e.g. Hald [58], Picone [25]), including the definitions of pornography viewing (including Patterson [59], Perry[42], and Luder [60]), and standardised mental health factors (Lim [22], Fernandez [61]).
However, there are strengths from these cross-sectional studies. Many used larger sample sizes, unlike the interventional and controlled trials, where the higher statistical power provides more stable findings. The high number of cross-sectional studies, the results of which generally concur, also has contributed to a consensus that exposure to pornography correlates with negative effects.
An example of this is the regular observation that a person’s viewing-frequency correlates with increased sexual objectification of women [8, 62].
The strongest cross-sectional studies, based on the sample size, generalisability of subjects, and standardised questions, are Stanley [63], Peter and Valkenburg [4, 8], and Hald [45]. Even then, limitations still exist, especially with subjects from the Netherlands, where the society is regarded as more sexually permissive, in contrast to the other countries [4, 8, 45].
9
1.3.3 Longitudinal, interventional and controlled trial limitations and strengths
The longitudinal studies generally involved self-report surveys of adolescents over 12- to 36-month
periods, examining changes in behaviours and attitudes. The studies by Doornwaard [1, 3], and Peter
and Valkenburg [7, 8], are strengthened by their larger sample sizes, but are limited by the minimal
measures defining pornography and their lack of an intervention. Peter and Valkenburg make the
point that there are difficulties in designing interventional studies for adolescent populations,
especially because of ethical concerns about exposing them to harm [7].
Brown’s studies examined teenagers using surveys two years apart, but they were conducted in a
period prior to the handheld device and broadband internet (2006 to 2009). The digital landscape
for teenagers has rapidly changed in that time. Ybarra’s 2011 study on pornography and sexual
aggression is quite strong, in that it has three waves of surveys, (12 and 24 months after baseline),
with much higher sample sizes (1588 at start, and 1155 by third wave), and recruited a broad range
of computer-literate teenagers [64].
The interventional studies introduce the dimension of causality and offer additional strengths to this
broader literature analysis. However, only four of the eight studies (Wright [62] , Fernandez [61], Yeo
[65], and Negash [66]) relate to pornography exposure. The others are examples about either school
programs or broader behavioural addiction programs. None of the pornography-themed
interventional studies utilised randomised subject selection or control groups. They are all non-
generalisable, have relatively small sample sizes, and depend on self-report surveys. The three non-
randomised control studies [47, 67, 68] do not relate directly to pornography exposure. However,
despite these limitations, their findings provide direction for further research, while presenting
potential models for future interventions.
10
The randomised controlled trials (RCT) studies included in this review, while generally regarded as
the most robust and reliable study design, do not describe how pornography affects adolescents, or
how these effects may be mitigated. Of the eight RCTs listed in Table 1.2, five relate to school-based
education interventions addressing other topics, including: drugs and alcohol; teen pregnancies;
anxiety; and physical wellbeing. Although not entirely relevant to this study, because they do not
relate directly to sexualised media or pornography, they are helpful references for developing
general school-based interventions. Three studies focus on aspects of exposure to sexualised media
[69-71], but they are not robust studies as they have small sample sizes (28–152), and selection bias
limitations (volunteers responding to advertisements), and adult-only subjects. Thus, these RCTs are
not easily generalisable.
1.3.4 Conclusion
This analysis of the literature shows a reliance on cross-sectional studies, which lack many
standardised elements, including recruitment methods, questions, subject profiles, and theoretical
frameworks. They do not describe causation, but at least combine to provide an emerging picture of
how sexualised media is shaping adolescent behaviours and attitudes worldwide. There is a heavy
weighting of studies examining the impact of pornography exposure on adolescents, but there is
only one [71] study aimed explicitly at reducing any negative effects.
1.4 The Effects of Pornography on Young People
There have been at least 65 empirical articles reviewing the impact of pornography on adolescents
[5]. The most recent and comprehensive systematic reviews are by Owens [12], Peter and
Valkenburg [5], Flood [11], Hald [19], and Bloom[33]. Most reviews are concerned with a post-
internet era, between 1995 and 2015, where pornography access has rapidly expanded, aided by
rapid technology growth, providing unprecedented access to content by young people. Studies into
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pornography’s effects on adolescents are but a small part of a wider body of literature. Most studies
have involved adults, because they are more accessible. The sheer sensitivity of sexual studies, the
various ethical risks in exposing young people to sexual content, and other limitations in accessing
and studying adolescents (limited exposure due to age), explain why there are comparably fewer
studies to explore. This review will, at times, include adult studies alongside adolescent ones,
especially when related to long-term exposure.
This literature review will categorise the (various) effects of pornography into three broad areas: 1.
personal effects; 2. relational effects; and 3. social effects. Although this is a logical way to cover the
content, no review is consistent in how to arrange and describe these effects. Most empirical studies
focus on the personal effects of pornography on the users, with some studies exploring how broader
sexualised and pornified culture effects social attitudes and behaviours. But the breadth of possible
effects reaches far and wide, including longitudinally. Thus, the categories of personal, relational and
social can encompass all studies.
1.4.1 Positive personal effects of pornography
Some literature suggests that pornography exposure can have positive effects, or at least effects
that are not negative. Pornography viewing has been positively associated with: stronger
relationships, increasing a couples’ desire to be with each other [72]; better sexual understanding
and practice; providing a recreational sexual outlet or a buffer against sexual assaults; and having
therapeutic benefits for common sexological dysfunctions [19]. Some claim there is an educative
benefit from viewing pornography to learn about sex, including new techniques, even if this may not
result in better sexual experiences [73].
Other studies suggest pornography improves positive attitudes towards women, having no
correlation with sexual aggression, rape culture, or a contribution to relationship breakdown [74].
12
Rasmussen found no association between pornography and committing violent harm [75].
Diamond concluded that pornography had no negative social effect on sex-related crimes and
child sexual abuse. Contrarily, those countries with relaxed pornography laws had a decline in
these incidences [76]. One analysis of the widely consulted 2002 Swiss Multicenter Adolescent
Survey on Health concluded that ‘pornography exposure is not associated with risky sexual
behaviour’ [60]. Prause concluded that there was no association with pornography and riskier
behaviour, and that to describe pornography use as ‘addictive’ was not empirically valid [72].
These studies have limitations. Staley’s study was of a small cross-sectional study of 44 adult
couples, and Rothman’s sample size was only 23 [73]. Luder’s [60] analysis of risky sexual behaviour
from the 2002 Swiss Multicenter Adolescent Survey on Health was limited by the condition that for
inclusion in the analysis, the students (with an average age < 18) needed to have had sexual
intercourse, yet fails to account for attitudes, intentions or desires. Furthermore, Diamond [74],
Rasmussen [75], and Hald [77] draw their conclusions from reviews of predominantly cross-sectional
studies, which lack standardised questions, uniform subjects, and research where study designs did
not explicitly target the question of positive effects from pornography.
Overall the evidence for the positive effects of pornography is sparse compared with the larger
volume of research associating pornography with negative effects.
1.4.2 Negative personal effects of pornography
1.4.2.1 Objectification, sexual aggression, and negative gender attitudes
Pornography exposure has been associated with objectification attitudes and increased sexual
aggression [6, 24, 64, 78, 79]. The type of pornography viewed (violent or non-violent) has little
effect on the degree of violent tolerance found in users (verbal aggression is more affected than
physical aggression, but not significantly different) [79].
13
Regular viewers of pornography are inclined to hold negative gender attitudes [6, 58, 63] and
commit sexual harassment [80].
Wright’s meta-analysis suggest that increased sexual aggression occurs in both males and females
after prolonged exposure [79]. A belief that sexual aggression is a precursor to ‘rape training’ and
domestic violence, is amplified by the availability of aggression-themed pornography. A study of 304
scenes from a random sample of the top 275 selling adult movies in 2005 described the level of
violence in contemporary pornography. It showed that 88% of scenes contained physical violence
(including choking, spanking, gagging, slapping, and hair-pulling); 49% contained verbal violence;
94% of the recipients of violence were women; and 95% of the violence was received neutrally or
with pleasure [81].
Acceptance of victimisation by female users increases over time, with exposure to predominantly
sexually aggressive pornography (against women) increasing a female’s normalising of such
behaviour [80].
1.4.2.2 Mental Health and Behaviour changes
A range of mental health difficulties has been described in association with pornography viewing:
depression, and reduced self-esteem [2, 82]; increased sexual uncertainty [4] and sexual insecurity
[12]; and anxiety accompany prolonged use. Doornwaard showed a relationship between
psychological wellbeing (lower levels of self-esteem) and excessive sexual interest as predictors of
compulsive porn use [2].
In contrast to the work of Rothman [73] (cited in 1.4.1), pornography is described as a poor sex
educator [11]. Increased exposure to pornography positively correlates with increased sexual
14
uncertainty and confused sexual belief [4, 12], as well as increased unrealistic attitudes about sex,
including altering the user’s sense of sexual realism [7, 12].
Academic outcomes for adolescents are poorer in pornography users [83]. Two experimental studies
by Laier suggested memory retention and decision making are compromised by pornography use
[69, 70]. These studies were of very short duration – where subjects were shown some pornography
images, then immediately given memory and cognitive processing tests. The sample sizes were small
(n=28, 82), and these studies did not assess any longer-term neurological change or additional
impacts of the exposure.
Other studies, however, suggest that behavioural changes may occur from prolonged exposure. This
includes increases in acting out [84], casual sex [4, 7, 62], earlier first-time sexual activity [78],
sexually permissive attitudes [12], and sexual sensation seeking[45, 85]. Additionally, general
increases in risky behaviour [45, 78], including sexting and alcohol consumption have been found
[86]. There is also evidence of increased sexual preoccupation, [8, 12, 87], and reduced capacity to
delay gratification [12, 66, 88-90]. Since these studies are predominately cross-sectional, there is no
sure way of describing causality, nor are confounding variables accounted for.
1.4.3 Neurological effects
A wave of recent scholarship has emerged on the relationship between compulsive pornography use
and its neurological impact, with one source citing 37 neurological studies and 13 literature reviews
[91]. These studies have not involved teenagers, since they have often involved exposing subjects to
explicit visual cues, a process most research centres would regard as unethical for non-adults. The
evidence of these studies show that regular pornography use correlates with real change to the
brain, and supports the view that compulsive pornography-use fits the behavioural addiction models
of similar DSM-5 disorders like Internet Gaming Disorders [92].
15
Voon et al. found that compulsive pornography users (compulsive sexual behaviour (CSB)) had heightened reactions to sexual cues in the dorsal anterior cingulate, ventral striatum and amygdala, areas of the brain generally associated with sexual desire/craving. They also found that these same subjects had no increase in ‘liking’ sexual activity compared to non-users, concluding that this brain behaviour was consistent with drug addictions [56].
Another study from Voon et al. assessed cue-reactivity through attentional bias in compulsive pornography users, concluding that there were ‘possible overlaps with enhanced attentional bias observed in studies of drug cues in disorders of addictions’. They dovetailed these results with their previous study concluding their evidence provides ‘support for incentive motivation theories of addiction underlying the aberrant response to sexual cues in CSB’ [54].
Schmidt et al. analysed 92 males, 23 of whom were compulsive pornography users, finding a significant reduction in the functional activity between the amygdala and the dorsolateral prefrontal cortex (DLPFC) compared to non-pornography users [39]. As Hilton summarises, the DLPFC is widely accepted as the instrument of cognitive control, and the functional activity between it and the amygdala is associated with a range of behaviours including emotion regulation, impulsivity, modulating negative emotions, as well as anxiety, depression and stress. This loss of the frontal control system, known by neuroscientists as the braking system, is well documented amongst patients with substance addictions like cocaine and methamphetamines, accompanied by observable reductions in brain volume [93].
Kuhn found that compulsive pornography users have losses in grey brain matter, in particular the right striatum, as well as reduced functioning of the left putamen — both of which mediate
16
cognition of various functions including executive controls, compared to healthy subjects — similar
to that of substance abusers [37].
One web-based resource [94] summarises these combined studies suggesting that pornography
affects the brain in three ways:
a. sensitisation — where motivational and reward circuits become hypersensitive to memory
cues;
b. desensitisation —where the brain becomes less sensitive to pleasure;
c. and hypofrontality — where the increased dysfunction between the prefrontal cortex and
limbic system results in reduced impulse control, and increased cravings.
1.4.4 Is compulsive pornography viewing a form of addictive behaviour?
Regarding addiction, there has been (general) reticence in classifying problematic or compulsive
pornography use as ‘addictive’. In part that has been due to a classical definition of addiction as
pertaining to psychoactive substances like alcohol, opiates and cocaine [95], as well as the research
frontier of pornography and neurology being relatively new. However, in 2011 the American Society
of Addiction Medicine (ASAM) redefined addiction to include other broader behavioural influences
on the brains reward, motivation and reward circuitry. In 2013 the American Psychiatric Association
(APA) added Internet Gaming Disorder as a behavioural addiction in its Diagnostic and Statistical
Manual (DSM-5). Internet pornography was not included as an addiction. Love makes the compelling
argument that compulsive internet pornography use fits into the addiction framework, sharing
similar processes as substance addictions [95]. This conclusion is consistent with Voon [9, 54] and
Kühn [37].
17
The APA’s reticence to include other internet-related behaviours, including pornography use, in their
DSM-5 publication, is based on the perceived lack of rigorous research, stating that “future research on other excessive uses of the Internet would need to follow similar guidelines as suggested herein discovered” [92]. Schmidt’s study supports this reservation. He observed neurological differences between substance and behavioural addicts. The amygdala grey matter in brains of compulsive pornography users was significantly greater, rather than smaller compared with controls. This is in contrast to Kuhn’s work (79). However, Schmidt also concludes that there is impaired functional connectivity between prefrontal control regulatory and limbic regions, consistent with substance abusers [39]. He also cautions for more research, citing limitations in the currently available studies.
There are also limitations in Voon and Kühn’s studies [37, 54, 56], with relatively small sample sizes, use of only male subjects, and cross-sectional designs. Longitudinal research would help answer the case for or against the addiction model.
Others are also reticent to define persistent pornography use as addictive behaviour. Grubbs, writing about validating compulsive pornography use [96] shifted the language from pornography addiction to ‘perceived’ pornography addiction. This phrase quickly became adapted by others, relegating pornography addiction to mere subjectivity. For example, Leonhardt’s ‘perception of pornography addiction’ scale [97] cites Grubbs, claiming that subjective self-report assessments (particularly in the case of religiosity, which was Grubb’s main interest) do not define addiction, even if better at predicting levels of psychological stress compared with previous objective measures [97]. The irony is that Leonhardt’s source for his scale in a separate study, the Sexual Compulsivity Scale, was already recognised as an objective measure of compulsivity. In contrast, a recent critique by
Fernandez of the ‘perceived addiction’ language, has robustly defended Grubb’s original language, showing that his assessment tools clearly assess real compulsivity, not merely perceived compulsivity [61]. We now know that the brain has neuroplastic properties, including the ability to adapt and recover in some circumstances from injuries and disorders. Doidge, a leader in this field,
18
has suggested that partial to complete cues can be constructed under certain circumstances. This is
relevant for the study of how pornography may affect the brain. While it has been shown (e.g.
Voon [56]) that the brain can negatively adapt to regular neurological stimulation, Doidge suggests
that intentional therapy may be able to reverse the effects of pornography – either in creating
alternative neural pathways for other activities, as well as reducing the degree of reactivity to sexual
cues [98]. This suggests that techniques such as cognitive behavioural therapy may be useful in
reversing the neurological effects of long-term pornography use on compulsive users.
In summary, there is evidence is that excessive long-term pornography exposure may impact the
brain, particularly the limbic system and DLPFC, in ways consistent with substance addictions, and
interventions seeking to reduce the effects of pornography on young people may benefit from
techniques use in addictive behaviour therapy. However, as this is a new field, mainly using cross-
sectional data, rigorously evaluated intervention studies will be needed to see if this is so.
1.4.5 Relational effects of pornography
As already noted (1.4.1), some studies suggest that pornography is helpful for relationships while
others suggest it has negative effects on present and future relationships. This section examines the
research investigating the negative effects of pornography on relationships.
In a 2014 survey by Parker et al., 77% of young women said ‘pornography has led to pressure on girls
or young women to look a certain way’, and 75% said ‘pornography has led to pressure on girls and
young women to act a certain way’ [99].
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Pornography may contribute to erectile dysfunction disorder. As many as 50% of male pornography users experience diminished libido or erectile function in real relationships [9, 89]. Pornography use appears to corrupt arousal mechanisms in some users, reducing the chance of enjoying physical sex with one partner, even when there is no trouble being sexually aroused to pornographic triggers
[56].
There is evidence that pornography may contribute to dishonesty, mistrust and insecurity within a relationship. Resch surveyed 340 heterosexual women, who reported that where couples are both non-users of pornography, they have higher sexual and relational satisfaction. In contrast, when one or both partners use porn, there is lower sexual satisfaction [57]. Newstrom found that when a women discovers the partner’s use of pornography, this causes trauma akin to cheating, resulting in lower self-esteem and a deeply altered perception of the character and trustworthiness of the partner [100]. As honesty is a predictor of relationship satisfaction amongst women, secrecy about pornography use, followed by discovery puts a wedge between the quest for relationship joy and realised satisfaction [57].
Pornography may contribute to adultery. Gwimm et al. found that users are inclined to perceive alternative romantic relationships as better, and thus seek them out [101]. A 2014 survey of 350 members of the American Academy of Matrimonial Lawyers found 56% of divorces were related to
‘Obsessive interest in pornographic sites’ [102]. Rasmussen concluded that pornography leads to the development of sexual scripts that increase the likelihood of infidelity and unfair comparisons between real-life partners and those viewed in pornography, including perspectives that those outside the relationship are better suited for sexual fulfilment [75].
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1.4.6 The Social effects
It has been suggested that pornography is a private matter which is acceptable if it does not affect
anyone else [103]. The following literature analysis contends that pornography is not private, with
implications on many across society. No young person can adequately assess the effects of
pornography without an understanding of pornography production.
1.4.6.1 Is pornography production exploitative and harmful?
The educative pros and cons of pornography use by adolescents has already been discussed. The
following analysis seeks to describe what happens behind the camera. This may contribute to how a
person can understand their sexual shaping from pornography and assist educators in developing
interventions for addressing the negative effects of pornography.
The pornography ‘industry’ is big business for producers, distributors, advertisers, technology
producers, and service providers. It is difficult to ascertain the annual worldwide income from
pornography since there is little transparency from producers and distributors about income. Some
worldwide revenue estimations lie between $12 billion and $96 billion (USD) per annum [21].
The pornography industry is poorly regulated. Even in its most heavily regulated region for
production, California, there is an absence of basic worker entitlements including health insurance,
sick-leave, annual-leave, job redeployment services, guaranteed employment, minimum wages, non-
compulsion to use condoms [21]. It is not an industry in the conventional sense of abiding by
common industrial laws. According to Dines, the pornography industry generally resists any
government regulation that cuts into profit. For example, lobby groups on behalf of the pornography
industry aggressively opposed the ‘Measure B’ County of Los Angeles Safer Sex in the Adult Film
Industry Act 2012, which proposed that male actors wear condoms, since viewers don’t want to see
21 them [104]. Only the most esteemed performers in safer regions like California are awarded the protection of negotiations and terms prior to shooting, but most are not paid well [21] .
Performers are generally exploited, disadvantaged and socially atypical. For example, pornography performers have higher rates of depression, anxiety, child sexual abuse, living in poverty, STIs, substance abuse, earlier age for first-time sexual activity, and are more likely to be in bisexual or same-sex relationships [105-107].
Performers regularly report doing things against their will. They report being coerced, manipulated, deceived and threatened [108].
There is a link between pornography and prostitution. Pornography production, and the participating performers, have well documented links with prostitution [50, 106]. By definition, prostitution is the engagement of sexual activity for money. Pornography performers are a subset of prostitution and are vulnerable to the abuses and vulnerabilities associated with prostitution. These include financial exploitation [105], human trafficking [109, 110], and child-sexual abuse [105]. Some children and women who are trafficked and prostituted are used for the production of pornography without consent [43].
Pornography leaves a permanent record. Porn enslaves the performers to their past, placing them on perpetual display. Even when a performer chooses to leave the ‘industry’, they have no control over the ongoing distribution of their activities. It can be argued they are defined by, even controlled by, the stigma of the past [21].
22
1.4.6.2 Pornography and popular culture
Popular culture is in constant step with pornography. Recent popular television shows like Game of
Thrones or Orange is the New Black, or advertisements like the UltraTune series, portray sexual
activity not broadcasted 25 years ago with a steady increase of sexual content over time [111]. The
UltraTune commercials, the most complained about Australian commercials in 2017 due to their
highly sexualised content (including themes of bondage) were not restricted by Australia’s
Advertising Standards Board [112], suggesting that over time, mainstream media has normalised
sexual themes previously only found in pornography.
Pornography culture can influences social behaviour with evidence that prevalent exposure to
sexualised mass media (movies, advertising, tv, and magazines) accelerates sexual activity and early
first-time intercourse in young people [113].
Porn culture sexualises young girls. As pornography infiltrates and influences mainstream media,
there is evidence of the growing sexualisation of young girls in our society [114]. Researchers
suggest that the marketing strategy of ‘age compression’, where products are marketed to lower
ages, reduces a girl’s ‘space for action’ (i.e. how their femininity and beauty is re-defined through
overt sexualised media exposure) [115]. This, combined with the other evidence of the growing
pressure on females to look and behave more sexually [114], means that it is difficult to divorce
private personal pornography consumption from the wider influence on society, as shown when
activists challenged controversial Target ads for pre-teen clothing in 2012 [116].
Pornography can increase objectification culture. As already observed (1.4.2), pornography users
adapt objectification attitudes towards women [6, 62] over time, including aggressive attitudes [79],
while normalising the acceptance of female victimisation amongst girls and women[80]. This
predominately, but not exclusively, applies to males, the main consumers of pornography.
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1.4.6.3 Pornography and Religion
There is a body of research on the relationship between pornography and spiritual and religious
identity. Pornography use by actively religious people is accompanied by higher levels of guilt and
unhappiness than in the general population [59]. Religious pornography users have reduced
spiritual coping, increased spiritual and relational isolation [25], and increased spiritual struggles
[44]. Perceived addiction to pornography has been shown to negatively affects the user’s self-
esteem, and contributes to more anger [52], whilst reducing their general religious and spiritual
health [44]. Conversely, people who have a more active spirituality (for example, pray more) were
less likely to watch pornography [25].
One study found that 75% of youth pastors and 64% of senior pastors reported that personal use of
pornography has negatively impacted their ministry at some time [43]. Religious people are more
likely to perceive their pornography use as addictive, and negative, compared to the general
population [117].
Religious parents who use pornography spend less time discussing and reading religious materials
with their children compared with religious parents who do not use pornography. Fathers are the
primary agents of these outcomes [42, 118].
Pornography use can negatively affect the spiritual health of religious relationships. In relationships
where one or both partners regularly view pornography, higher levels of relationship anxiety were
experienced [97]. On average, relationships with (at least) one pornography user pray less often
together [119].
24
In summary, pornography appears to influence the spiritual dimension of users, relationships and
families although these findings are from mostly cross-sectional studies that have limitations (1.3.2).
Longitudinal research is required these observations are to be validated.
1.4.7 Summary of the Effects of Pornography on Young People
Overall, there is a large body of literature on how pornography affects young people personally,
relationally, socially, and spiritually — in the context of their place in sexualised society. The weight
of evidence falls on the side of pornography having notable negative effects, but with the heavy
reliance on cross-sectional studies, there remains questions about causation.
Of relevance to young consumers of pornography is how their private consumption connects with
the other dimensions of relationships and social effects. For example, would they be ethically
content to associate with, and even enable, the abuse of vulnerable people for personal pleasure? It
may be that they are ignorant of the wider relationships between pornography and societal effects,
and hence may be untroubled. However, when provided with education on the connectedness of
private use and public outcomes, they may take a different view. Would education moderate a
feeling of regret, promoting a desire for social accountability about how pornography may harm
others? And would young people desire to reduce the prevalence, use of, and approval of
pornography in their own and society’s life?
These are but some of the questions arising out of the analysis of how pornography affects young
people, to be explored further in this study after examining the research on how people have
attempted to reduce, mitigate and prevent these perceived negative effects.
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1.5 Suggestions for reducing the negative effects of pornography
The belief that pornography negatively effects young people is not new, yet there is minimal
evidence that efforts to reduce these effects exist. This section explores the evidence for reducing
the negative effects of pornography.
1.5.1 Education interventions1
1.5.1.1 Pornography-related curriculum
There are only a few internationally published pornography education interventions, a number of
which are Australian. These include In The Picture [28]; Porn — what you should know [29]; Sexting:
social and legal consequences [26]; We Need to Talk About Pornography [30]; Catching On Later [31];
and Building Respectful Relationships [32]. These are briefly reviewed in Appendix A. After
conducting a search of the literature, we have not found any studies assessing the effectiveness of
these curricula. There is no description of any theoretical basis behind the content in the programs
in Appendix A. The only consistent themes addressed by these curricula are sexting, objectification
culture, and unrealistic sexual expectations. There is no reference to compulsivity and neurological
harms, nor the long-term effects on relationships and society. There is a gap in the literature for a
holistic curriculum that targets the negative effects discussed in this chapter.
A search for other empirically evaluated interventions (pornography-related) produced only one
randomised controlled trial performed on male undergraduates to evaluate the effect of a
computer-based education intervention. Results indicated this intervention could reduce certain
negative attitudes associated with violent and extreme pornography, reducing attraction to sexual
aggression, whilst improving attitudes that disapproved of violence in pornography [71]. However,
this intervention is not reproducible in a school environment, since subjects were shown clips of
1 The term “intervention” has different meanings in different fields. For the purpose of this paper, the intervention is any new curriculum built from the theory and evidence presented herein. Thus “intervention” and “curriculum” are used interchangeably. 26
violent pornography as part of the education. Additionally, the study was not generalisable since the
subjects were adults, male, and volunteers with self-confessed pornography problems.
Thus, there is little guidance from the current pornography-specific programs in circulation. An
alternative source for knowledge on effective education interventions is to examine the
effectiveness of general internet-use curriculum, sex-education interventions; and substance abuse
education interventions.
1.5.1.2 Other education studies for avoidance and reduction of undesirable behaviours
Although there has been little research on interventions for internet-related behaviours, one
program produced a positive effect on reducing internet gaming addictions and general stress in
adolescents. This study tested the effectiveness of empowerment education program for reducing
internet gaming addiction behaviours and was based on ‘Freire's Empowerment Education Model’,
as performed by Joo [67].
In a review of teenage pregnancy rates in the UK, Skinner concluded that the education component
of the UK Teenage Pregnancy Strategy was instrumental in the high reduction in pregnancy rates
(from 2000–13). Although this strategy was multiple-pronged, including wide coordination amongst
government and community bodies, media campaigns, and improved support for pregnant
teenagers, a central element behind its success was the high-quality school-based sex and
relationship education [27].
Sex education interventions have had some degree of positive outcomes. For example, there is
evidence that safe-sex education increases usage of contraceptives [120]. On the question of
whether exposing young people to pornography education will encourage riskier, more harmful
behaviour, one meta-analysis found that of 47 studies, 25 reported no change in sexual activity or
27
pregnancy rates, 17 reported reduced sexual activity, pregnancies and STI rates, whilst only three
reported an increase in sexual behaviours [121]. In Kirby’s literature review of the effect of sex
education and school-based sex-clinics, there was no evidence that such programs increased riskier
sexual behaviour, rather that most common programs helped ‘delay sex, reduce the frequency of
sex, increase condom or contraceptive use, or decrease pregnancy and childbearing’ [122].
Some peer-run education interventions have been studied, which we discuss below in the peer-to-
peer relationships section [123], [124], however they were limited in success.
1.5.1.3 General substance abuse curriculum
Moving beyond sexuality-themed programs, other broader education programs on reducing health-
related behaviours and attitudes are worth exploring, if only for methodological guidance. For
example, in a meta-analysis of the effectiveness of education strategies for reducing adolescent
smoking, Willemsen and Zwart found little long-lasting benefit from school-based education
programs alone, but when combined with other variables like restricted access, advertising ban,
higher cigarette prices, mass-media campaigns, there were successes in reducing long-term
adolescent smoking. This suggests a program may benefit from broader social engagement and
utilisation [125].
The mode of teaching appears to make a difference. A meta-analysis of 207 universal school-based
drug prevention programs found that interactive programs, which engage students and foster
‘development of interpersonal skills’ were found to be significantly effective, whilst non-interactive,
lecture style programs which merely disseminated information were found to be ineffective [126].
At the most general level, several education controlled-trials have found success in reducing
problematic adolescent behaviours whilst increasing relevant knowledge (e.g. alcohol [127], cyber-
28
bullying [128], drugs [129], anxiety and depression [65, 130]). Not all education interventions,
however, were successful (smoking [131], teen-pregnancies [132], physical education [133]). These
different outcomes reinforce the need for researchers to regularly assess a specific intervention
against clearly defined aims and outcomes, and not assume common education is effective or
transferable to a specific topic.
In summary, there is evidence that good education coupled with additional community supports,
may produce positive outcomes. Sex-education has, in general, not been associated with increased
riskier behaviours, but it may increase knowledge and reduce negative outcomes. In developing a
pornography-related school curriculum, these various adolescent education programs on sexuality,
health and addictive behaviours can serve as guides for its development and implementation.
1.5.2 Parental interventions
The volume of research exploring the relationship between parents and adolescent attitudes and
behaviour, particularly relating to pornography, sexuality and internet addictive behaviours, is
substantial. Parents are central to their teenager’s behaviour, and as young people develop and
mature, the nuances of parent-child relationship become pronounced, reinforcing the need for
ongoing parenting education for topics like pornography.
Rasmussen’s study of emerging young adults revealed significant correlations between
adolescent/parental relationships and pornography use. Specifically, when parents discussed
pornography, expressing negative opinions about it to their teenagers (called ‘negative active
mediation’), there was less pornography consumed in early adulthood [51]. Rasmussen also found
that when parents imposed strict rules on behaviour, like restricting access to the internet or
pornography, there was some long-term effect on emerging adult viewing habits [51].
29
Weber examined whether a teenager’s perception of autonomy, including from parental control, related to increased pornography use. This study found that subjects were more likely to use porn if they perceived to be under the control of parents [20]. Consistent with Rasmussen, Weber found that restrictive parental mediation (rules without communication) was not effective in reducing pornography [51]. However, Weber’s study should be taken with caution since he only included females (n = 143) who were non-porn consumers, whereas all male subjects (93%) were excluded because they were porn consumers [20]. Additionally, his questions about parental relationships were not specific to pornography or sexual behaviours, but rather general questions about the teenager’s sense of independence from parents.
A third study found that the perception of parental expectations amongst black teens in America had a stronger influence on their sexual activity than exposure to sexual content in popular media [113].
There is a range of youth internet addiction studies examining the relationships between parenting style and behaviour. For example, Ding found that adolescents with a perception that their parents both monitored their behaviour, whilst having interest in their welfare, would develop better self- care. This was because their parents showed active engagement and care. The outcome was a reduction of their general internet addiction [134]. Qin-Xue Liu found that multi-family group therapy sessions, where parental communication was facilitated, had significant positive effects on reducing an adolescent’s internet addictive behaviours [47]. And Jian Xu found a correlation between poor parental communication and a teenager’s development of internet addictions (in particular, poor mother-adolescent relationships lead to more problematic behaviours [135]).
Two additional studies from Greece looked at the relationship between parents and their teenager’s internet behaviours, including using pornography. They showed how different parenting models effected behaviour. The first study by Siomos [53] (cross-sectional, n = 2,000 teenagers) explored
30 how parental bonding and parental rules influenced addictive internet behaviours, with the following three conclusions: 1. families without preventative steps in accessing the internet had the highest rates of problematic internet behaviours; 2. parental bonding (including empathy, closeness, emotional warmth, and affection) was the most potent factor when seeing reduced addictive behaviours; 3. internet prevention-rules alone had minimal effect. The second study by Floros [55], on compulsive adolescent online gambling, found that teenagers with higher levels of perceived care, yet lower levels of perceived overprotection, had the lowest rates of compulsive behaviours, including internet pornography. Overprotective parents without care led to higher rates of compulsive behaviours
A study on adolescent smoking found that parents who were encouraging, and discussed the problems of smoking in a constructive and respectful manner, were the most successful in preventing their teenagers from smoking regardless of whether the parents were smokers or not
[49]. In an Australian study on adolescent alcohol usage, greater outcomes of abstinence and self- control occurred in family environments with active parental monitoring and rules on alcohol use. Of particular interest was the finding that abstinence increased when a father had closer emotional relations with their teen [136].
A meta-analysis of adolescent substance abuse found consistent support for the parent’s role in influencing the child’s behaviours. When parents had permissive attitudes, were substances users themselves, were relationally antagonistic or detached, their child had a higher chance of substance abuse. Conversely, parents with stronger communication skills, who had preventative behaviour strategies, including rules, and promoted an abstinence culture, contributed to lower levels of substance abuse [137].
31
These non-pornography studies correlate with both Rasmussen’s and Weber’s findings, showing that
parents who communicate regularly and respectfully, showing interest in their children, while
explaining the reasons for their boundaries, have the best chance of reducing problematic
behaviours in their teenagers. Overbearing, strict, controlling parents have a neutral to negative
impact on problematic behaviours.
When considering intervention models for reducing the effects of pornography on adolescents,
parental involvement is significant. Any new education curriculum should explore integrating
relational engagement between parent and child, including regular positive dialogue about a
parent’s own views and behaviours related to pornography. This could be through homework
activities, joint seminars, and take-home information. This may also require education of the
parents, who may be unaware of the variables involved in accessing and using pornography, or the
broader consequences that arise from pornography exposure. Education may include information
about pornography, technology, adolescent behaviour, and improving communication with
adolescents.
1.5.3 Peer to peer relationships
The adolescent’s attitude and behaviour to pornography can be mediated by their peers. A
distinction has been found between the influence of a teenager’s ‘perception’ about their peers’
pornography use, and the influence of what they actually know about their closer peer behaviours.
For example, Rasmussen found that when a teenager perceived that the wider peer group viewed
pornography or were positive towards pornography, it increased their likelihood of using porn
themselves [51]. However, if the teenager had specific knowledge about their closer peers’ attitudes
and usage of pornography, that knowledge would moderate usage. It would seem communication
between peers to describe their behaviour makes a difference.
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Weber also found that a youth’s perception of their peer’s engagement with porn influenced personal use. Unlike Rasmussen, he did not distinguish perception from reality. He observed that porn use was often integrated into group interaction, with his study showing about 25% of males and females watch or share with peers [20]. Pornography was frequently discussed among peers, especially by males (48% compared to 22% females), suggesting it was a socially desirable behaviour.
The more aware a young person was of their peer’s pornography use, the more likely they also would consume it [20].
Can peer influence be harnessed in a curriculum? In an older literature review exploring peer-to- peer participation in adolescent substance abuse education (1988), there were promising conclusions about the potential for peer-influenced behaviour change. It was suggested that when educations programs included a youth-to-youth approach, positive behaviours could result. More specifically, when peers critically engaged with the content through these methods, their ‘here and now’ thinking was challenged, improving personal and social skills, and inviting them to contribute to their solution-making [138]. Not all agree. One study on peer-led sexual health education, in this case on using condoms, found negligible effects from peer-led education for improving sexual outcomes for teenagers [68, 123]. Milburn’s meta-analysis also observed the general difficulty in using artificial environments for peer-influenced sexual education to simulate what is really a social process [124].
Overall, the literature suggests that there is a strong relationship between peer influence and personal behaviour, but primarily when related to peer culture and perceived beliefs. Peer-run education may or may not be effective, and is an area requiring further research. Reducing the gap between perception and reality, through increased dialogue with their peers, as well as mutual engagement during learning, may influence positive behaviour. Any education intervention seeking
33
to moderate the effects of pornography should involve strategic peer-to-peer communication and
activities, probably in the form of discussion groups and joint assignments.
1.5.4 Cognitive behavioural therapies and other responses to neurological harms
Considering the number of teenagers regularly using pornography, it raises the question of
compulsivity: if compulsive behaviour is present in teenagers, does this pose a risk of harm requiring
attention? And how may an intervention incorporate this?
A careful search of the literature, including Cochrane and PubMed, does not find any peer-reviewed
studies on successfully treating adolescents (or adults) for internet pornography addiction. There
are, however, numerous studies on treatment and recovery from other substance, behaviour, and
internet related addictions. These broader studies may provide some guidance.
Compulsivity and addictive behaviours are primarily neurological related. As discussed in Section 1,
there is a growing body of research connecting compulsive pornography use and neurological harms
akin to substance addition. The work of Voon et al. [56], Seok [40], and Brand [139] showed
heightened activity in the limbic system and reduced activity between it and the dorsolateral
prefrontal cortex. The aetiological significance possibly being: if excessive pornography use impaired
the cognitive control over the behaviour [23], then a case for exploring interventions that can
reverse these neurological changes is promising. A starting point would be observing similar
strategies that have been successful with substance addiction.
Cognitive behavioural therapies (CBT) have proven to be effective for adolescents with substance
abuse problems, and have been recommended as part of treating general internet-use-disorders
[140]. In a meta-analysis treating adolescent substance abuse, which included various randomised
trials, Waldron concluded that CBTs were very successful. Notably, group therapy was successful
34
[141]. Other common methods which were successful included ‘self-monitoring, avoidance of
stimulus cues, altering reinforcement contingencies and coping-skills training to manage and resist
urges to use’. In addition, other skills-focused interventions, mood regulation and relapse prevention
were regularly present in these studies [141]. Some clinical trials emphasised the effectiveness of
early family-based treatments, which is consistent with findings in the parental intervention section
above. Waldron did not conclude that CBT is the silver bullet, because not all adolescents found CBT
to be effective, however when faced with an adolescent’s problematic pornography use, CBTs
should be considered.
A study examining a similar therapeutic approach to CBT, called Acceptance and Commitment
Therapy (ACT), found promising results for treating people with problematic internet pornography
behaviours [142]. However, there were serious limitations to this study, including small sample size
(n = 6), subjects comprising only Caucasian males from one US city, no controls, and the instrument
was a self-reported survey.
A danger of integrating therapies like CBT or ACT in an adolescent-aimed education broad curriculum
is that it may not be done well. Such therapies are generally assigned to professional therapists.
However, if the content was prepared by CBT educators, and accompanied by sufficient teacher
training, or if trained therapists were included as part of the broader program for problematic
behaviours, there are opportunities to use CBTs or similar therapies to address compulsivity in
students.
1.5.5 The neurological and behavioural effects of Abstinence
Abstinence strategies, which may be a subset of CBTs, or stand alone, have been found to be
effective for reducing addictive behaviours. In one small addiction study on the effectiveness of a 12-
step style program of 127 adolescents, a positive effect on addictive behaviours was seen, in
35 particular for those with more severe symptoms [41]. In another study, the effect of dieting- abstinence on obesity, which is a recognised as a behavioural addiction in the DSM-5, led to a significant reduction in the white brain matter of obese patients. Prior to abstinence, obese patients had greater volumes of white matter compared to lean subjects [36]. In a study of recovering cocaine addicts, significant increases in the grey matter were detected after abstinence, compared to non-using control subjects. The grey matter found in the anterior cingulate, inferior frontal gyrus and insular cortex regions (critical to behavioural control) increased after 35 weeks of abstinence, with further growth in longer periods [143]. Notwithstanding that compulsive pornography use is yet to be defined as addictive, or that adolescents have experienced similar neurological effects of these wider addictive behaviours, the potential for similar benefits of abstinence could be researched.
Not all abstinence strategies have been successful. In a meta-analysis about programs designed to increase condom use and prevent STIs, the relative effectiveness of abstinence programs versus comprehensive sex education curriculum were compared. It was found that abstinence programs were overall unsuccessful in increasing condom use, delaying adolescent sexual activity, or reducing risky sexual activity, yet the comprehensive education programs had much greater success on increasing abstinence and safe sexual practices [144]. In slight contrast, Bennett’s meta-analysis of
16 randomised control studies in the USA found that some abstinence-only interventions had a positive effect on reducing teenage sexual behaviour and pregnancies. It was found that when combined with knowledge-imparting education programs, these ‘abstinence-plus’ programs saw improved outcomes in subjects (compared to controls), including knowledge about contraceptives
[145]. The evidence from Bennett’s conclusions is strong because he only reviewed longitudinal, randomised control trials – the gold standard of research.
In summary, there is a lack of education programs, therapies, and general research around the reduction of pornography-related behaviours and attitudes for adolescents. There are some
36
potentially comparable sexuality or substance-abuse programs, but even then, the research on what
is effective is inconsistent. There is a need for more research here, but the development of an
adolescent intervention should consider these additional studies when exploring effective ways to
reduce problematic behaviours. Parental and peer-to-peer engagement methodologies, behavioural
therapies, and potentially neurologically targeted therapies for serious compulsive behaviours
should be considered.
1.6 Chapter Summary
The research presents a largely negative picture of the effects of pornography on adolescents. This
may be because of underlying agendas of the researchers, or limitations from inconsistent study
designs and reliance on cross-sectional studies. However, the evidence of positive effects is slim.
These negative effects impact the user, including their attitudes, behaviours, and neurology. It
impacts relationships, and wider social spheres. Despite a small sample of school-based programs
addressing these negative effects, their lack of evidence-based content and empirical evaluation
justifies a study to address this gap in the research. Guidance may be obtained from other successful
education programs on sexuality, health and addictive behaviours. Additionally, interventions with
positive parental engagement, or strategic peer-to-peer communication and activities, may be
effective. At a clinical level, behavioural therapies that address compulsive behaviours may also be
effective.
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Chapter 2: Development of a Methodology
2.1 Introduction
Chapter 1 shows that there is a plethora of studies on how pornography may affect young people,
yet very little research on how any negative effects may be countered or reduced. The research
mostly portrays pornography as having negative effects on adolescents, with limited research
supporting any positive aspects. Of the studies that describe the effects of pornography, most have
limitations, predominantly their cross-sectional design. The studies on adverse effects provides
justification for conducting an interventional study exploring whether negative effects can be
reduced.
This chapter argues that a new intervention needs to be designed, because at present there is no
suitable one to use. We posit that the best context for conducting a larger scale study is in a school-
based context. We also examine why the current lack of theoretical frameworks produce difficulties
in advancing standardised studies and interventions on the interplay between pornography and
adolescents. Thus, the intervention proposed is preliminary, novel, and regarding theoretical
framework, hypothetical. The chapter presents the following points:
a. Why there are no sufficient theoretical frameworks to adopt for an intervention designed to
reduce a broader suite of negative effects, relegating this study to a preliminary pilot.
b. How the identifying and systematising of key constructs for an intervention can emerge from
the Chapter 1 categories of ‘personal’, ‘social’ and ‘relational’ categories.
c. What is required to place an intervention in a school-based educational framework.
This chapter serves as groundwork for the two major studies of this PhD, the design and validation of
a baseline survey, and the design and implementation of a school-based intervention.
45
About terminology: since this chapter proposes a school-based education program as the
intervention, the terms ‘intervention’, ‘program’, ‘pilot’, and ‘curriculum’ can be considered
interchangeable.
2.2 An Absence of a Theoretical Framework for the Interventional Study
The research cited in Chapter 1 has not described a theoretical framework, paradigm or precedent
sufficiently broad enough to govern the design of a pilot education program for exploring the
reduction of the negative effects of pornography. The majority of studies related to adolescent
exposure to pornography focus on identifying the effects but do not build their studies on any
theory, as observed by Peters and Valkenburg [1]. A smaller number do use some form of theory.
Peters and Valkenburg identified 12 different models in their extensive review: the media practice
model, the sexual behaviour sequence, social cognitive theory, the theory of reasoned action, social
bonding theory, uses and gratification theory, the hedonic-valence model, ego-identity-status
theory, consistency theories, social comparison theory, the sexual scripts approach, and cultivation
theory. Their review also observed “that a relatively large number of studies did not rely on
established theoretical frameworks” [1]. Amplifying this, Owen’s review concluded that there
remained a need for future research “that incorporates more sophisticated methodologies that
move beyond simple correlational analysis and cross-sectional designs” [2].
2.2.1 One Framework to Consider, the DSMM
Peters and Valkenburg advanced their own theoretical framework called the Differential
Susceptibility to Media Effects [3] Model (DSMM), which is the most definitive attempt to organise
and incorporate the body of research [1, 4]. As the main framework to encompass
adolescent/pornography research, it is worth considering whether it should inform the current
study. The DSMM incorporates ‘approaches, such as the media practice model, the sexual behaviour
sequence, and social cognitive theory’, which they claim has the advantage of accommodating ‘both
46 research on predictors of adolescents’ pornography use and research on how this use is associated with certain criterion variables’. The DSMM promotes four core propositions:
1. that three types of variables (i.e., dispositional, developmental, and social) predict media
use;
2. that response states, originating from media use, mediate the relationship between media
use and criterion variables—the response states include cognitive, emotional, and excitative;
3. that dispositional, developmental, and social variables may not only predict media use but
also moderate how media use predicts criterion variables; and
4. that media use and criterion variables correlate in a ‘transactional way’, such that changes in
criterion variables as predicted by media use may conversely predict media use [1].
In essence, the DSMM designates ‘media use’ as the overarching principle for arranging and understanding adolescent pornography research. It has been attractive to other researchers as well
— for example, Turner [5] and Housten [3]. It seems a helpful way to ground adolescent pornography-related behaviours to their principal medium of media usage to explain why some adolescents are more vulnerable to pornography exposure.
However, the DSMM model has limitations. For example, it omits non-media predictors on pornography use. Neurological studies, including compulsive behaviours, or other catalysts for pornography consummation apart from media exposure, like sexual drive and biological change.
Although the authors cite Owen’s review, which discusses the neurological research available in
2012. Peters and Valkenburg make no reference to this area. An explanation about why neurological studies were excluded was provided by one of the authors, Professor Jochen Peter, in email correspondence. He said that due to time and space limitations, in the context of resolving more basic challenges like the limitations to sampling, design, and assessment of the content of
47 pornography, they could not include that field. That said, he believed the DSMM does ‘by no means preclude neurological approaches to media effects, notably in its focus on response states.’2
Even if neurological forces influencing pornography engagement were considered response states from media use, which the research has not yet demonstrated, other environmental factors like parenting or peer culture, may have more of an influence of an adolescent’s sexual behaviours and attitudes then just being mere mediators of media use, as the DSSM suggests.
Furthermore, some broader societal effects that influence well-being, mental health, and gender inequalities, may be independent of the individual’s susceptibility to media effects.
A further concern by this author about the DSMM, is that the structure and content of research in
Peters and Valkenburg’s systematic review relies heavily on this framework. However, as a pragmatic observation, the Chapter 1 categories of ‘personal’, ‘societal’ and ‘relational’ effects (in this thesis), also account for and systematises the same research without the limitations of a ‘media effects’ paradigm.
Furthermore, the categories in Chapter 1 that account for the wider effects on adolescents is more expansive, by including the relevant dimensions of societal effects (which were shown to have a recursive influence adolescent attitudes and behaviours e.g. peer attitudes [6]), as well as relational effects, including the temporal dimension of future relationships. This seems to be more holistic when addressing preliminary research.
Considering there is no adequate framework to develop and implement a program we propose to develop a new theoretical framework, building on the broad body of data discussed in Chapter 1, to
2 Email correspondence with Professor Jochen Peters dated 1 May 2020. 48
guide the design and implementation of an interventional study that incorporates many of the main
risks and solutions.
2.3 Core Constructs for the Intervention
2.3.1 Negative Effects Constructs
In collating the negative effects of pornography from Chapter 1, it is helpful to allocate constructs
according to the common aspects of education: knowledge, attitudes and behaviours (KAB).
a. Knowledge
• Poor sexual knowledge, unrealistic expectations
• Neurological effects, Compulsivity, sexual preoccupancy, academic and memory
consequences
• Social and legal consequences of Sexting
• Long-term relationships and personal health
b. Attitudes
• Wellbeing, including self-esteem, emotional stability, conduct, empathy, and relationships
with peers.
• Gender imbalance, objectification culture
c. Behaviours
• Prevalence of access
• Sexual violence and violence against women
• Sexually permissive behaviour, sexual risk taking, earlier first-time engagement
• General behavioural problems
• Social responsibility
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2.3.2 Positive Solutions Constructs
In developing methodologies for achieving positive outcomes (in reducing negative effects), it seems
appropriate as a starting point to apply the methodologies shown to be effective (Chapter 1). It
follows that a program could be strengthened with the following:
2.3.3 Education
• Information on pornography, positive relationships, and good sexuality (KABs)
2.3.4 Parental engagement
• Parental mediation of pornography (facilitating discussion about pornography)
• Parental relationships (improving the general quality of parental relationships)
• Parental restrictive mediation (boundaries and rules around internet access and sexualised
behaviours)
2.3.5 Peer engagement
• Peer communication (facilitating clear communication about attitudes and expectations)
• Corporate critical thinking and social responsibility (seeking corporate ownership of reducing
the negative effects of pornography)
2.3.6 Broader integration of community involvement
• Parent awareness events
• School-wide or community group-wide awareness and support of the learning content and
outcomes
• Engaging community leaders and external resources to complement the program
2.3.7 Behavioural therapies
• Encourage abstinence for problematic use
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• Engage with techniques and therapies like CBT where appropriate
• Engage with therapeutic interventions where other adverse effects from pornography are
being experienced by students (e.g. depression, low self-esteem)
2.4 Further Considerations for a School-Based Context?
In synthesising the research to develop an education program on pornography, a key question
arises: What is an effective program, and what governs its purpose and outcomes?
The major stakeholders in shaping an intervention are those responsible for young people, including
parents, schools and education departments. There may also be community groups like faith-based
organisations, non-government schools, governing bodies, policy makers, and other institutions
responsible for young people.
A sound intervention should be designed to include a school context, where wide reach and
standardised training and evaluation can be applied. However, if there were inhibiting factors
restricting the delivery of an evidence-based, research-driven curriculum in schools, (for example,
local censorship or religious sensitivities), a program may also be tailored for a non-school context
based on this research.
This study proposes that the intervention be a school-based education program. There are a number
of reasons for this, including:
• There is a high number of potential subjects that can be recruited.
• Schools can provide a healthy quantity of ‘otherwise normal’ subjects, increasing the
generalisability of the results (given sufficient sample size).
• Schools have ready-made systems suitable for both recruiting and conducting a study like
this.
51
• Teachers are well qualified to teach on many of the topics and issues identified in the
constructs section, including nationally accredited teaching standards.
• There are educational frameworks, like National and State curriculums, that can shape and
direct the intervention’s content and delivery, increasing its robustness, respectability, and
empirical validity.
• If the intervention is successful, it may be adaptable for wider use.
Good sources of guidance in developing the new program are the parameters given by government
education departments. It is well documented in Australia, for example, that education programs are
holistic, concerned with wellbeing, social responsibility, reduce harm, encourage life-long success
and social responsibility, social equality, and produce positive longer-term relationships (this is
discussed in Section 4.1 below). Although knowledge and critical thinking are foundational, healthy
living is a major goal. Thus, a school-based intervention should seek to address many of the negative
effects of pornography as they pertain to the wellbeing of students, their peers, their communities,
and their future.
2.4.1 Local Contexts for Program Frameworks
As discussed in Chapter 1, pornography-related interventions have previously been developed in
Australia and the UK, in accordance with their respective national/regional curriculums. In Australia,
this sits under the Health and Physical Education (HPE) strand of the National Curriculum. The stated
aims of the HPE strand are to: “develop the knowledge, understanding and skills to enable students
to… access, evaluate and synthesise information to take positive action to protect, enhance and
advocate for their own and others’ health, wellbeing, safety and physical activity participation across
their lifespan [7].”
Similarly, the NSW Board of Studies Personal Development, Health and Physical Education (PDHPE)
curriculum includes the key aims that: “maximise their individual talents and capabilities for lifelong
52
learning; prepare all students for effective and responsible participation in their society; develop
positive self-concepts and their capacity to establish and maintain safe, healthy and rewarding lives;
promote a fair and just society that values diversity; and develop a system of personal values based
on their understanding of moral, ethical and spiritual matters [8].”
The UK’s National Curriculum on Sex and Relationship Education, a statutory component of the
Personal, Social, Health and Economic (PSHE) education curriculum requires that: “the development
of attitudes and values, personal and social skills, and knowledge and understanding; to help young
people make responsible and well informed decisions about their lives, through their physical,
emotional and moral development, for lifelong learning about physical, moral and emotional
development [9].” This is within the broader core themes of Health and Wellbeing, Relationships,
and Living in the Wider World [10].
These curricula each seek to develop the student holistically, not merely to impart knowledge and
engage in critical thinking. The themes of wellbeing, health, respectful and successful relationships,
preparation for adulthood, and social responsibility, allow for a broad interaction with the various
effects of pornography as identified in the literature. That is, a new curriculum should address
knowledge, attitudes and behaviours, both in the student’s present and future life, and as they
engage socially.
2.4.2 Limitations of some National Curricula
Concern has been raised about blindly conforming to current guidelines from government education
departments, because this may limit a program’s effectiveness. For example, in her reflections of the
challenges of developing pornography-related curriculum in an Australian context (under the
national curriculum), Ollis questions whether the ‘strength-based’ approach that undergirds the
national curriculum can help achieve key outcomes [11].
53
The strength-based movement, which followed the Seligman’s ‘positive psychology’, has influenced the creation of many strength-based frameworks. The goals of positive psychology include happiness and well-being through the harnessing of the positive strengths within the patient (contrary to classic deficit-oriented approach to psychotherapy) [12]. Likewise strength-based curricula seek to build on the default strengths in a student, to assist them to realise their potential, enabling them to be successful both personally and professionally [13], and recognises the positive aspect of a student’s own effort and achievement [14].
The risk that concerns Ollis, is that core educational outcomes may be missed, particularly when sex- positive education is at odds with imminent, unavoidable negative discourses like violence against women and gender inequality. Furthermore, if the emphasis on individual determination permits the student, who may lack a normalised view of respectful relationships, to bypass engagement with those important themes, or if the numerous negative, de-humanising messages in pornography have become normalised for the student (i.e., violent attitudes to women is a strength), then strength- based education is limited. Clabaugh raises concerns of the limitations of a methodology that educates by individual determination, particularly if it excludes learning skills and elements essential for holistic competence [15]. Another concern raised by Ollis is the problem of de-gendering the curriculum, which may avoid critical analysis of pornography’s mainly female-negative messages
[11].
Taking into account these observations, it is still possible that strength-based approaches can be harnessed in pornography education insofar as students bring a heightened awareness of technology, sexual awareness, or a desire for a healthy functional adult life, driving discussion, critical thinking and goal setting. Education methodologies are tools for achieving outcomes, not the
54
outcomes themselves. What is required are clear constructs and outcomes that are measurable and
achievable.
2.5 Need for an Assessment Instrument
An assessment tool will need to be created to conduct the empirical study which follows. Although
there are some validated survey instruments for smaller studies [16-18], there are no measures
comprehensive enough to assess a school-based educational intervention. This is unsurprising, since:
• pornography related studies are still a relatively new phenomenon;
• there is no consensus on theoretical frameworks, on what constitutes a negative effect, and
thus what a program should actually target;
• current programs have not been subjected to rigorous empirical evaluation; and
• an education program covers a broad knowledge base, which requires an extensive and
time-consuming instrument development followed by validation.
These current limitations suggest a new assessment tool is required, one that can measure the
constructs identified in Section 2, as well as any change in those constructs following an
intervention.
2.6 Conclusion
Despite some adolescent pornography studies being conducted within theoretical frameworks, or
the establishment of more comprehensive frameworks like the DSMM to advance future research,
no adequate model exists to develop a program of the scope proposed in this study. Thus, an
exploratory theoretical framework is proposed for developing and implementing a school-based
program that reduces key negative effects from pornography.
55
The framework directs three methodologies: didactic teaching, peer-to-peer engagement, and parental engagement, to reduce key negative effects associated with individual, relational and societal dimensions of an adolescent’s pornography exposure.
The characteristics of a program built on this framework should include:
• content built on the key negative risk constructs identified by research;
• research-driven strategies that have demonstrated some reduction in those risks, including
knowledge-based education, peer-engagement strategies, and parent-engagement
strategies, and possibly therapies targeting neurological and cognitive behaviours;
• content that conforms to acceptable national standards for schools and students (within an
Australian context (in this case), being aware that some standards may risk limiting the
intervention’s effectiveness; and
• measurability by being able to assess changes in knowledge, attitude and behaviour, as well
as being able to distinguish and gauge what strategies may contribute to a change in
knowledge, attitudes and behaviours.
Following these considerations, a clear pathway forward for this study has emerged, including drafting a program, subjecting it to a robust review process, creating and validating a baseline survey sufficient to measure the program’s effectiveness, and then implementing and analysing the program for effectiveness.
56
2.7 Chapter References
1. Peter, J. and P.M. Valkenburg, Adolescents and Pornography: A Review of 20 Years of Research. The Journal of Sex Research, 2016. 53(4-5): p. 509-531. 2. Owens, E.W., et al., The Impact of Internet Pornography on Adolescents: A Review of the Research. Sexual Addiction & Compulsivity, 2012. 19(1-2): p. 99-122. 3. Houston, J.B., M.L. Spialek, and J. First, Disaster Media Effects: A Systematic Review and Synthesis Based on the Differential Susceptibility to Media Effects Model. Journal of Communication, 2018. 68(4): p. 734-757. 4. Valkenburg, P.M. and J. Peter, The Differential Susceptibility to Media Effects Model. Journal of Communication, 2013. 63(2): p. 221-243. 5. Tomić, I., J. Burić, and A. Štulhofer, Associations Between Croatian Adolescents’ Use of Sexually Explicit Material and Sexual Behavior: Does Parental Monitoring Play a Role? Archives of Sexual Behavior, 2018. 47(6): p. 1881-1893. 6. Rasmussen, E.E., et al., The Relation Between Norm Accessibility, Pornography Use, and Parental Mediation Among Emerging Adults. Media Psychology, 2016. 19(3): p. 431-454. 7. ACARA. Australian Curriculum Health and Physical Education. 2017 Accessed on 14/3/2018]; Available from: https://australiancurriculum.edu.au/f-10-curriculum/health-and-physical- education/. 8. NSW, B.o.S., Personal Development, Health and Physical Education: Years 7-10: Syllabus. 2003, Board of Studies NSW. 9. Britain, G., Sex and Relationship Education Guidance. 2000: Department for Education and Employment. 10. https://www.pshe-association.org.uk/curriculum-and-resources/resources/programme- study-pshe-education-key-stages-1 11. Ollis, D., The Challenges, Contradictions and Possibilities of Teaching About Pornography in Sex and Relationships Education (SRE): The Australian Context, in Global Perspectives and Key Debates in Sex and Relationships Education: Addressing Issues of Gender, Sexuality, Plurality and Power. 2016, Springer. p. 48-67. 12. Rashid, T., Positive Psychotherapy: A Strength-based Approach. The Journal of Positive Psychology, 2015. 10(1): p. 25-40. 13. Stebleton, M.J., K.M. Soria, and A. Albecker, Integrating Strength-based Education into a First-year Experience Curriculum. Journal of College and Character, 2012. 13(2). 14. Lopez, S.J. and M.C. Louis, The Principles of Strengths-based Education. Journal of College and Character, 2009. 10(4). 15. Clabaugh, G.K., Strengths-based Education: Probing its Limits. Educational Horizons, 2005. 83(3): p. 166-170. 16. Peter, J. and P.M. Valkenburg, Adolescents' Exposure to Sexually Explicit Internet Material, Sexual Uncertainty, and Attitudes Toward Uncommitted Sexual Exploration: Is there a Link? Communication Research, 2008. 35(5): p. 579-601. 17. Grubbs, J.B., et al., Internet Pornography Use: Perceived Addiction, Psychological Distress, and the Validation of a Brief Measure. Journal of Sex & Marital Therapy, 2015. 41(1): p. 83- 106. 18. Evans-DeCicco, J.A. and G. Cowan, Attitudes Toward Pornography and the Characteristics Attributed to Pornography Actors. Sex Roles, 2001. 44(5): p. 351-361.
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Chapter 3: Design and Validation of Baseline Survey
3.1 Introduction
In Chapter 1, it was observed that a broad body of peer-reviewed quantitative research concludes
there can be negative outcomes from an adolescent’s exposure to pornography. A minority view
that pornography exposure can have positive effects, or at least effects that are not negative, was
also observed. However, the small number of studies giving the minority view was outweighed by
the larger volume of research associating pornography with negative effects. Some of the key
constructs derived from the negative effects associated with pornography exposure include:
adapting attitudes of sexual objectification towards women [1], increased sexual aggression [1-5],
increased positivity towards uncommitted sexual exploration [6], negative gender attitudes [1, 7, 8],
increased compulsivity [9] and addictive behaviours [10], reduced self-esteem [11, 12], emotional
stability, social empathy [4, 13], social conduct [14], poor family [5, 14] and peer relationships [15],
and increased sexualised behaviours on social media, including ‘sexting’ [7, 16].
Chapter 1 also noted the limitations to these studies, including most being cross-sectional, and study
samples varying in size, age, and social background of subjects. The studies have not used
standardised measures, making it difficult to compare findings. The lack of longitudinal and
controlled interventional research means that adverse effects of exposure to pornography have not
been conclusively demonstrated in otherwise healthy adolescent populations.
Regarding the reduction of negative effects for adolescents exposed to pornography, there is
minimal research that establishes effective strategies for reducing negative effects, although
broader studies have indicated that parental rules and communication [17-23], peer attitudes and
behaviours [17, 24], education programs [25], and behavioural therapies may be effective. Despite
the well documented negative effects of pornography on adolescents, there is only a small number
58
of school-based education programs that address pornography and sexualised media. None of these
programs have been empirically tested for effectiveness.
In Chapter 2, it was argued that the theoretical frameworks for understanding adolescent
engagement with pornography are poorly developed. This vacuum, coupled with the lack of
empirical evidence for other effective interventions, justifies a new intervention building on key
negative effect and positive solutions constructs for a school-based context guided by national
curriculum standards. The core hypotheses of the study posit that a three-pronged strategy
integrating didactic content, peer-to-peer activities, and parental engagement, can reduce the
documented negative effects, identified in Chapter 2 (3.1), on a cohort of young people aged
between 14 and 16.
A preliminary requirement is the creation and validation of a baseline survey to assess change. This
chapter describes how a baseline survey was designed, implemented, and validated.
3.1.1 Important considerations for a school-based baseline survey
Some limitations arise when conducting a survey in a school context, which restrict aspects of this
study.
a. If a survey is to be implemented across numerous schools, and with varying and congested
timetables, it should be able to be completed in a reasonable time. Advice from school
contacts suggests a survey should be completed under 30 minutes because most high school
classes/periods are 40–50 minutes long (and additional time is required explain the process,
set students up on devices, and allow for slower students to finish) – longer than 30 minutes
is unrealistic. A 90-100 question survey is proposed. Independent schools in NSW have been
59
chosen because they are less regulated by overarching bodies, reducing the risk of time-
delays for completing the study.
b. The language and concepts of the survey need to be age-appropriate for Year 10. Year 10 has
been chosen because the elements covered in the proposed program in Chapter 5 aligned
with Stage 5 of the Australian National Curriculum.
c. Every effort to minimise risk of harm needs to be taken, including: using previously validated
questionnaires, ensuring confidentiality and anonymity, and providing counselling services in
the event of distress.
3.2 Aim
The aims of the survey project are:
a. To design a baseline survey that includes the constructs in Chapter 2, within the limitations
of length and age-appropriateness for Year 10 school students.
b. To conduct this survey in a school-based context, similar to where the program will be
implemented
c. To test the validity of the survey factors
3.3 Method
3.3.1 Survey construction and implementation
Selection philosophy:
To determine instruments that measure the constructs outlined in Chapter 2, past studies were
surveyed to identify relevant instruments. If these instruments had previously been validated, were
brief, and could theoretically measure one of the chosen constructs, they were considered for
60
inclusion. Where possible, these instruments should keep their original wording, format, including
number of Likert Scale answers.
If the instruments can align with those used in similar studies, especially related to school-based
education research, they were selected over other comparable instruments. For example, the La
Trobe Sexualised Social Media Scale [26] was chosen to explore ‘sexting’ over other studies because
it is a relatively recent scale used by Australian students, which is better for local cross-comparisons
than, say, the Sexting Behaviours Questionnaire conducted by Morelli in Italy [16].
Control variables have been included for stratifying purposes, including ones commonly asked in
surveys like gender, age, and age of first-time exposure, to provide better comparison with
international studies and because it may help stratify to subjects in this study. For example, the
schools recruited are all independent religious schools, so parental working status, or student and
family religious status, may skew results compared to a typical population.
Some items were included as exploratory ideas, not prompted by past studies. By way of discerning
a survey item from a general term or concept, all survey factors use a capital throughout these
chapters to distinguish them. For a full list of the survey questions, including response options,
please see the table in Appendix B.
3.3.2 Control Variable Selection
The control variables were selected according to the following rationale:
a. Age of first time viewing:
This is a commonly used item for correlation and study-comparison analysis. Students were asked
the age they first viewed pornography. Pornography was defined as “any pictures, videos, or 61
literature designed to sexually excite” [14, 27]. Although commonly associated with the internet,
students were told this could also be from books, television, magazines, phones or shared files. Data
on first-time age of pornography exposure differ across studies. For example, an Australian study
found average first-time exposure ages were 13 for boys and 16 for girls [28], where an international
study found the age to be younger—11 for boys and 12 for girls [29]. b. Viewing Prevalence:
This study adapted 2 items from Peter and Valkenburg’s 2008 Dutch study [30] as the primary
measure of pornography exposure. It asked whether students had encountered pictures or movies
which either had 1. people having sex; or 2. exposed genitals, within the last 6 months, with 7
choices (Never; Less than once a month; One to three times a month; Once a week; Several times a
week; Every day; Several times a day). Pornography is defined as “any pictures, videos, or literature
that is designed to sexually excite you”. The original study [30] found 79% of females and 42% males
(age 15-16) had never watched pornography, and 3% of females and 28% of males watch
pornography weekly of more. An Australian study of young people (age range of 15–29) found 1% of
males (n = 258) and 32% of females (n = 683) had never viewed pornography where as 84% of males
and 19% females viewed pornography weekly or more (noting the higher age range of 15–29) [28].
These are good benchmarks for comparisons. c. Preferred Viewing Device:
This item is relevant because of the rapid change in technology over the last 15 years, where the
interplay between media exposure and student behaviours may is likely to be influenced by
technological trends. For example, in Lim’s 2017 study of Australian young people, 96% of males
used either phones (33%) or computers (63%), and 90% of females used phones (41%) or computers
(49%) [38], suggesting that digital devices are a main way adolescents now access and view
pornography. This will be explored in this study. d. Parental Relationship:
62
This item was included as the marital status of the students’ parents may affect parenting patterns,
student behaviours, and wellbeing factors. The options are ‘married’, ‘divorced’, ‘live together (de
facto)’, ‘widowed’, and ‘other’.
e. Parental Employment:
This is a standard indicator of socio-economic status
f. Religion:
This item has been included because the schools to be invited will be independent religious schools,
so it is important to stratify results according to religious participation. The type of religion is not
defined. However, since all schools within this study were associated with the Christian tradition, it
can be assumed that most (but not all) associate with Christianity. Religion was also a control
variable in other studies, notably Peter and Valkenburg’s 2008 adolescent research [6]. To further
ascertain subject generalisability, a comparison of student results can be compared to 2016
Australian census data could be made. The Australian population reports 52% being Christian and
30% were not religious
g. Gender:
Gender is one of the most significant determinants of usage, attitudes and outcomes [1, 14, 29, 31].
The categories asked are ‘male’, ‘female’, and ‘other’.
3.3 Survey Factors derived from Constructs
a. Attitudes to Pornography
The Attitudes to Pornography scale [32] has 13 items measuring a range of negative attitudes about
pornography. The higher the score, the more negative the respondent’s opinion is about
pornography. This 13-item scale was included because it was brief, and includes key questions
about: pornography’s educative value, its impact on relationships and society, and gender imbalance
63
(aligning with Chapter 2 constructs). It has been used elsewhere [32, 33], with a Cronbach Alpha
reliability score of α = 0.85. b. Attitudes to Uncommitted Sexual Exploration
This scale was used in Peter and Valkenburg’s original study, called ‘Attitudes Toward Uncommitted
Sexual Exploration’ [6] where it received a Cronbach Alpha reliability score of α = 0.89. It explores
attitudes towards the type of sexual permissiveness that is promoted by pornography:
uncommitted, casual, and experimental. This measure focuses on attitudes, rather than behaviours,
which may predict future intentions and aspirations in a cohort of 15-year olds. As explored in
Chapter 1, past theory suggests that increased pornography-viewing correlates with increases in
acting out [34], casual sex [6, 35, 36], earlier first-time sexual activity [3], sexually permissive
attitudes [14], and sexual sensation seeking[37, 38], so additional behavioural risks may be identified
through this scale. c. Women as Sex Objects
This scale, first used by Ward [39] and adapted by Peter and Valkenburg [1] (Cronbach Alpha
reliability score, α = 0.75), has been included with no modifications. Noting the substantial research
about the association between viewing pornography and sexual objectification of women, increased
sexual aggression[1-5], and negative gender attitudes[1, 7, 8] – it was useful to use a scale that was
brief and previously validated in adolescent research. d. Well-Being Scales
There are many adolescent wellbeing instruments, including Achenbach’s Youth Self report, Piers-
Harris’s Self-Concept Scale for Children, Goodman’s Strengths and Difficulties Questionnaire, and
Marsh’s Self-Description Questionnaire.
This study selected 6 subscales from 2 questionnaires — the Self-Description Questionnaire II (SQII)
[40] and the Strengths and Difficulties Questionnaire (SDQ) [41] — because these subscales are brief,
and align with well-being factors in Chapter 1. Although there is no known precedent for these
64
subscales being used in pornography-related studies, their brevity affords a means of assessing if
some items from well-recognised general adolescent scales correlate with the other factors in this
study.
Self-Description Questionnaire II
Marsh’s Self-Description Questionnaire is widely recognised as validated and robust, and compares
well to the Youth Self Report [40, 42]. It has been described as the most psychometrically
validated self-esteem measure for late childhood/early adolescence [43]. The following subscales
have been used:
e. Parent Subscale
These 4 items measure the general health of student-parent relationships. It has a Cronbach Alpha
reliability score of α = 0.84 [40]. It is included as it has been shown that adolescents may have poorer
parental relationships when pornography use increases [5, 14]. f. Self-Esteem Subscale
The Self-Esteem subscale uses 6 items and has a Cronbach Alpha reliability score of α = 0.84 [40].
Self-esteem is being measured in this study since it has often been observed to change when
pornography viewing increases. For example, Kor [44] predicted that self-esteem decreases as
pornography viewing increases . Other research [45, 46] predicted that general internet addictive
behaviours (like social media use) would correlate with lower self-esteem. g. Emotional Stability Subscale
This 5-item subscale has a Cronbach Alpha reliability score of α = 0.80 [40], and is included because
of its general application to a range of mental health observations including depression [11, 12],
sexual uncertainty [6] and sexual insecurity [14].
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Strengths and Difficulties
Goodman’s Strengths and Difficulties Questionnaire has been well validated [41, 47], and has a
precedent for the subscales being used independently [48]. As with Marsh’s SQII, the brevity of
these scales and alignment with Chapter 2 constructs make them suitable candidates for this study.
h. Conduct Subscale
The Social Conduct 5-item sub-scale measures a student’s self-perception of rule-keeping, risk
taking, and general social conduct, (Cronbach Alpha reliability score of α = 0.65) [41]. Other authors
have suggested that pornography viewing contributes to poorer social conduct [14], an increase in
risky behaviour [3, 37], and compromised decision making [49, 50]. i. Peer Subscale
This 5-item sub-scale measures the general health of student-peer relationships. a moderate
Cronbach Alpha reliability score of α = 0.61. There are inconsistent theories about how viewing
pornography affects the quality of an adolescent’s peer relationships. For example, Marriot [15]
argued that as pornography viewing increases, peer relationships become poorer. In contrast, Peter
and Valkenburg [29] conclude that attachment to peers is unrelated to adolescents’ use of Internet
pornography. However, Andreassen theorised that pornography users have closer peer relationships
due to a craving for intimacy [51]. Notwithstanding that clarifying the effects of pornography on peer
relationships will be helpful, the subsequent intervention study will also involve peer interaction,
and thus this measure will assist in evaluating its effectiveness. j. Prosocial Subscale
This factor measures the teenager’s levels of empathy for, and desire to help and show kindness, to
others (Cronbach Alpha α = 0.72) [41]. Considering the Chapter 1 observations that pornography
usage could harm others, including gender discrimination, sexual aggression and violence, and that
66
pornography production often involves the exploitation of vulnerable people — measuring a
student’s change in social empathy should be a helpful indicator of the intervention’s effectiveness. k. Peer Injunctive scale
The Peer Injunctive Norm 2-item scale, devised by Rasmussen [17] and first validated by Rhodes
[52], measures the normative views about pornography within the student’s peer group. It does not
describe the behaviours of peers (regarding pornography use), rather it captures the student’s
perception about what is normative and acceptable within their peer group. Peers’ normative beliefs
have significant influence on a student’s own engagement with pornography [17, 24], a key focal
element of this study’s intervention. This factor will be relabelled as Peer Attitudes throughout this
study. l. Peer Descriptive scale
The Peer Descriptive 2-item scale, also taken from Rasmussen’s study [17], is defined as what the
adolescent knows about their peers’ pornography-related behaviours [17]. Peer descriptive
normative behaviours have been shown to be more influential on pornography consumption than
the more distant perceptions of Peer Attitudes [17]. This factor will be relabelled as Peer Behaviours
throughout this study. m. Negative Active Mediation scale
The Negative Active Mediation 4-item scale is defined as the frequency of parental discussions
(with their child) about their negative views of pornography (Rasmussen [17]). This factor has been
found to have a significant direct effect on pornography viewing [17]. Similar studies have found
that a parent’s negative communication about pornography (or similar undesirable behaviours) is
effective in reducing pornography viewing [18-23]. This factor will be relabelled as Parent
Communication throughout this study. n. Restrictive Mediation scale
The Restrictive Mediation scale, is defined by Rasmussen as ‘rules and restrictions about media
access’ [17]. It originally was a 2-item scale asking about parental restrictions for accessing
67
pornography, but 2 additional questions about access to digital devices and social media accounts
have been added by us to this study. Vakalahi [23] and Habib [53] have suggested that parental rules
and restrictions are more effective than parental communication, in reducing the frequency of
pornography viewing. Although some studies have claimed that rules encourage resistance to
desirable behaviours [24], especially in the absence of proactive communication [17, 18, 21, 54], this
study will theorise that restrictive mediation, independent of parent communication, would be
effective in reducing pornography viewing. This factor will be relabelled as Parent Rules throughout
this study. o. Cyber Pornography Use Inventory
The 9-item Cyber Pornography Use Inventory–9’ (CPUI-9), is comprised of 3 subscales (each with 3
items), and measures the perceived compulsivity of a pornography use, how intentional the effort to
access pornography is, and if emotional distress about viewing pornography occurs. First developed
by Grubbs [9], the CPUI-9 has been useful in measuring perceived compulsivity, and actual
compulsivity [10]. Fernandez [10] and Wilt [55] concluded that the 3 subscales are best separated
into 2 subscales, with the Compulsivity and Access Efforts subscales combined because of consistent
correlation, whilst the Emotional Distress subscale should function independently. Fernandez [10]
showed distress worked independently from the perceived compulsivity and access efforts subscales
and Wilt [55] identified that emotional distress, mediated by religious moral disapproval, worked on
an emotional level, not cognitive, with no effect on perceived compulsivity. These theories will be
explored through confirmatory factor analysis in Section 3.2. p. Sexualised Social Media Behaviour
The Sexualised Social Media Behaviour scale is an 8-item measure describing the prevalence of
sexualised social media behaviours, adapted from the La Trobe University study, National Survey of
Australian Secondary Students and Sexual Health 2013 [26]. We have added two new items to the
original 6-item scale to explore the student’s perception of normalised sexualised social media
behaviours amongst friends and in society. This scale is particularly useful for this given the
68
correlations between pornography viewing and social media behaviours [7, 16]. Often described as
‘sexting’, this behaviour has potential problems for both sender and receiver, including harassment
and the illegal distribution of child pornography [56]. European research [7] suggests that up to 69%
of females (average age of 14) have sent a form of sext, while up to 77% have received one. For
males in that study, up to 46% have sent a sext, and up to 58% have received one. Since the 2013 La
Trobe study was conducted in an Australian context [26] and included students aged 14–18, it will be
useful for comparing with the students in this validation study, and the interventional study
(Chapters 5–9), to gauge how typical they are, or if shifts in sexualised social media behaviours have
occurred since 2013. No validation of this measure has been published.
3.4 Results
3.4.1 Survey validation
Schools were recruited from a database of 40 independent schools in New South Wales, Australia.
School principals were invited via mail between March and April 2018, and surveys were conducted
between May and June 2018. A total of 9 schools volunteered, with 2 later withdrawing due to
difficulties completing within the preferred schedule. Of the final 7 schools, 3 were single-sex schools
(2 male and 1 female school) and four were co-educational. Out of a maximum 834 students available
from the 7 participating schools, 746 Year 10 students completed the survey (564 boys and 182 girls),
an 89.4 % participation rate. There were 59 incomplete surveys. Consent was opt-out, with 29
students not participating at the request of their parents. It is difficult to gauge from the literature if
7 out of 40 schools is a typical response rate, since as Blom-Hoffman observed, only 11.5% of schools
reported participation rates [57]. Additionally, schools generally only reported the final student
participation, not the rate of the school’s initial invitation acceptance. However, what can be
compared is the rate of student participation for ‘passive’ or opt-out acceptance, which in past studies
is on average 89.1%, and similar to this study.
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Participation Information Statements (PIS) were sent to students, class teachers, and parents. Opt-out consent was required by both parents and the student. The PIS’s made clear that the surveys were anonymous, confidential, and that students could withdraw at any time during the process.
Additionally, school counsellors were available to meet with students in the event of distress caused by the survey. Although there is the risk of bias from self-report surveys, it has been shown that confidential and anonymous self-report surveys are best suited for sensitive matters (e.g. sexuality) with adolescents [58], and where there are a lot of questions within the survey [59].
The survey consisted of 93 questions, including items taken from 18 scales from past studies, and 10 control questions (Appendix B).
The online survey was delivered using RedCap, Sydney University’s preferred online survey platform, separated into 8 sections, requiring the selection of a ‘next page’ tab before proceeding to a new section. The only items that were compulsory were the preliminary control questions and the Age of
First Exposure question. Other items that were not completed were treated as missing data. If students did not choose to submit the form at the conclusion, the survey was marked ‘incomplete’, and excluded from the study.
After the survey, all schools reported:
a. no students complaining or expressing concerns about the survey;
b. no administrative difficulties in administrating the surveys; and
c. the surveys generally taking less than 20 minutes to complete.
Missing Data were handled in two ways. If students indicated they had never viewed pornography, questions pertaining to viewing frequency, preferred device, intentionality, compulsivity and viewing
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distress were left blank. Whenever data analysis was performed on those items, the whole
observation was excluded, being treated as listwise deletion. If data were missing for other reasons,
steps were taken to replace missing data using the Multiple Imputation (MI) method [60]. There
were 454 unique missing items, approximately 0.3% of all items. MI is commonly accepted as the
strongest method for dealing with missing data particularly as it preserves the original standard
errors, eliminating bias once missing data is replaced. The criterion for replacing missing data was
that data was either Missing Completely at Random (MCAR) or Missing at Random (MAR) — a
requirement for MI. Analysis of all missing items satisfied this criterion, so data were replaced using
the average of 20 imputations.
Ordinary Least Squares (OLS) regression analysis was applied in all simple linear and multiple
regression models rather than ordinal logistics regression even though the questions were ordinal
Likert scales, and not normally distributed when tested using the using the Shapiro-Wilk test for
normality. It is commonly assumed for parametric regression that data are normally distributed.
However, it is widely accepted that parametric tests are robust for violations for normality [61],
particularly in the case of higher sample sizes – as in this study. Many of the past studies, from which
this research has obtained its scales and inventories, also applied OLS or other parametric models on
their Likert-based data [1, 6, 10, 17, 41, 62]. Thus, this study also applied OLS parametric analysis.
Data was analysed using Stata IC 15.1.
3.4.2 Validating the constructs
The process of validating the survey constructs followed three phases. Firstly, exploratory factor
analysis (EFA) and principle components analysis (PCA) were conducted on all items excluding the
questions about parental marriage and employment status. Secondly, confirmatory factor analysis
(CFA) was performed on all scales/constructs taken from past studies, as well as new factors
identified in phase one. Lastly, Cronbach alpha analysis was conducted on all factors (Table 1.).
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The use of EFA and PCA was not strictly necessary, as this survey primarily used previously validated scales. However, since was is no precedent for combining these scales (which together total 90 items), it seemed worthwhile to see if factors naturally arise, or if there are high correlations across the scales, thus rendering some items or factors redundant. As there is a lack of consensus about whether EFA or PCA is preferable, with some evidence suggesting PCA is slightly favoured [63], both methods were explored. Only factors or components with eigenvalues of 1 or above were selected.
To conclude if EFA factors loaded acceptably, factor loadings of 0.3 and above were selected, using oblique rotations (preferred when there is the likelihood of some degree of correlation between factors [9, 63]). To conclude if principal components loaded acceptably, loading values of 0.3 and above were selected. Table 1 shows if a scale loaded as a unique factor using EFA, or component using PCA. Only the scales Attitudes to Pornography, Sexual Objectification of Women, and
Sexualised Social Media Behaviour did not load in either. The original 9 item scale Compulsive
Problematic Internet Use inventory (CPUI9) also did not load. However, 6 of the items (from the
Compulsivity subscale and Efforts subscale) did, and the remaining 3 items (from the Distress subscale) loaded as a separate factor and component. As indicated in Section 3.2, Fernandez established that the Distress subscale is a distinct factor [10], so for the purposes of this study it has been separated it from the original CUPI9 inventory, to provide two factors: Compulsivity
(comprising of the original 6 items Compulsive and Efforts subscales from the CPUI9), and Distress
(maintaining its original items).
The Attitudes to Pornography did not load on either EFA or PCA. There were 4 items which loaded on a separate factor. The distinct aspect of these 4 items was that they asked whether pornography provided a positive effect, whilst the other 9 items asked if it had a negative effect. Various models were attempted to reconcile the 13 items at the CFA stage, with a mediocre [64] fit found by correlating 2 latent variables: the 4-item positive effects latent variable and the 9-item negative
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effects of pornography latent variable (RMSEA of 0.088, TLI 0.852, and Coefficient of Determination
0.96). An attempt to validate two separate factors from the 13 items failed, since CFA modelling
yielded RSMEA scores of 0.165 for the 4-item positive effects and 0.098 for the 9-item negative
effects latent factors. The full 13-item scale still produced a strong Cronbach alpha score (0.84),
suggesting it has acceptable merit. This scale’s original source [32] only provides Cronbach alpha
scores to support its validation, with no factor analysis conducted. So, with no other guidance on
how best to use it, the original scale will be maintained.
Another new factor emerged in the EFA and PCA studies, which was the combination of two control
items – My Religion and Family Religion. Subsequently, this new factor (simply called ‘Religion’) has
been tested at the CFA and Cronbach stages (Table 1) and preserved for later analysis in Chapter 4.
Each other factor was then assessed using CFA modelling, using maximum likelihood parametric
estimation for the goodness of fit tests. At a basic level, latent variables were modelled using the
original items for each construct, using Root Mean Square Error of Approximation (RMSEA) and
Tucker Lewis Index tests as guides for acceptable model fit [64].
3.4.2.1 The Super Wellbeing Scale
As a final analysis, a novel exploration of a new scale devised for this study was performed, called
the Super Wellbeing Scale. Its purpose is to provide a measure that broadly describes student
wellbeing, which may be useful in assessing the impact of an intervention. It combines the 3
subscales from Goodman’s Strengths and Difficulties questionnaire (Prosocial, Peer, Conduct) with
the 3 subscales from Marsh’s Self-Description Questionnaire subscales (Parent, Self-Esteem and
Emotional Stability). There is no precedent for this, and it is acknowledged that the psychometric
theories behind each scale may vary. Nonetheless, as each subscale is valid within itself, and each
measures the student’s general wellbeing (aspects that have been found to be associated with
73 pornography from wider studies), it was thought to be worth exploring. The Super Wellbeing Scale does validate under CFA with a RMSEA of 0.057, so it will be used to explore whether pornography viewing has any effect on the adolescent’s broad wellbeing in Chapters 4, 7 and 9.
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Table 3.1
Construct Validation Factor # of EFA PCA Cronbach CFA RMSEA TLI Items
Pornography Viewing 2 ? 0.9 . . .
Attitudes to Pornography 13 × × 0.84 ?? 0.088 0.85
Compulsivity 6 ? 0.74 ?? 0.108 0.92
Distress from Viewing 3 0.83 0 1
Emotional Stability 5 × 0.83 0.053 0.98
Parent Communication 4 ? 0.89 0.065 0.99
Parent Relationships 4 0.86 0.058 0.99
Parental Rules 4 × 0.66 0 1
Peer Attitudes 2 0.87 0 1
Peer Behaviour 2 0.73 0 1
Peer relationships 5 × 0.58 0 1
Religion 2 0.87 . . .
Self-Esteem 6 0.86 0.056 0.98
Sexual Objectification of Women 5 × × 0.67 0 1
Sexualised Social Media Behaviour 8 × × 0.81 0.083 0.92
Social Conduct 5 0.67 0.058 0.92
Social Empathy 5 × 0.59 0 1
Uncommitted Sexual Exploration 4 ? 0.74 ?? 0.102 0.93
Super-Wellbeing 30 × × 0.86 0.057 0.85
Note: RSMEA = Root mean square error of approximation. TFI = Tucker Lewis System, also known as Non-normed Fit Index (NNFI). Where RSMEA and TFI values are ‘.’, the models did not converge. ‘?’ – PCA factors only loaded when item values > 0.15. ‘??’ – CFA factors were outside the acceptable range (<0.3), but lowest value > 0.15.
All factors found some degree of validation, either via Cronbach Alpha scores or CFA, but not all were convincing. The weakest factors were Attitudes to Pornography and Compulsivity, which should still be included in the interventions baseline survey due to the acceptable Cronbach scores, as well as their historical validation [9, 32].
The additional questions added to the Parental Rules and Sexualised Social Media Behaviour scales loaded acceptably. And a new factor, Religion, has emerged.
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The implementation phase of the survey with its the high participation rate and low complaint rate
suggested this survey is age-appropriate, not distressing, and the implementation process is
manageable by schools.
3.4.3 Limitations
Despite an 89.4% student participation rate, there were only 7 out of 40 schools who accepted the
initial invitation to participate. This may reduce the generalisability of the sample. To assess how
typical the study cohort is of Australian students or broader adolescent studies, Chapter 4’s analysis
will include a comparison of the demographic, prevalence, factor correlations and means with wider
studies.
3.5 Conclusion
This study has achieved three objectives in preparation for designing and implementing a
pornography-related intervention.
a. A baseline survey suitable for Year 10 students was designed based on constructs
that emerged from the wider literature, using scales and items capable of measuring
prevalence, predictor and outcome factors related to pornography viewing.
b. The survey was successfully implemented in a school-based context, with a high
student participation rate, manageable time requirement, and with no adverse
effects or difficulties reported by schools.
c. The survey factors were validated, confirming that the survey is a reliable statistical
instrument, providing confidence that it will be suitable for evaluating the efficacy of
school-based program on pornography.
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Chapter 4 will continue the analysis of the survey data, comparing the results with the wider research and exploring for additional insights or questions, so that what is learned about this cohort may contribute to the design of the school-based intervention.
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3.6 Chapter References
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22. Harakeh, Z., et al., Parental Rules and Communication: Their Association with Adolescent Smoking. Addiction, 2005. 100(6): p. 862-870. 23. Vakalahi, H.F., Adolescent Substance Use and Family-Based Risk and Protective Factors: A Literature Review. Journal of Drug Education, 2001. 31(1): p. 29-46. 24. Weber, M., O. Quiring, and G. Daschmann, Peers, Parents and Pornography: Exploring Adolescents’ Exposure to Sexually Explicit Material and Its Developmental Correlates. Sexuality & Culture, 2012. 16(4): p. 408-427. 25. Skinner, S.R. and J.L. Marino, England's Teenage Pregnancy Strategy: A Hard-won Success. The Lancet, 2016. 388(10044): p. 538-540. 26. Mitchell, A., et al., National Survey of Australian Secondary Students and Sexual Health 2013. Melbourne: Australian Research Centre in Sex Health and Society & La Trobe University, 2014. 27. Merriam-Webster, Pornography. Merriam-Webster online dictionary, 2006. 28. Lim, M.S.C., et al., Young Australians' Use of Pornography and Associations with Sexual Risk Behaviours. Australian and New Zealand Journal of Public Health, 2017: p. n/a-n/a. 29. Peter, J. and P.M. Valkenburg, Adolescents and Pornography: A Review of 20 Years of Research. The Journal of Sex Research, 2016. 53(4-5): p. 509-531. 30. Peter, J. and P.M. Valkenburg, Adolescents' Exposure to Sexually Explicit Internet Material and Sexual Preoccupancy: A Three-Wave Panel Study. Media Psychology, 2008. 11(2): p. 207- 234. 31. Bonino, S., et al., Use of Pornography and Self-reported Engagement in Sexual Violence Among Adolescents. European Journal of Developmental Psychology, 2006. 3(3): p. 265-288. 32. Evans-DeCicco, J.A. and G. Cowan, Attitudes Toward Pornography and the Characteristics Attributed to Pornography Actors. Sex Roles, 2001. 44(5): p. 351-361. 33. Coyne, K.M., et al., Sexual Health of Adults Working in Pornographic Films. International Journal of STD & AIDS, 2009. 20(7): p. 508-509. 34. Baxter, A., How Pornography Harms Children: The Advocate's Role. Child L. Prac., 2014. 33: p. 113. 35. Wright, P.J. and R.S. Tokunaga, Activating the Centerfold Syndrome: Recency of Exposure, Sexual Explicitness, Past Exposure to Objectifying Media. Communication Research, 2013. 42(6): p. 864-897. 36. Peter, J. and P.M. Valkenburg, Processes Underlying the Effects of Adolescents’ Use of Sexually Explicit Internet Material: The Role of Perceived Realism. Communication Research, 2010. 37(3): p. 375-399. 37. Hald, G.M., et al., Does Viewing Explain Doing? Assessing the Association Between Sexually Explicit Materials Use and Sexual Behaviors in a Large Sample of Dutch Adolescents and Young Adults. The Journal of Sexual Medicine, 2013. 10(12): p. 2986-2995. 38. Reid, R.C., et al., Reliability, Validity, and Psychometric Development of the Pornography Consumption Inventory in a Sample of Hypersexual Men. Journal of Sex & Marital Therapy, 2011. 37(5): p. 359-385. 39. Ward, L.M., Does Television Exposure Affect Emerging Adults' Attitudes and Assumptions about Sexual Relationships? Correlational and Experimental Confirmation. Journal of Youth and Adolescence, 2002. 31(1): p. 1-15. 40. Marsh, H.W., et al., A Short Version of the Self Description Questionnaire II: Operationalizing Criteria for Short-form Evaluation with New Applications of Confirmatory Factor Analyses. Psychological assessment, 2005. 17(1): p. 81. 41. Goodman, R., H. Meltzer, and V. Bailey, The Strengths and Difficulties Questionnaire: A Pilot Study on the Validity of the Self-report Version. European Child & Adolescent Psychiatry, 1998. 7(3): p. 125-130. 42. Marsh, H.W., R.H. Parada, and V. Ayotte, A Multidimensional Perspective of Relations Between Self-concept (Self Description Questionnaire II) and Adolescent Mental Health (Youth Self-Report). Psychological Assessment, 2004. 16(1): p. 27.
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43. Guerin, S. and M. Tatlow-Golden, How Valid Are Measures of Children’s Self-Concept/ Self- Esteem? Factors and Content Validity in Three Widely Used Scales. Child Indicators Research, 2018. 44. Kor, A., et al., Psychometric development of the Problematic Pornography Use Scale. Addictive Behaviors, 2014. 39(5): p. 861-868. 45. Pantic, I., et al., Association Between Physiological Oscillations in Self-esteem, Narcissism and Internet Addiction: A Cross-sectional Study. Psychiatry Research, 2017. 258: p. 239-243. 46. Andreassen, C.S., S. Pallesen, and M.D. Griffiths, The Relationship Between Addictive Use of Social Media, Narcissism, and Self-esteem: Findings from a Large National Survey. Addictive Behaviors, 2017. 64: p. 287-293. 47. Panter-Brick, C., et al., Mental Health and Childhood Adversities: A Longitudinal Study in Kabul, Afghanistan. Journal of the American Academy of Child & Adolescent Psychiatry, 2011. 50(4). 48. Goodman, R., The Strengths and Difficulties Questionnaire: A Research Note. J Child Psychol Psychiatry, 1997. 38. 49. Laier, C., F.P. Schulte, and M. Brand, Pornographic Picture Processing Interferes with Working Memory Performance. Journal of Sex Research, 2013. 50(7): p. 642-652. 50. Laier, C., M. Pawlikowski, and M. Brand, Sexual Picture Processing Interferes with Decision- Making Under Ambiguity. Archives of Sexual Behavior, 2014. 43(3): p. 473-482. 51. Popovic, M., Pornography Use and Closeness with Others in Men. Archives of Sexual Behavior, 2011. 40(2): p. 449-456. 52. Rhodes, N. and D.R. Ewoldsen, Attitude and Norm Accessibility and Cigarette Smoking. Journal of Applied Social Psychology, 2009. 39(10): p. 2355-2372. 53. Habib, C., et al., The Importance of Family Management, Closeness with Father and Family Structure in Early Adolescent Alcohol Use. Addiction, 2010. 105(10): p. 1750-1758. 54. Floros, G.D., et al., Adolescent Online Gambling: The Impact of Parental Practices and Correlates with Online Activities. Journal of Gambling Studies, 2013. 29(1): p. 131-150. 55. Wilt, J.A., et al., Associations of Perceived Addiction to Internet Pornography with Religious/Spiritual and Psychological Functioning. Sexual Addiction & Compulsivity, 2016. 23(2-3): p. 260-278. 56. Commissioner, O.o.t.e., Sexting: Social and Legal Consequences 2016: Australian Government. 57. Blom-Hoffman, J., et al., Consent Procedures and Participation Rates in School-Based Intervention and Prevention Research: Using a Multi-Component, Partnership-Based Approach to Recruit Participants. School Mental Health, 2009. 1(1): p. 3-15. 58. Brener, N.D., J.O. Billy, and W.R. Grady, Assessment of Factors Affecting the Validity of Self- reported Health-risk Behavior Among Adolescents: Evidence from the Scientific Literature. Journal of adolescent health, 2003. 33(6): p. 436-457. 59. Paulhus, D.L., et al., The Self-Report Method. Handbook of Research Methods in Personality Psychology, 2007. 1: p. 224-239. 60. Schlomer, G.L., S. Bauman, and N.A. Card, Best Practices for Missing Data Management in Counseling Psychology. Journal of Counseling Psychology, 2010. 57(1): p. 1-10. 61. Norman, G., Likert Scales, Levels of Measurement and the "Laws" of Statistics. Advances In Health Sciences Education: Theory And Practice, 2010. 15(5): p. 625-632. 62. Grubbs, J.B., et al., The Cyber-Pornography Use Inventory: The Development of a New Assessment Instrument. Sexual Addiction & Compulsivity, 2010. 17(2): p. 106-126. 63. Gaskin, C.J. and B. Happell, On Exploratory Factor Analysis: A Review of Recent Evidence, An Assessment of Current Practice, and Recommendations for Future Use. International Journal of Nursing Studies, 2014. 51(3): p. 511-521. 64. Schermelleh-Engel, K., H. Moosbrugger, and H. Müller, Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-fit Measures. Methods of Psychological Research Online, 2003. 8(2): p. 23-74.
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65. Rasmussen, K., A Historical and Empirical Review of Pornography and Romantic Relationships: Implications for Family Researchers. Journal of Family Theory & Review, 2016. 8(2): p. 173-191.
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Chapter 4: Analysis of Survey Data
4.1 Introduction
In Chapter 3, a baseline survey was designed, implemented and internally validated in preparation
for conducting an intervention in a school context. An additional study is required to determine if
these survey measures, both control variables and factors, perform consistently with past research.
A potential threat to the study’s validity could arise if the survey cohort — a local population of
contemporary Australian students — is atypical of broader adolescent studies. The data from the
Chapter 3 study should be explored to confirm that Australian students are generalisable, in that
pornography poses typical negative risks for them, thus making them appropriate candidates for the
intervention.
There are various ways the data was explored:
a. comparing the prevalence results of initial indicators with other studies. This included the
control variables listed in Table 4.1, as well as some factors like Sexualised Social Media
Behaviours;
b. Regression analysis was performed on the predictor and outcome factors of Table 4.1, in
relation to pornography viewing, both to describe how the subjects were being impacted,
whilst reinforcing broader theories about the negative effects of pornography.
If the analysis shows that the students are typical with the broader research, then the proposed
intervention should be built upon the Chapter 2 constructs and shaped by these survey results.
Another benefit from exploring the survey data is that there may be unusual observations, or new
discoveries, which although not anticipated, may direct how the intervention should be constructed.
For example, new risks may be observed, or additional theories may arise, which with no
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explanation from the broader research, can be incorporated into the intervention prior to
implementing.
Table 4.1 Baseline Survey Measures
Control Variables Predictor Factors of Outcome Factors from Pornography Use Pornography Use
Viewing Prevalence Parent Communication Attitudes to Pornography*
Age of 1st-Time Viewing Parental Rules Women as Sex Objects
Preferred Viewing Device Peer Attitudes Uncommitted Sexual Exploration
Viewing Intentionality Peer Behaviour Parent Relationships
Parental Relationship Sexualised Social Media Behaviours* Peer Relationships
Parental Employment Compulsivity* Self-Esteem
Religion Attitudes to Pornography* Emotional Stability
Gender Social Conduct
Compulsivity*
Distress from Viewing
Sexualised Social Media Behaviours*
Super Wellbeing Total
Note: *The factors Compulsivity, Sexualised Social Media Behaviour, and Attitudes to Pornography are listed both as predictors of, and outcomes from, pornography viewing, as the largely cross-sectional research is inclusive about causation. They may function as either.
4.2 Aims
To confirm that the frequency data from control variables and the relationships between predictor
and outcome factors behave comparably with the past theory. This chapter hypothesises the
following:
• H1 – the frequency data for Viewing Prevalence (H1a), Age of 1st-Time Viewing (H1b),
Preferred Viewing Device (H1c), Viewing Intentionality (H1d), Religion (H1e), Gender (H1f)
and Sexualised Social Media Behaviour (H1g) will be comparable to past research.
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• H2 – the predictor factors will correlate with pornography viewing in the following way:
Parent Communication (H2a) and Parental Rules (H2b) will decrease when Viewing
Prevalence increases. Peer Attitudes (H2c) and Peer Behaviour (H2d) will increase when
Viewing Prevalence increases. Age of 1st-Time Viewing (H2e) and Viewing Intentionality
(H2f) would decrease when Viewing Prevalence increases.
• H3 – these primary outcome factors will correlate with pornography viewing in the following
way: Compulsivity will increase when Viewing Prevalence increases (H3a). Viewing Distress
will decrease when Viewing Prevalence increases (H3b). Negative Attitudes to Pornography
will decrease when Viewing Prevalence increases (H3c). Women as Sex Objects (H3d),
Uncommitted Sexual Explorations (H3e), and Sexualised Social Media Behaviours (SSMB)
(H3f) will increase when Viewing Prevalence increases.
• H4 – these secondary wellbeing factors will behave as follows: Self-Esteem (H4a), Emotional
Stability (H4b), Prosocial Conduct (Social Empathy) (H4c), Social Conduct (H4d), Parent
Relationships (H4e), and Peer Relationships (H4f) will decrease when Viewing Prevalence
increases. All six wellbeing factors, when combined into a Super-Wellbeing Factor, will
decrease when Viewing Prevalence increases (H4g).
Additionally, the data will be explored for unusual and novel findings, which may be considered for
integration into the intervention or future studies.
4.3 Method
The frequency data was analysed by gender and as totals. It was anticipated that a gender
distinction would be present in all variables. Additional t-tests were conducted comparing the
gender means of various factors, including for low and high frequency pornography viewers. The
frequency results were compared to other major studies, to provide a conclusion on whether
Hypothesis 1 holds.
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For analysis of Predictor factors, multiple regression analysis was performed on Viewing Prevalence.
Where the individual factor sample size was substantially different from other factors, it was
dropped from the regression analysis and instead analysed using simple linear regression.
For analysis of Outcome factors, simple linear regression was used to describe pornography’s effect.
Structural equation modelling on Distress from Viewing, using Religion as a modifier, was a helpful
way of resolving the predictions of Fernandez [1] and Wilt [2] (that it is independent of Compulsivity,
but is mediated by Religion).
For regression methodology, Ordinary Least Squares (OLS) regression analysis was applied in all
simple linear and multiple regression models, as explained in Chapter 3 (Section 3.4.1).
Lastly, a bivariate matrix of all factors (predictor and outcome) was analysed. Any unusual
correlations between factors, including ones not considered central to the intervention, were
explored, in case new research questions or ideas emerged.
All results with p value <0.05 were regarded a significant, recognising that in analyses which have a
very high number of variables, some results will be <0.05 just by chance. This significance test
benchmark is used in Chapters 7-9 also.
4.4 Results
4.4.1 Excluded control variables
An initial analysis of two control variables — Parental Employment and Parental Marital Status —
compared the demographics of student families to the national average. The frequency statistics for
both Parental Employment (Table 4.1.1) and Marital Status (Table 4.1.2) were difficult to compare to
the general population using Australian Bureau of Statistics 2016 Census data [3], since the census
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data cannot be isolated according to families of Year 10 students only. Census data included parents
of non-high-school students (younger and older), and senior aged parents, possibly explaining why
the proportion of widows or non-working couples differed. That said, some basic similarities can be
observed, including the proportion of single-income homes, the high percentage of combined
married/de facto couples, and divorced couples. When simple linear regression was conducted on
the Viewing Prevalence factor by these variables, neither showed a significant correlation (Parental
Employment p= 0.734; and Parental Marital Status p= 0.960). For these reasons, the two variables
are not considered in the subsequent Chapter 4 analysis. They will, however, be useful in Chapters
7–9, where the intervention study cohort can be compared to this cohort.
Table 4.1.1 Parental Employment
Students (N) % 2016 Census 2016 Census mean diff p-value Working Working Adults (N) Adults % One 174 23.3% 1,051,923 22.4% 0.01 0.78 Both 560 75.1% 2,374,062 50.5% 0.25 0.00 None 12 1.6% 1,270,842 27.1% -0.26 0.05 Total 746 100% 4,696,827 100% Note: The Census statistics includes the complete adult population, whilst the school sample is of families with active Year 10 students
Table 4.1.2 Parental Marital Status
Students % 2016 2016 mean p-value (N) Census Census diff Families (N) Families % Married 616 82.6% 5,557,897 60.8% 0.22 0.00 Divorced 76 10.2% 1,626,890 13.1% -0.03 0.44 De Facto 20 2.7% 1,637,547 13.2% -0.11 0.17 Widowed 7 0.9% 985,204 8.0% -0.07 0.49 Other 27 3.6% 608,059 4.9% -0.01 0.75 Total 746 100% 10,415,596 100% Note: The Census statistics includes the complete Australian population, whilst the school sample is of families with active Year 10 students.
4.4.2 Frequency results
The frequency results for control variables, and where relevant, their comparisons with other
studies, are reported below. 86
4.4.3 Age of First-Time Viewing
145 students out of 746 (19.4%), 58 out of 564 males (10.3%), and 87 out of 182 females (47.8%),
said they had never been exposed to pornography. The average Age of 1st-Time Viewing was 12.1
(males 12.1, females 12.3) from a possible age range between “5 and below” and “17 and above”
(coded 517, with “never” being 0) for students who had been exposed to pornography. 323 (43.3%)
of all students had been exposed by age 12, and 554 (74%) by age 14. In Lim’s 2017 study of young
Australians, the average male age was 13 and 16 for females [4]. However, as noted in Chapter 3,
other studies had male averages of 11 and female averages of 12 [5]. It can be concluded that the
1st-Time Viewing age for both males and females sit within a typical range and hypothesis (H1b) is
upheld.
4.4.4 Viewing Prevalence
Students were asked if they had viewed pornography in the previous six months using two questions
from Peter and Valkenburg’s Pornography Viewing Scale [6]: a. to pictures, videos etc of exposed
genitals; and b. of people engaging in actual sexual activity. Scores were added together then
averaged.
The findings in Table 4.2 are relatively consistent with Peter and Valkenburg’s original 2008 study
[6], and other studies [7], showing males are much more likely to watch pornography, and at higher
frequencies, than females. Alternatively, females are 3.8 times less likely to have ever watched
pornography than males, whereas males are 7.6 times more likely than females to watch
pornography at a weekly or more frequency. Lim’s recent Australian study of young people found
more excessive exposure – with only 1% of males (n = 258) and 32% of females (n = 683) never
having viewed pornography, whilst 84% of males and 19% of females viewed pornography weekly
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or more (noting the higher age range of 15–29) [4]. The results in Table 4.2 sit within the range of
these other studies. Therefore, hypothesis H1a is upheld.
Table 4.2 Viewing Prevalence Frequency Prevalence Table Male Female Total
Never 82 (14.5%) 101 (55.5%) 183 (24.5%)
Less than monthly 86 (15.2%) 43 (23.6%) 129 (17.3%)
Monthly 110 (19.5%) 24 (13.2%) 134 (18.0%)
More than once/month but less than once/week 122 (21.6%) 7 (3.8%) 129 (17.3%)
Weekly 117 (20.7%) 7 (3.8%) 124 (16.6%)
More than once/week but less than every day 37 (6.6%) 0 (0.0%) 37 (5.0%)
Daily 10 (1.8%) 0 (0.0%) 10 (1.3%)
Total 564 (100%) 182 (100%) 746 (100%)
Note: Question adapted from Peter and Valkenburg’s Pornography Exposure Scale [6].
4.4.5 Preferred Viewing Device
The Preferred Viewing Devices for pornography access were heavily weighted towards mobile
computer devices. Of note, males were weighted towards a phone preference, whilst females prefer
either phones, laptops or unspecified sources. These results appear similar to Lim’s 2017 study,
where 96% of males used either phones or computers and 90% of females used phones or
computers [38], therefore hypothesis H1c is upheld.
Table 4.3 Preferred Viewing Device Preferred Device Table Male Female Total
Phone 282 (58.0%) 33 (38.4%) 315 (55.1%)
Tablet/iPad 60 (12.3%) 10 (11.6%) 70 (12.2%)
Laptop 92 (18.9%) 21 (24.4%) 113 (19.8%)
Desktop 6 (1.2%) 1 (1.2%) 7 (1.2%)
TV 12 (2.5%) 6 (7.0%) 18 (3.1%)
Other 34 (7.0%) 15 (17.4%) 49 (8.6%)
Total 486 100% 86 100% 572 100% Note: Only one choice was given. 88
4.4.6 Viewing Intentionality
Viewing Intentionality was defined as whether a ‘normal’ encounter with pornography is intentional
or accidental. This single item, 5-Likert scale variable was used for longitudinal evaluation after
students did the education intervention. Table 4.4 shows that males were skewed towards
intentionality, whereas females were less intentional about accessing pornography.
Table 4.4 Viewing Intentionality Viewing Intentionality Male Female Total Never 129 (9%) 7 (58%) 136 (17%) Rarely 150 (16%) 6 (21%) 156 (16%) Sometimes 97 (19%) 7 (8%) 104 (18%) Usually 78 (30%) 19 (7%) 97 (26%) Always 46 (26%) 53 (8%) 99 (23%) Total 500 100% 92 100% 592 100% Note: This only includes students who had previously viewed pornography.
4.4.7 Sexualised Social Media Behaviours
Table 4.5 shows that the proportion of males likely to send sexualised content via social media was
slightly higher than females, but not significantly, p = 0.16. The proportion of girls likely to receive
sexualised content was slightly higher than males, but not significantly, p = 0.32. The final column
contains the original results from the 2013 National Survey of Australian Secondary Students and
Sexual Health, from which this scale was obtained [8], and have been included for comparison.
There are limitations for comparing results with the La Trobe study, firstly because in their study, La
Trobe combined Year 10–12 student data, whereas this study only reports Year 10 students. The
developmental difference between 15 year olds and 17–18 year olds is significant. Additionally,
technology advances in that period, particularly mobile apps like Instagram and Snapchat, which
were only emerging in 2013, have occurred. Notwithstanding these limitations, there were enough
similarities in the proportions of senders and receivers to uphold hypothesis H1g.
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Table 4.5 Sexualised Social Media Behaviour
Question Male Female Total La Trobe Never 340 (60%) 124 (68%) 464 (62%) (52%) Have you ever sent a sexually explicit Don't written text message? know 52 (9%) 18 (10%) 70 (9%) (5%) Yes 172 (30%) 40 (22%) 212 (28%) (43%) Never 275 (49%) 86 (47%) 361 (48%) (42%) Have you ever received a sexually Don't explicit written text message? know 45 (8%) 12 (7%) 57 (8%) (4%) Yes 244 (43%) 84 (46%) 328 (44%) (54%) Have you ever sent a sexually explicit Never 441 (78%) 152 (84%) 593 (79%) (72%) Don't nude or nearly nude photo or video of know 29 (5%) 3 (2%) 32 (4%) (3%) yourself? Yes 94 (17%) 27 (15%) 121 (16%) (26%) Have you ever sent a sexually explicit Never 498 (88%) 167 (92%) 665 (89%) (89%) Don't nude or nearly nude photo or video of know 24 (4%) 6 (3%) 30 (4%) (2%) someone else? Yes 42 (7%) 9 (5%) 51 (7%) (9%) Have you ever received a sexually Never 330 (59%) 101 (55%) 431 (58%) (56%) Don't explicit nude or nearly nude photo or know 38 (7%) 7 (4%) 45 (6%) (2%) video of someone else? Yes 196 (35%) 74 (41%) 270 (36%) (42%) Never 383 (68%) 159 (87%) 542 (73%) (74%) Have you ever used a social media site Don't for sexual reasons? know 50 (9%) 9 (5%) 59 (8%) (4%) Yes 131 (23%) 14 (8%) 145 (19%) (22%) Is sending and receiving naked pictures a Never 412 (73%) 156 (86%) 568 (76%) - Don't - normal thing your friends do with each know 102 (18%) 19 (10%) 121 (16%) other? Yes 50 (9%) 7 (4%) 57 (8%) - Never - Is sending naked pictures acceptable 279 (49%) 98 (54%) 377 (51%) Don't amongst close friends or people who are - know 139 (25%) 47 (26%) 186 (25%) in a relationship? Yes 146 (26%) 37 (20%) 183 (25%) - Total 564 (100%) 182 (100%) 746 (100%) n=2100+ Note: Questions 1-6 adapted from National Survey of Australian Secondary Students and Sexual Health 2013 [8].
4.4.8 Religion
Religion was a factor combined from two questions: a. “Religion is important to my family”; and b.
“Religion is important to me”. Table 4.6 shows 38% of adolescents described religion as “Mostly” or
“Always” important, and 39% described religion as “Rarely” or “Never” important. The Religion
factor (Table 4.6) was originally included only as a control variable, but will again be discussed below
in 4.5.8 as it correlates with many other factors. But regarding frequency, Religion compared
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favourably with the general Australian population as reported in the 2016 Census, where 52%
reported being Christian and 30% were not religious [9]. Therefore, hypothesis H1d is upheld. It
should be noted that all schools in this study identified as Christian, although there is no assumption
that a student or their family’s faith was Christian.
Table 4.6 Religion Total Religious Activity Male Female Total Never 162 (28.7%) 42 (23.1%) 204 (27.3%)
Rarely 130 (23.0%) 36 (19.8%) 166 (22.3%)
Sometimes 68 (12.1%) 28 (15.4%) 96 (12.9%)
Mostly 112 (19.9%) 34 (18.7%) 146 (19.6%)
Always 92 (16.3%) 42 (23.1%) 134 (18.0%) Total 564 (100%) 182 (84%) 746 (100%) Note: Religion is mostly or always important to 36% of males and 42% of females (38% total).
4.4.9 Gender
The relationships between gender and pornography-related attitudes and behaviours require deeper
analysis, not just because of the significant differences in prevalence of Viewing Prevalence, Viewing
Intentionality, Preferred Viewing Device and Sexualised Social Media Behaviours, but because, as
observed in Chapter 1, these differences generally reduce, the more pornography affects the user
[10, 11]. Table 4.7 shows a comparison of outcome factor means between genders (using a two-
sample t-test). Tables 4.8.1 and 4.8.2 compare predictor and outcome factor means between
genders, stratified into the groups “Low Pornography Viewers” (less than monthly viewing) and
“Regular Pornography Viewers” (monthly or more). The following observations can be made:
i. Males were more likely to engage with pornography than females and were more likely to
intentionally view pornography.
ii. Females were more likely to be influenced by Religion (p = 0.03).
iii. 10.3% of males and 47.8% of females reported never being exposed to pornography.
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iv. There were no significant differences for Age of 1st-Time Viewing of those who had viewed
pornography (average age 12.1 males, 12.3 females).
v. Females were more likely to face stricter Parental Rules about accessing pornography,
devices and social media. However, that was not true for the Regular Viewing group.
vi. Males were more likely to receive instructional communication from parents about
pornography culture (p = 0.01).
vii. Males were more likely to have peers who view pornography (p = 0.00). They were also more
likely than females to believe that their general peer group approves of pornography (p =
0.00), but there is no gender difference for Regular Viewers (p = 0.31). viii. Females were more likely to have negative attitudes to pornography (p = 0.00). However,
when comparing Regular Pornography Viewers, the gender difference became insignificant (p
= 0.36).
ix. Males were more likely to perceive themselves as having pornography Compulsivity
behaviours (p = 0.00). However, when comparing Regular Viewers, the gender difference
became insignificant (p = 0.07).
x. There were no significant differences in Viewing Distress between genders (p = 0.96).
xi. Males were more likely to entertain positive attitudes to Uncommitted Sexual Exploration (p
= 0.00). However, when comparing Regular Pornography Viewers, the gender difference
became insignificant (p = 0.17).
xii. Males were more likely to view Women as Sex Objects (p = 0.00), and this remained true
when comparing Regular Pornography Viewers (p = 0.00). However, when comparing genders
on the survey items “Pornography degrades women” and “Pornography degrades men”
(from the Attitudes to Pornography scale), the difference was statistically insignificant for
frequent pornography users (p = 0.96, 0.59 respectively). xiii. Males were more likely to engage in Sexualised Social Media Behaviours (p = 0.03), including
a moderately higher chance of sending sexualised content (p = 0.06), however there was no
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statistical gender difference between Frequent Pornography Viewers. Additionally, there was
a trend for females to receive sexualised content via social media, although this did not reach
statistical significance (p=0.16). xiv. Males were more likely to be emotionally stable (p = 0.00). This is consistent with past
research, which has frequently found that adolescent females generally have lower levels of
Emotional Stability and wellbeing than males [12] (independent of pornography viewing).
xv. Males were more likely to have higher Self-Esteem (p = 0.00), which is consistent with past
research [13]. xvi. Males were more likely to have better relationships with their parents (p = 0.00). xvii. Males were more likely to have better relationships with their peers (p = 0.02). xviii. Females were more likely to have better social empathy (p = 0.00), which has been observed
in the past [14, 15], although not consistently [16]. xix. There was no significant difference between the genders for Social Conduct (p = 0.48),
contrary to studies which have generally identified males as having poorer social behaviour
[17] .
xx. Overall, males reported having higher scores in the Super-Wellbeing index (p = 0.00), which
remained the case even when comparing Regular Pornography Viewers (p = 0.00).
The general trend in gender comparisons is that males are more likely than females to engage with
pornography, adapt negative attitudes and behaviours, and have peers who approve of and engage
with pornography, as predicted. However, for the regular pornography viewers, there were no
statistical differences for the predictor factors: Parental Rules and Peer Attitudes, nor for the
outcome factors: Compulsivity, Uncommitted Sexual Exploration, Sexualised Social Media
Behaviours, and Peer Relationships. The similarities in gender behaviours for Regular Viewers have
also been seen in the past, further supporting hypothesis H1f.
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All H1 hypotheses were confirmed, meaning that the prevalence data for the survey cohort is consistent with wider literature, making them a good reference for the design of the pilot education intervention.
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Table 4.7 Frequency and Outcome Factor Mean Differences between Males and Females Means Numbers (n=) t-tests Males Females Combined Males Females Total Mean Diff Std. Err. t-score df p-value Religion 0.4 0.5 0.5 564 182 746 -0.1 0.0 -2.13 744 0.03 Viewing Prevalence 0.4 0.1 0.3 564 182 746 0.3 0.0 13.79 744 0.00 1st-Time Viewing 12.1 12.3 12.1 506 95 601 -0.2 0.2 -0.92 599 0.36 Intentional Viewing 2.5 0.9 2.2 500 92 592 1.6 0.1 11.18 590 0.00 Attitudes to Porn 0.5 0.6 0.6 564 182 746 -0.1 0.0 -6.13 744 0.00
Compulsivity 0.2 0.1 0.2 502 94 596 0.2 0.0 5.17 594 0.00 Viewing Distress 0.3 0.3 0.3 500 93 593 0.0 0.0 -0.09 591 0.92 Uncommitted Sexual Exploration 6.6 5.0 6.2 564 182 746 1.6 0.3 5.84 744 0.00 Women as Sex Objects 8.7 5.6 7.9 564 182 746 3.1 0.3 10.58 744 0.00 Sexualised Social Media Behaviours 4.7 3.9 4.5 564 182 746 0.8 0.4 2.18 744 0.03 Have received sexual content 0.9 0.9 0.9 564 182 746 -0.1 0.1 -0.90 744 0.37 Have sent sexual content 0.5 0.4 0.5 564 182 746 0.1 0.1 1.90 744 0.06 Super Wellbeing Index 0.73 0.68 0.72 564 182 746 0.05 0.01 5.48 744 0.00 Emotional Stability 13.1 9.0 12.1 564 182 746 -4.2 0.5 -8.91 744 0.00 Self Esteem 22.2 19.8 21.6 564 182 746 2.4 0.4 -5.44 744 0.00 Parent Relationships 16.6 15.0 16.2 564 182 746 1.6 0.3 -5.01 744 0.00 Peer Relationships 7.9 7.6 7.9 564 182 746 0.3 0.1 -2.29 744 0.02 Prosocial Behaviour 7.4 7.9 7.5 564 182 746 -0.5 0.2 -3.29 744 0.00 Conduct 7.9 7.8 7.9 564 182 746 0.1 0.2 -0.72 744 0.47 Note: Female sample sizes for frequent pornography viewers are relatively small, reducing the reliability of mean comparisons.
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Table 4.8.1 Predictor Factor Mean Differences between Males and Females by Viewing Prevalence
Total Low Pornography (Less than monthly) Regular Pornography (Monthly or more) Male Female Male Female Male Female (n=564) (n=182) (n=202) (n=154) (n=362) (n=28) t- p- Mean SD= Mean SD= t-score p-value Mean SD= Mean SD= t-score p-value Mean SD= Mean SD= score value Parent Communication 3.82 3.66 3.01 3.52 2.62 0.01 4.76 3.96 3.21 3.60 3.80 0.00 3.30 3.38 1.93 2.91 2.09 0.04 Parental Rules 0.29 0.28 0.34 0.31 1.87 0.06 0.41 0.31 0.36 0.31 1.34 0.18 0.23 0.25 0.22 0.28 0.19 0.85 Peer Attitudes 3.33 1.89 2.19 1.78 7.13 0.00 2.23 1.80 1.94 1.68 1.56 0.12 3.94 1.64 3.61 1.71 1.03 0.31 Peer Behaviours 4.82 1.38 2.92 1.63 15.38 0.00 3.99 1.54 2.74 1.60 7.42 0.00 5.28 1.03 3.89 1.45 6.63 0.00
Table 4.8.2 Outcome Factor Mean Differences between Males and Females by Viewing Prevalence
Low Pornography Viewers Regular Pornography Viewers Males (n=) Females (n=) p-value Males (n=) Females (n=) p-value Religion 2.0 202 2.1 154 0.71 1.6 362 1.4 28 0.49 Viewing Prevalence 0.6 202 0.3 154 0.00 3.3 362 2.6 28 0.00 Attitudes to Porn 48.0 202 49.8 154 0.14 38.6 362 40.7 28 0.36 Compulsivity 0.1 142 0.0 66 0.01 0.2 360 0.1 28 0.07 Viewing Distress 1.8 139 1.7 65 0.77 1.4 361 1.3 28 0.64 Uncommitted Sexual Exploration 5.5 202 4.8 154 0.04 7.2 362 6.4 28 0.17 Women as Sex Objects 8.1 202 5.4 154 0.00 9.0 362 6.8 28 0.00 Sexualised Social Media Behaviours 2.4 202 3.3 154 0.02 5.9 362 7.2 28 0.15 Super Wellbeing Index 0.8 202 0.7 154 0.00 0.7 362 0.6 28 0.00 Emotional Stability 13.5 202 9.0 154 0.00 12.9 362 8.4 28 0.00 Self Esteem 22.6 202 19.9 154 0.00 22.0 362 19.5 28 0.01 Parent Relationships 17.1 202 15.3 154 0.00 16.4 362 13.6 28 0.00 Peer Relationships 8.0 202 7.6 154 0.04 7.9 362 7.6 28 0.39 Prosocial Behaviour 7.6 202 7.9 154 0.14 7.3 362 7.9 28 0.10 Conduct 8.3 202 8.0 154 0.11 7.7 362 6.8 28 0.01 Note: “Low” is defined as viewing pornography less than once monthly, and “Regular” is defined as viewing pornography once monthly or more. All p-values are all two-tail t-test mean comparisons. For the Wellbeing factors, a higher score means positive wellbeing. For Religion, a higher score means more religious engagement. For Attitudes to Pornography factor, a high score means less approving of pornography. For the Prevalence Viewing, Compulsivity, Viewing Distress, Uncommitted Sexual Exploration, Women as Sex Objects, and Social Media factors, a higher score means a poorer outcome
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4.5 Predictor Factor Results
The following section describes analysis on each predictor factor that will theoretically affect
Pornography Viewing Frequency. Additionally, where relevant, analysis was performed on the
relationships between various factors apart from Viewing Prevalence. This study theorised that key
influences of pornography viewing were: Age of First-Time Viewing, Gender, Parent Communication,
Parental Rules, Peer Attitudes, Peer Behaviours, Religion, and Viewing Intentionality. Two additional
outcome factors were included as possible influences on pornography viewing: Sexualised Social
Media Behaviour and Compulsivity. All factor scores in Tables 4.10 and 4.11 were indexed to a range
0 to 1. Tests for multicollinearity showed the factors were not highly correlated (VIF range 1.19–
1.96). Additionally, the Bivariate Correlation Matrix between all factors showed no correlation higher
than 0.64 (Table 4.9).
4.5.1 Age of First-Time Viewing
Students were asked about their Age of First-Time Viewing of pornography. If students indicated
that they had no previous exposure they were not asked about their Viewing Prevalence Frequency
or questions related to Compulsivity or Viewing Distress. When using a simple linear model, Age of
First-Time Viewing had a significant effect on Pornography Viewing (β = -0.04, p = 0.00, R = 0.11)
when analysing all students who have previously viewed pornography (n = 601). Thus, hypothesis
H2e is upheld.
4.5.2 Multiple and simple linear regression on Viewing Prevalence
When performing multiple regression analysis, the variables Age of First-Time Viewing and
Compulsivity were excluded due to having substantially less observations. Instead separate linear
regression was performed on them. Since Compulsivity is also assessed as an outcome factor, its
analysis is reserved for Table 4.11 with the other outcome factors.
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4.5.3 Gender
Table 4.10 showed that Gender had statistically significant influence on the prevalence of Viewing
Prevalence (β = -0.01, p=0.00, R= 0.24). Since males were coded “1” and females “2”, and males
were more likely to view pornography, the higher proportion of males in this study accounts for the
substantial contribution Gender has to the variability of Viewing Prevalence. With males more likely
to view pornography, this further supports hypothesis (H1f) as this was anticipated from previous
studies.
4.5.4 Parent Communication
When controlling for the other variables in the multiple-regression equation, Parent Communication
was insignificant (p=0.25). However, when applying simple linear modelling, Parent Communication
has a statically significant effect on Viewing Prevalence (β = -0.11, p=0.001, R= 0.015). Therefore,
hypothesis H2a is upheld.
4.5.5 Parental Rules
When controlling for the other variables in the multiple-regression equation, Parental Rules had a
significant effect on Viewing Prevalence (β = -0.31, p = 0.005). In a simple linear model, the effect
was also significant (β = –1.02, p = 0.00, R = 0.08). When Parental Communication was zero (n=233),
the effect of Parental Rules on Viewing Prevalence was even more significant (β = -1.53, p = 0.00, R =
0.06). Lastly, Parental Rules did not correlate with Self-Esteem, Emotional Stability, Parent
Relationships or Social Conduct. Therefore, hypothesis H2b is upheld.
4.5.6 Peer Attitudes
When controlling for the other variables in the multiple-regression equation, Peer Attitudes were
significant influencers on Viewing Prevalence (β = 0.19, p = 0.000). In a simple linear model, the
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effect was also significant (β = .45, p = 0.000, R = 0.29). Therefore, hypothesis H2c is upheld.
4.5.7 Peer Behaviour
When controlling for the other variables in the multiple-regression equation, Peer Behaviours were
significant influencers on Viewing Prevalence (β = 0.22, p = 0.00). In a simple linear model, the effect
was also significant (β = 0.55, p = 0.00, R = 0.33). Additionally, this result supports the previous
observation by Rasmussen [18] that peer descriptive normative behaviours are more influential on
pornography consumption than the more distant Peer Attitudes. Therefore, hypothesis H2d is
upheld.
4.5.8 Religion
When controlling for the other variables in the multiple-regression equation, Religion was not a
significant predictor of Viewing Prevalence (β = -0.03, p = 0.157 – See Table 4.9). Yet in a simple
linear model the effect was significant (β = 0.16, p = 0.00, R = 0.038). Furthermore, the bivariate
correlation matrix (Table 4.9) shows that Religion correlated significantly with Viewing Prevalence,
noting that only four factors did not correlate: Peer Behaviour, Peer Relationships, Emotional
Stability and Social Conduct. Therefore, hypothesis H1e is upheld.
4.5.9 Viewing Intentionality
Although used for longitudinal purposes, this item significantly correlated with Viewing Prevalence,
with a simple linear model showing a statistical significance (β = 0.11, p = 0.00, R = 0.39).
Additionally, Viewing Intentionality had a significant effect on increasing Compulsivity (β = 0.04, p =
0.00, R = 0.09), whilst conversely had a significant effect on decreasing Distress from Viewing (β = -
0.02, p = 0.01, R = 0.01). Therefore, hypothesis H2f is upheld.
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4.6 Outcome Factors Influenced by Pornography Viewing
The outcome factors hypothesised to be affected by pornography viewing frequency were analysed
using simple linear regressions (Table 4.11). Each is discussed separately below:
4.6.1 Attitudes to Pornography
A simple linear analysis of the effect of Viewing Prevalence showed the effect was significant (β =
-0.28, p = 0.00, R = 0.21). Additionally, this factor performed consistently with past research [19].
Therefore, hypothesis H3c is upheld.
4.6.2 Women as Sex Objects
A simple linear analysis of the effect of Viewing Prevalence showed the effect was significant (β =
0.21, p = 0.00, R = 0.09). That is, the higher the Viewing Prevalence frequency, the Women as Sex
Objects factor increased. This factor also performed consistently with past research [20]. Therefore,
hypothesis H3d is upheld.
4.6.3 Uncommitted Sexual Exploration
A simple linear regression model showed that the effect of Viewing Prevalence on Uncommitted
Sexual Exploration was significant (β = 0.25, p = 0.00, R = 0.11) as predicted. An alternative multiple
regression model involving all independent variables in Table 4.10 on this factor showed the most
significant factors affecting it were Peer Attitudes (β = 0.22, p = 0.00), Parental Rules (β = -0.37, p =
0.002), Distress from Viewing (β = -0.11, p = 0.001) and Religion (β = -0.07, p = 0.004). There was
significant bivariate correlation with most other factors (Table 4.9). However, Peer Relationships,
Self-Esteem and Emotional Stability had no significant effect on attitudes to Uncommitted Sexual
Exploration. Notwithstanding these additional correlations, hypothesis H3e is upheld, because
Uncommitted Sexual Exploration positively correlated with Viewing Prevalence means.
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4.6.4 Compulsivity
A simple linear analysis of the effect of Viewing Prevalence on Compulsivity showed the effect was
significant (β = 0.31, p = 0.00, R = 0.17) and positive. Therefore, hypothesis H3a is upheld.
Conversely, the bivariate matrix showed that both Parental Rules and Communication had no
significant correlation with Compulsivity, nor did Social Conduct, Social Empathy, and Sexualised
Social Media Behaviour.
4.6.5 Distress from Viewing
A simple linear analysis of the effect of Viewing Prevalence on Distress from Viewing showed the
effect was significant (β = -0.11, p = 0.01, R = 0.01) and negative. Therefore, hypothesis H3b is
upheld. Furthermore, when Structural Equation Modelling (SEM) path analysis was applied to
analyse the effect of Viewing Prevalence on Distress from Viewing using Religion as an effect
modifier, the direct effect of Viewing Prevalence was only moderately significant (β = -0.08, p = 0.05)
and the indirect effect was more significant (β = -0.03, p = 0.01), whilst the direct effect of Religion
was significant (β = 0.15, p = 0.00). Therefore, the effect of Viewing Prevalence on Distress from
Viewing is mostly mediated by the Religion Factor.
4.6.6 Emotional Stability
All items in the following six wellbeing subscales were totalled, then indexed to 0–1 (although the
unindexed totals were kept for the Gender comparisons in Table 4.6). Linear regression modelling
showed that an increase in Viewing Prevalence correlated with more stable emotions (β = 0.07, p =
0.024). This is contrary to expectation and, therefore, hypothesis H4b is rejected.
4.6.7 Parent Relationships
Linear regression modelling showed that Viewing Prevalence had no significant effect on Parent
Relationships (p = 0.250). Therefore, hypothesis H4e is rejected. All the other wellbeing factors,
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however, were significantly correlated with Parent Relationships in a positive direction, as were
Compulsivity, Distress and Religion (Table 4.9). Parental Rules and Communication did not correlate.
Although Viewing Prevalence did not influence this factor, an alternative simple linear regression on
the effect of Parent Relationships on Sexualised Social Media Behaviours (β = -0.13, p = 0.00, R =
0.03) showed that a healthy parental relationship has a significant reducing effect.
4.6.8 Self-Esteem
Linear regression modelling showed that Viewing Prevalence had no significant effect on Self-Esteem
(p = 0.75). Therefore, hypothesis H4a is rejected. Table 4.9 showed that Self-Esteem was negatively
correlated (p < 0.05) with Sexualised Social Media Behaviour, Compulsivity and Viewing Distress. It
was positively correlated with Peer Attitudes, Religion, and the five other wellbeing factors.
4.6.9 Social Conduct
A simple linear regression showed Viewing Prevalence had a significant negative effect on Social
Conduct (β = -0.12, p = 0.00, R = 0.03) as predicted. Therefore, hypothesis H4d is upheld. The
bivariate factor matrix showed that most factors significantly correlated with Social Conduct (as
expected), but Parental Rules, Parent Communication and Religion were not correlated.
4.6.10 Peer Relationships
A simple linear regression between Peer Relationships and Viewing Prevalence showed an
insignificant effect (p = 0.86). Therefore, hypothesis H4f is rejected.
4.6.11 Social Empathy
A simple linear regression of Social Empathy by Viewing Prevalence showed this significantly
declined (β = -0.10, p = 0.00, R = 0.02) as expected. Therefore, hypothesis H4c is upheld. The
bivariate matrix shows that most factors correlate significantly in the direction that indicates healthy
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behaviours, apart from Parental Rules, Parent Communication, and Sexualised Social Media
Behaviour, which have no significant effect.
4.6.12 Sexualised Social Media Behaviour (SSMB)
A simple linear regression of SSMB by Viewing Prevalence showed a significant positive relationship
(β = 0.41, p = 0.00, R = 0.17) as predicted. Therefore, hypothesis H3f is upheld. Table 4.9 also shows
no correlation between SSMB and Viewing Distress, Self-Esteem, Emotional Stability, Social Empathy
and Peer Relationships.
4.6.13 Super-Wellbeing
When a simple linear model was run on the combined Super-Wellbeing factor with Viewing
Prevalence as an independent variable, the result was insignificant (β = 0.03, p = 0.10). Therefore,
hypothesis H4g is rejected.
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Table 4.9 Bivariate correlation matrix between all latent factors
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Bivariate correlation matrix between factors
1 * Viewing Prevalence Uncommitted Sexual Exploration 2 0.34* *
Sexual Objectification of Women 3 0.31* 0.47* *
Attitudes to Pornography 4 -0.46* -0.45* -0.51* *
Parent Communication 5 -0.12* -0.15* -0.10* 0.31* *
Parental Rules 6 -0.28* -0.18* -0.09* 0.31* 0.54* *
Peer Behaviour 7 0.57* 0.28* 0.31* -0.34* 0.01 -0.17* *
Peer Attitudes 8 0.54* 0.44* 0.35* -0.64* -0.28* -0.34* 0.54* *
Distress from Viewing 9 -0.11* -0.21* -0.16* 0.37* 0.30* 0.27* -0.07 -0.35* *
Compulsivity 10 0.42* 0.16* 0.20* 0.14* 0.05 0.04 0.27* 0.14* 0.27* *
Religion 11 -0.20* -0.28* -0.13* 0.28* 0.23* 0.28* -0.06 -0.32* 0.21* 0.10* *
Parent Relationships 12 -0.04 -0.13* -0.03 0.12* 0.05 -0.00 0.05 -0.10* -0.09* -0.10* 0.13* *
Self-Esteem 13 0.01 -0.02 0.05 0.05 0.07 0.01 0.14* -0.00 -0.09* -0.14* 0.08* 0.46* *
Emotional Stability 14 0.08* 0.03 0.19* -0.13* -0.01 -0.02 0.14* 0.05 -0.17* -0.12* -0.02 0.25* 0.34* *
Social Empathy 15 -0.15* -0.14* -0.18* 0.14* 0.11* 0.08* -0.09* -0.14* 0.04 -0.02 0.20* 0.24* 0.33* 0.01 *
Social Conduct 16 -0.17* -0.13* -0.15* 0.13* 0.04 0.04 -0.12* -0.14* -0.03 -0.20* 0.03 0.31* 0.29* 0.18* 0.26* *
Peer Relationships 17 0.01 0.7 0.10* -0.04 -0.02 -0.11* 0.06* 0.03 -0.16* -0.14* -0.03 0.24* 0.39* 0.30* 0.21* 0.17* *
Sexualised Social Media Behaviour 18 0.41* 0.29* 0.22* -0.32* -0.07* -0.17* 0.37* 0.35* -0.07 0.21* -009* -0.18* -0.06 -0.00 -0.06 -0.28* 0.04 *
Note: Super-Wellbeing is not included as it is a higher order latent factor; *p < 0.05.
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Table 4.10 Predictor Factors that Contribute to Pornography Viewing Prevalence Factor β SE t-score p-value Std. β*
Gender -0.91 0.11 -7.93 0.00 -0.24
Religion -0.04 0.03 -1.20 0.23 -0.03
Parent Communication 0.00 0.01 0.18 0.86 0.01
Parental Rules -0.49 0.18 -2.74 0.01 -0.09
Peer Attitudes 0.23 0.03 3.96 0.00 0.23
Peer Behaviour 0.13 0.04 6.41 0.00 0.16
Sexualised Social Media Behaviour 0.07 0.01 6.65 0.00 0.19
Negative Attitudes about Pornography -0.02 0.00 -3.61 0.00 -0.13
Note: Multiple regression analysis with Pornography Viewing as the dependent factor; N = 746; Total R2 = 050. * Beta coefficients are standardised.
Table 4.11 Outcome Factors Affected by Pornography Viewing Prevalence
Factor β SE t-score p-value R2
Attitudes to Pornography -0.28 0.02 -14.1 0.000 0.21
Sexual Objectification of Women 0.21 0.02 8.79 0.000 0.09
Uncommitted Sexual Exploration 0.25 0.03 9.71 0.000 0.11
Social Empathy -0.10 0.02 -4.19 0.000 0.02
Parent Relationships 0.03 0.03 1.15 0.250 0.00
Peer Relationships 0.00 0.02 -0.18 0.857 0.00
Self-Esteem -0.01 0.02 -0.32 0.752 0.00
Emotional Stability 0.07 0.03 2.27 0.024 0.01
Social Conduct 0.12 0.02 4.75 0.000 0.03
Compulsivity 0.31 0.03 11.16 0.000 0.17
Distress from Viewing -0.11 0.04 -2.59 0.010 0.01 Sexualised Social Media Behaviour 0.41 0.03 12.41 0.000 0.17
Super-Wellbeing Index 0.03 0.02 1.63 0.103 0.00 Note: N = 746, OLS Simple Linear Regression with Pornography Viewing as regressor
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4.7 Discussion
The study sought to confirm that the frequency data from control variables, and the relationships
between predictor and outcome factors with pornography viewing, would behave consistently with
the research of Chapter 1. There were 27 hypotheses in total. Five of the H4 hypotheses were rejected:
Emotional Stability, Parent Relationships, Self-Esteem, Peer Relationships, and Super-Wellbeing. Some
consideration as to why these factors failed to behave as predicted is given below, however overall
the results confirm the study cohort are representative of typical adolescents, and the survey reliably
describes the interaction between predictor and outcome factors with exposure to pornography.
4.7.1 Control Variables
All H1 hypotheses were confirmed, meaning that the prevalence data for the survey cohort is
consistent with wider literature, making them a good reference for the design of the pilot education
intervention.
The observation that around 30% of students had sent a sexual message, and 44% had received one,
may raise concern for parents and educators, as this behaviour may be outside the law. Often
described as ‘Sexting’, Sexualised Social Media Behaviours (SSMB) pose potential risks for both the
sender and receiver, including the illegal distribution of child pornography [21]. This is a worldwide
phenomenon. For example, emerging research on SSMBs [22, 23] suggests that up to 69% of females
(average age of 14) have sent a form of “sext”, whilst up to 77% have received one. For males, up to
46% have sent a sext, and up to 58% have received one. As already noted, the Australian context is
similar, with the National Survey of Australian Secondary Students and Sexual Health [8] describing
similar prevalence in a large sample of students aged 14–18. Since the prevalence of SSMB is
substantial (Table 4.5), and it correlates with pornography viewing and the primary outcome factors
(Table 4.9), the pilot program should address these additional risks, behaviours and attitudes.
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This study shows significant gender differences in attitudes and behaviours related to pornography,
sexuality, psychology and relationships. This study shows that when pornography use increases,
differences in behaviour between males and females become less marked. This supports previous
observations [11, 20, 24] that females are likely to adopt “less-progressive gender role attitudes”,
and attach their identity to their sexuality as they increase consumption of pornography. It also
shows that males are more at risk of increased exposure to pornography. However, once exposure
occurs, there is equal risk to both males and females for the various negative effects analysed in this
survey. In designing the education program, and when performing analysis of pre- and post-
intervention data, these gender differences should be considered. It may be appropriate to establish
multiple strands in the intervention that can isolate specific factors that are likely to address the
respective genders. That said, there are no statistical differences between the genders for students
who view pornography frequently in their attitudes toward uncommitted sexual exploration,
compulsivity behaviours, sexualised social media behaviours, and attitudes toward pornography
(which includes additional items about sexual objectification of women). This is a compelling
argument for the damage pornography does to a teenager, regardless of their gender, since it is the
frequency of exposure that correlates with these other negative outcomes, not gender. Thus,
reducing the risk of exposure for all adolescents, male and female, is a clear imperative.
4.7.2 Predictor Factors
As theorised, all H2 predictor factors significantly correlated with Pornography Viewing, with
Parental Rules, Peer Attitudes and Peer Behaviours having the most influence. It stands that any
intervention seeking to reduce negative behaviours and attitudes related to pornography viewing
and sexualised social media behaviours, should incorporate strategies involving parental
engagement and peer interaction.
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The observation that Parental Rules contributed more to reduced pornography viewing than Parent
Communication is important for this study. This contradicts theories by Rasmussen [18] and Weber
[25] that it would be less effective. Moreover, Parental Rules appear effective without negatively impacting the wellbeing factors of their child (Table 4.9). Indeed, as Parental Rules increased, so did
Social Empathy. Furthermore, the correlation between increased rules and a reduction in their peers’ positive porn-related attitudes and behaviours, and general peer relationships, could suggest parents may be able to influence the type of friends the student keeps. Parents should be informed about the potential benefits of regulating their child’s access to devices, the internet, and social media.
The observation that Peer Behaviours is more influential on viewing behaviours than Peer Attitudes provides an opportunity for the intervention to isolate and separate the two influences. If students can work closely together and engage in critical thinking about the normative beliefs and expectations of the wider peer group, they may succeed in challenging Peer Attitudes, and together create a new narrative that is more influential on their behaviours.
Lastly, as mentioned in 4.2, the Religion factor was intended as a control variable only (to compare the demographics of students to wider populations). However, since it correlates with Pornography
Viewing, and all other factors in Table 4.8 except Peer Behaviour, Peer Relationships, Emotional
Stability and Social Conduct, it may present additional opportunities to moderate student behaviours and attitudes. There is no intention to include ‘religious’ elements in the pilot program for this thesis. However, parents, educators and policy makers may factor this into their own strategies for improving youth health and behaviour. Also, for future research, it is curious why
Emotional Stability and Social Conduct were unaffected, since one would assume Religion would enhance moral frameworks and existential certainty.
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4.7.3 Outcome Factors
All H3 hypotheses were confirmed. Pornography Viewing had an expected effect on the primary
outcome factors, but not three of the H4 secondary factors: Parent Relationship, Peer Relationships,
and Self-Esteem, which were not affected. Emotional Wellbeing was significantly affected, but in the
alternative direction. This warrants further investigation. The high correlation of the predictor Peer
Attitudes and Peer Behaviours factors suggest that pornography viewing behaviours may be
normalised, or socially desirable amongst peers, such that the classical assessment that people use
pornography because they are depressed or lonely is no longer the case (as described in 1.4.2.b in
Chapter 1). Another unexplored factor is narcissism, which has been observed to increase since the
advent of social media culture [26]. This is considered below when addressing Self-Esteem.
One striking observation from the bivariate correlation matrix (Table 4.9) is that the coefficient
between Attitudes to Pornography and Peer Attitudes is the highest within all factor relationships
(-0.64). This amplifies the potential influence of peer-group normalisation, and suggests that critical
thinking about pornography culture, and other knowledge-related elements from the Attitudes to
Pornography scale, could be particularly effective in peer-to-peer activities.
Regarding Compulsivity, this study was uncertain about whether it was a predictor or outcome
factor. The high correlation between Compulsivity and Pornography Viewing means the efforts to
determine this should be expanded. If it is a predictor, it may complicate an easy fix for problematic
behaviours, since behavioural addictions are difficult to address without specialised therapies.
Additionally, determining if the student’s self-assessment of having compulsive behaviours is a
subjective perception, or an objective description, cannot be concluded from a cross-sectional study.
In a recent study, Fernandez also showed that this Compulsivity factor was more than just a
perceived compulsion, but an objective description of a compulsive behaviour [1]. Whether
Compulsivity is a predictor factor and an actual behaviour, may be determined by incorporating
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Fernandez’s “Abstinence Efforts” item into the survey. If, hypothetically, a student increases effort to abstain from viewing pornography, but also fails to reduce their viewing frequency, then the nature of Compulsivity will be better understood, and additional strategies for addressing problematic behaviours may arise.
The relationship between Distress from Viewing and Religion, where the latter mediates an indirect effect, reinforces earlier observations that Religion may be a consideration for addressing problematic behaviours and attitudes. In line with Wilt’s observations [2], religion seems to enhance the moral compass of a student, which may improve chances of positive change.
As previously noted, four of the wellbeing factors did not behave as expected. Yet even Social
Conduct, which did correlate with Pornography Viewing, did not positively correlate with Parental
Rules, Parent Communication, or Religion. This should be concerning to parents and educators, because an environment of guidance and education may not impact the social conscience of the teenager.
The observation that Self-Esteem failed to decrease when Pornography Viewing increased is inconsistent with past research [27], as is the increase of Emotional Stability. Furthermore, as
Emotional Stability increased, so did Sexual Objectification of Women (Table 4.9). These results are counterintuitive. One emerging theory is that an increase in self-promoting social media behaviours, which has been observed in other studies to be an increasing phenomenon amongst young people, may fuel unhealthy levels of narcissism [26, 28, 29], distorting the adolescent’s self-esteem, self- concept, and identify formation. To resolve these questions, the intervention should give consideration to the interplay between self-media behaviours, narcissism, self-esteem and pornography or sexualised social media behaviours.
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The finding in this study (of the lack of correlation between Pornography Viewing and Parent
Relationship) was inconsistent with past research [24, 30]. Furthermore, the observation in Table 4.9 that both Parental Rules and Parent Communication do not correlate with Parent Relationships, suggests there may be a disconnect between what parents think is going on and what the actual behaviour of their child is. This lack of correlation is in contrast with Sexualised Social Media
Behaviour, where a healthy parental relationship has a significant reducing effect (even though it does not reduce Pornography Viewing). Could the contrast be down to Social Media behaviours being more public and thus more discoverable by parents? For future studies, it would be helpful to seek clarity about: what the student thinks their parent’s attitude to Pornography Viewing is; whether the student conceals the use of pornography from their parents; and whether a deeper understanding about these issues would affect the quality of the student’s relationship with their parents.
The lack of correlation between Peer Relationships and Pornography Viewing appears less surprising when coupled with the observation that Peer Attitudes and Behaviours affect a student’s viewing behaviours. If pornography viewing is thoroughly normalised and a mutually acceptable part of peer culture, a revision of how private pornography viewing affects friendships is warranted. There is no evidence that students turn to pornography because they lack friends, are having friendship problems, or coping with relationship difficulties (noting again that Parent Relationships are similarly unaffected). Reinforcing this normalisation theory, Sexualised Social Media Behaviour is also uncorrelated with Peer Relationships (Table 4.9).
Lastly, the lack of correlation between the Super-Wellbeing factor and Pornography Viewing is, in hindsight, unsurprising once the reverse effect of some subscales is included. This doesn’t reduce its value, because an important measure of the intervention will be whether overall wellbeing is altered
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after doing the program. Any negative change in overall well-being would be a serious concern
about the value of doing the program.
4.8 Conclusion
The survey has demonstrated an internal validity and capacity to produce data consistent with wider
research. It is an appropriate tool to measure a broad range of causes and effects from adolescent
pornography exposure. The data demonstrates how ubiquitous pornography and sexualised social
media behaviours are amongst adolescents. It is not a remote threat, but a present reality for most
males and many females. Pornography’s negative influence on attitudes, behaviours, and general
wellbeing is unquestionable.
In the context of a society increasingly sensitive to objectifying women, sexual harassment, domestic
violence, and unlawful sexual conduct via social media, addressing these threats through focussed
education, parental engagement, peer-group involvement, and responsible digital device
management, are a minimum response by all responsible for the welfare and shaping of young
people.
Clearly parents and schools need to be alert to the risk these devices pose for accessing
pornography. Parental rules about device and internet access play the largest part in mitigating the
risk from pornography exposure. Additionally, the influence of peer attitudes and behaviours for
pornography-related behaviours, in the context of high social media usage, present additional
challenges for parents and education providers in addressing holistic responses to the topic.
Another challenge is that of compulsivity. The reality for many users of pornography is that they
can’t stop. This could partly be due to a change in neurological pathways. As observed in Chapter 1,
research is emerging that suggests the brains of compulsive pornography users mirror the brains of
112 drug addicts (for example see Voon [31], Love [32], Kühn [33], Hilton [34], Brand [35], and Schmidt
[36]). Alterations to the Limbic system, grey and white brain matter, and prefrontal cortex functionality, prompt serious, clinical attention. Students could benefit from psychotherapies, for example Cognitive Behavioural Therapies [37], or other similar interventions [37]. At any rate, some strategy involving school counselling services should be made available for individuals who display compulsive behaviours.
For the wellbeing factors that failed to behave as expected, some alternative theories offer credible explanations:
a. the prevalence of pornography in the media, culture, and amongst peer-groups, is now
normalised in the adolescent’s life. Hence, parent and peer relationships, self-esteem and
distress, are no longer negatively impacted, and the teenager’s conscience, or sense of guilt,
is simply unaffected;
b. a reason that pornography appears to positively affect some wellbeing aspects, like self-
esteem, is narcissism, particularly enhanced by excessive social media use. A teenager’s
identity is increasingly bound by their image, including sexual identity, such that sexualised
behaviour may empower their sense of worth. More research is required to understand this
phenomenon, but since pornography use increases sexualised social media behaviour, and
peer influences greatly affect pornography use, the relationship between pornography,
social media, narcissism, and self-esteem may be interconnected.
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4.9 Chapter References
1. Fernandez, D.P., E.Y.J. Tee, and E.F. Fernandez, Do Cyber Pornography Use Inventory-9 Scores Reflect Actual Compulsivity in Internet Pornography Use? Exploring the Role of Abstinence Effort. Sexual Addiction & Compulsivity, 2017. 24(3): p. 156-179. 2. Wilt, J.A., et al., Associations of Perceived Addiction to Internet Pornography with Religious/Spiritual and Psychological Functioning. Sexual Addiction & Compulsivity, 2016. 23(2-3): p. 260-278. 3. Australian Bureau of Statistics, 2016 Census: People — demographics & education, viewed 1 May 2020, https://quickstats.censusdata.abs.gov.au/census_services/getproduct/census/2016/quicksta t/036 4. Lim, M.S.C., et al., Young Australians' Use of Pornography and Associations with Sexual Risk Behaviours. Australian and New Zealand Journal of Public Health, 2017: p. n/a-n/a. 5. Peter, J. and P.M. Valkenburg, Adolescents and Pornography: A Review of 20 Years of Research. The Journal of Sex Research, 2016. 53(4-5): p. 509-531. 6. Peter, J. and P.M. Valkenburg, Adolescents' Exposure to Sexually Explicit Internet Material, Sexual Uncertainty, and Attitudes Toward Uncommitted Sexual Exploration: Is there a Link? Communication Research, 2008. 35(5): p. 579-601. 7. Flood, M. and C. Hamilton, Youth and Pornography in Australia: Evidence on the extent of exposure and likely effects. 2003. 8. Mitchell, A., et al., National Survey of Australian Secondary Students and Sexual Health 2013. Melbourne: Australian Research Centre in Sex Health and Society & La Trobe University, 2014. 9. Australian Bureau of Statistics, 2016 Census: Religion, viewed 27 September 2018, http://www.abs.gov.au/AUSSTATS/[email protected]/mediareleasesbyReleaseDate/7E65A14454055 1D7CA258148000E2B85 10. Wright, P.J., R.S. Tokunaga, and A. Kraus, A Meta-Analysis of Pornography Consumption and Actual Acts of Sexual Aggression in General Population Studies. Journal of Communication, 2016. 66(1): p. 183-205. 11. Bonino, S., et al., Use of Pornography and Self-reported Engagement in Sexual Violence Among Adolescents. European Journal of Developmental Psychology, 2006. 3(3): p. 265-288. 12. Bluth, K., et al., Age and Gender Differences in the Associations of Self-compassion and Emotional Well-being in a Large Adolescent Aample. Journal of Youth and Adolescence, 2017. 46(4): p. 840-853. 13. Quatman, T. and C.M. Watson, Gender differences in adolescent self-esteem: An exploration of domains. The Journal of genetic psychology, 2001. 162(1): p. 93-117. 14. Garaigordobil, M., A Comparative Analysis of Empathy in Childhood and Adolescence: Gender Differences and Associated Socio-emotional Variables. International Journal of Psychology and Psychological Therapy, 2009. 9(2): p. 217-235. 15. Van der Graaff, J., et al., Perspective Taking and Empathic Concern in Adolescence: Gender Differences in Developmental Changes. Developmental Psychology, 2014. 50(3): p. 881-888. 16. McMahon, S.D., J. Wernsman, and A.L. Parnes, Understanding Prosocial Behavior: The Impact of Empathy and Gender Among African American Adolescents. Journal of Adolescent Health, 2006. 39(1): p. 135-137. 17. Nilsson, E.L., Analyzing Gender Differences in the Relationship between Family Influences and Adolescent Offending among Boys and Girls. Child Indicators Research, 2017. 10(4): p. 1079- 1094. 18. Rasmussen, E.E., et al., The Relation Between Norm Accessibility, Pornography Use, and Parental Mediation Among Emerging Adults. Media Psychology, 2016. 19(3): p. 431-454. 19. Evans-DeCicco, J.A. and G. Cowan, Attitudes Toward Pornography and the Characteristics Attributed to Pornography Actors. Sex Roles, 2001. 44(5): p. 351-361.
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20. Peter, J. and P.M. Valkenburg, Adolescents’ Exposure to a Sexualized Media Environment and Their Notions of Women as Sex Objects. Sex Roles, 2007. 56(5): p. 381-395. 21. Office_of_the_eSafety_Commissioner, Sexting: Social and Legal Consequences ed. C. Schmidt. 2016: Australian Government. 22. Morelli, M., et al., Sexting Behaviors and Cyber Pornography Addiction Among Adolescents: the Moderating Role of Alcohol Consumption. Sexuality Research and Social Policy, 2017. 14(2): p. 113-121. 23. Stanley, N., et al., Pornography, Sexual Coercion and Abuse and Sexting in Young People’s Intimate Relationships. Journal of Interpersonal Violence, 2016: p. 0886260516633204. 24. Owens, E.W., et al., The Impact of Internet Pornography on Adolescents: A Review of the Research. Sexual Addiction & Compulsivity, 2012. 19(1-2): p. 99-122. 25. Weber, M., O. Quiring, and G. Daschmann, Peers, Parents and Pornography: Exploring Adolescents’ Exposure to Sexually Explicit Material and Its Developmental Correlates. Sexuality & Culture, 2012. 16(4): p. 408-427. 26. McCain, J.L. and W.K. Campbell, Narcissism and Social Media Use: A Meta-Analytic Review. 2016. 27. Kor, A., et al., Psychometric development of the Problematic Pornography Use Scale. Addictive Behaviors, 2014. 39(5): p. 861-868. 28. Andreassen, C.S., S. Pallesen, and M.D. Griffiths, The Relationship Between Addictive Use of Social Media, Narcissism, and Self-esteem: Findings from a Large National Survey. Addictive Behaviors, 2017. 64: p. 287-293. 29. Pantic, I., et al., Association Between Physiological Oscillations in Self-esteem, Narcissism and Internet Addiction: A Cross-sectional Study. Psychiatry Research, 2017. 258: p. 239-243. 30. Ybarra, M.L., et al., X-rated Material and Perpetration of Sexually Aggressive Behavior Among Children and Adolescents: Is There a Link? Aggressive Behavior, 2011. 37(1): p. 1-18. 31. Voon, V., et al., Neural Correlates of Sexual Cue Reactivity in Individuals with and without Compulsive Sexual Behaviours. PLoS ONE, 2014. 9(7): p. e102419. 32. Love, T., et al., Neuroscience of Internet Pornography Addiction: A Review and Update. Behavioral Sciences, 2015. 5(3): p. 388. 33. Kühn, S. and J. Gallinat, Brain Structure and Functional Connectivity Associated with Pornography Consumption: The Brain on Porn. JAMA Psychiatry, 2014. 71(7): p. 827-834. 34. Hilton, D.L. and C. Watts, Pornography Addiction: A Neuroscience Perspective. Surgical Neurology International, 2011. 2(1): p. 19. 35. Brand, M., et al., Integrating Psychological and Neurobiological Considerations Regarding the Development and Maintenance of Specific Internet-use Disorders: An Interaction of Person- Affect-Cognition-Execution (I-PACE) Model. Neuroscience & Biobehavioral Reviews, 2016. 71(Supplement C): p. 252-266. 36. Schmidt, C., et al., Compulsive Ssexual Behavior: Prefrontal and Limbic Volume and Interactions. Human Brain Mapping, 2017. 38(3): p. 1182-1190. 37. Waldron, H.B. and Y. Kaminer, On the Learning Curve: The Emerging Evidence Supporting Cognitive-behavioral Therapies for Adolescent Substance Abuse. Addiction (Abingdon, England), 2004. 99 Suppl 2(s2): p. 93.
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Chapter 5: Study Protocol for Education Pilot
5.1 Introduction
This chapter describes the design and implementation of the study protocol for a school-based
intervention aiming to reduce the negative effects of pornography and sexualised social media
behaviours. The protocol includes the processes for developing the teaching content of the program,
recruiting subjects for the study, implementing the program, and obtaining quantitative and
qualitative data for analysis.
5.2 Chapter Synopsis
Background: The baseline survey, built from the background research of Chapters 1 and 2, and
designed and validated in Chapter 3, enabled analysis which confirmed both the relationships
between pornography exposure and negative outcomes, whilst establishing the modifying effect to
viewing prevalence by parental and peer influences.
The analysis of baseline survey data in Chapter 4, hereafter referred to as the “2018 survey data”,
confirmed that the parental and peer predictor factors, as well as the Attitudes to Pornography
knowledge-based factor, significantly correlated with pornography viewing prevalence, and most
negative-effect outcome factors. Subsequently the intervention utilised a three-fold strategy with
peer engagement, parental engagement, and didactic content being the primary methods for
modifying knowledge, attitudes and behaviours. Additionally, with the unresolved questions about
social media behaviours, narcissism, and their relationships to self-esteem and sexualised media
engagement, the intervention included content addressing these issues. The program was
implemented in an Australian independent schools context, using students in Year 10, conforming to
National Curriculum’s Health and Physical Education (HPE) strand.
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Aim: The study aimed to create, implement, and empirically measure the effectiveness of a pilot
education intervention aimed at Year 10 age, in conformity with the National Curriculum’s Health
and Physical Education strand.
Method: The six-lesson pilot was developed from content derived from published research in
consultation with schools, parents, and Year 10 youth. The consultation period involved dialogue
about the revised iterations of the lessons until a consensus of approval was achieved on a final
draft. Invitations to independent schools in NSW were sent, with a response of 5–10 schools
expected. The pilot was run between May–September 2019. Opt-out parental consent was required.
A baseline survey was conducted at the commencement of the pilot, and within six weeks of the
completion of the pilot.
Data Analysis: Quantitative analysis was conducted on the survey data, including linear and multiple
regression analysis, t-tests, and mean comparisons. Qualitative data was obtained about the
program’s implementation, including the preparation phase, the teaching experience, and the
follow-up processes with students, researchers, and families.
5.3 Background to Study
5.3.1 Prevalence data from a recent study
In the recent baseline survey validation study in May and June 2018 (Chapter 4), the data showed
consistency with most of the theories identified in Chapters 1 and 2. For example, 70% of male
students and 21% of female students view pornography monthly or more. Females are 3.8 times
more likely never to have watched pornography, whilst males are 7.6 times more likely to watch
pornography at extreme frequencies (weekly or more). These results are consistent with other
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contemporary adolescent surveys within Australia and internationally, for example Lim [1] and Peter and Valkenburg [2], making the degree of exposure amongst this cohort typical and generalisable.
This survey also made these other observations about the genders: female students were likely to be more negative towards pornography; less likely to view women as sex objects; less likely to desire the exploration of uncommitted sexual behaviours; be less compulsive; have better prosocial behaviours; and embrace less sexualised social media behaviours. Conversely, male students were more likely to have higher scores in: emotional stability; self-esteem; parental and peer relationships. This is all consistent with past research.
The study identified the following factors as significant influencers for viewing pornography: Age of
1st-Time Exposure, Parent Communication, Parental Rules, Peer Attitudes, Peer Behaviour, Religion, and Motivation.
The survey found that pornography exposure increased the likelihood of students having:
a. positive attitudes towards pornography
b. views which sexually objectify women
c. an increase in their desire for uncommitted sexual exploration
d. developed compulsivity problems
e. reduced distress and guilt from viewing
f. poorer social conduct
g. less social empathy
h. increased sexualised social media behaviours (including ‘sexting’).
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However, students viewing behaviours did not have a significant effect on the quality of parental or
peer relationship, or their levels of self-esteem, and saw a correlation between increased viewing
and increased emotional stability. Thus, questions about new confounders affecting adolescents not
present in older studies were raised, theorising that self-promoting social media behaviours
increased narcissistic traits, altering the relationship between these outcome factors and sexualised
media engagement. Overall the survey data demonstrated how ubiquitous pornography and
sexualised social media behaviours are amongst an otherwise healthy adolescent population.
In the context of a society increasingly sensitive to objectifying women, sexual harassment, domestic
violence, and unlawful sexual conduct via social media, addressing the effects of pornography
through focussed education, parental engagement, peer-group involvement, and responsible digital
device management, provide a preliminary and potentially valuable response by those responsible
for the emotional wellbeing of young people.
5.4 Aims and Hypotheses
The aim of this research was to implement a longitudinal study assessing the effectiveness of a pilot
education intervention. The pilot intervention (the program) consisted of six 50 minute lessons, plus
home activities.
There are six primary hypotheses to this study:
• H1 – that participants in the program would have reduced scores in the negative outcome
factors associated with frequent pornography viewing: Attitudes to Pornography (H1a),
Women as Sex Objects (H1b), and Uncommitted Sexual Exploration (H1c);
• H2 – there would be an overall reduction in the frequency of pornography viewing itself;
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• H3 – there would be an increase in the mean score for the factors Parent Communication
(H3a) and Parental Rules (H3b);
• H4 – there would be reduced mean scores in the factors Peer Behaviours (H5a) and Peer
Attitudes (H5b), as peer-based critical thinking produces less favourable attitudes to
pornography;
Secondary hypotheses include:
• H5 – that narcissistic traits would correlate with self-promoting social media behaviours;
• H6 – that narcissism would mediate the relationship between pornography viewing,
sexualised social media behaviours, and self-esteem;
• H7 – that wellbeing factors would not decline following the intervention;
• H8 – that the intervention student sample would behave consistently with the 2018 survey
group, both in prevalence data (H8a) and factor correlation (H8b), meaning the intervention
is an appropriate fit for them, and datasets may be combined for future studies.
5.5 Development and Review Process for Pilot Program
5.5.1 Pedagogical ethos
The theoretical basis for the program’s teaching content was derived from a review of the peer-
review literature, assisted by additional surveying of other similar school-based education programs.
Additionally, with the unresolved questions about social media behaviours, narcissism, and their
relationships to self-esteem and sexualised media engagement, the intervention included content
addressing these issues.
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The pedagogical method for the class component of the content was defined by two considerations:
a. the current Five Interrelated Purposes of the Health and Physical Education (HPE) strand and
the General Capabilities of the Australian National Curriculum [3]. The HPE Aims are to:
develop the knowledge, understanding and skills to enable students to … access, evaluate
and synthesise information to take positive action to protect, enhance and advocate for their
own and others’ health, wellbeing, safety and physical activity participation across their
lifespan [4].
b. The program applied a three-pronged strategy: peer engagement, parental engagement,
and didactic content. These are the primary methods for modifying knowledge, attitudes
and behaviours. The proportion of time for each strategy (per lesson) was estimated to be
equal.
The process for developing the pilot was initially iterative and unstructured. A draft program was developed by the candidate (Marshall Ballantine-Jones), using data from the published literature, and modelled on the parameters of the Stage 5 Health and Physical Education (HPE) strand of the
National Curriculum. The draft was circulated to staff from three schools, who made multiple suggestions. Updated drafts were recirculated and amended until a consensus was obtained from the schools that the program was deemed satisfactory for a PDHPE program. Further feedback was obtained from parent and student focus groups to develop and strengthen the Parental Diary and
Student Discussion questions. Schools have advised the program would not involve any significant extra work for school staff as it complimented and was consistent with the Year 10 HPE. In detail, the following steps were taken:
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5.5.2 Teacher feedback
The full teaching unit was reviewed by PDHPE-trained staff from three different schools within the
period of November-December 2018. The overall response was very positive, and all felt the
program was consistent with the HPE National Curriculum requirements for Stage 5, including being
practical, age-appropriate, and easy to implement. The process for receiving and responding to
feedback was iterative, with the main points of concern listed below.
a. Keep content simple, making sure language is basic and sentences are short.
b. Consider allowing schools to be flexible in the process of facilitating peer-group discussions.
Suggestions include allocating senior students or pastoral staff to steer the questions within
the peer-group discussions, or appointing a team leader from the peers, to help all students
to participate.
c. Edit some of the content to remove grammatical errors.
All feedback was addressed and reviewed.
5.5.3 Parent feedback
The Parent Diary questions were assessed by five pairs of parents, each with teenagers within the
age range of 13–18 in late December 2018. All parents were positive about the questions, and felt
they would generate positive communication with their own children. Feedback to improve the
questions were given across the interviews, which is summarised below.
a. Ensure parents are not probed too directly on sensitive questions, rather keep questions
general enough to invite opinions without requiring answers.
b. Keep the language simple.
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c. Replace closed questions with open-ended options like “how”, “why”, “please explain” etc.
d. Don’t ask leading questions that may pressure parents into expressing a specific view, rather
allow variability in opinions, practices and beliefs.
All parents were shown the updated draft with these suggestions addressed, and were positive
about the changes.
5.5.4 Student feedback
The discussion questions from both the class discussions and peer-group discussions were discussed
amongst adolescents aged 13–19 in late December 2018. The total number of adolescents involved
in the process was twelve. They were asked to consider if: the questions were comprehensible; they
felt comfortable to discuss these questions amongst their class peers; they believed the questions to
be relevant to their peers; and felt their peers would positively engage with them. Overall, the
feedback was very positive, with a consensus that they would help kids think independently.
However, some of the feedback meant widespread redacting of grammar and vocabulary. Feedback
included:
a. Make questions clearer, that do not presume prior knowledge. If the question relates to new
content from that lesson, direct the students back to that content.
b. Use simpler language.
c. Make sure questions were “soft” and not too direct, so that students don’t feel accused.
d. Allow students to be creative as they think through solutions.
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5.6 Recruitment and Implementation Process for the Pilot Program
5.6.1 Ethics approval
University Human Ethics Committee approval was received to implement this study protocol on 13
June 2019, Project no.: 2019/386. All correspondence and teaching documents in Appendices C-J
were included in this approval.
5.6.2 Participant characteristics including sex, age range and inclusion/exclusion criteria
a. In July 2019, 173 Invitations were sent to the principals of members from the Association of
Independent Schools NSW, whose membership includes non-religious and faith-based
schools.
b. The participants were Year 10 students (age range 14–16 years).
c. Students without a minimum comprehension of English were not included in the invitation.
d. Students with significant cognitive impairment were considered for exclusion, based on the
judgement of their school or parents.
e. Parental consent was opt-out.
f. Seven schools accepted the invitation, but three withdrew later citing scheduling difficulties.
g. The main reasons principals gave for rejecting the invitation was that the schools were not
able to adjust their schedules in the given time. Australian schools run from February to
December but prepare lesson schedules the previous year.
h. Three of the four schools were coeducational and the other single sex. There were no
exclusion criteria based on the gender mix of a school.
i. The first school (n=72) ran the course in three separate classes. The second school had a
single class (n=26); the third (n=38) had two classes, and the final school (n=212), which was
all-male, had nine classes, and ran the program in condensed form over three weeks. In
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total, eight teachers taught the program across 15 classes, the total number of students
participating was 347.
5.6.3 Study participation
The schools did not report any students being withdrawn at the request of parents or excluded for
language or cognitive impairment.
Survey completion rates were as follows:
a. for the pre-intervention, 347 students commenced the survey. 38 did not complete. Final
completion rate was 309/347, or 89.0%;
b. for the post-intervention, 322 students commenced the survey. 46 did not complete. The
final completion rate was 276/322, or 85.7%.
As discussed in Chapter 3 (Section 3.4.1), a typical response rate for school-based interventions is
89.1%. Thus, both survey completion rates were typical of wider studies.
Two students indicated a gender of ‘other’ in the post-intervention survey and were included in all
analyses except when data was stratified by gender since the statistical size was too low for
meaningful analysis.
All schools completed the baseline surveys no earlier than one week prior to commencing the course
and follow up surveys were completed in the week after the course.
5.6.4 Sample size and Cohan’s ‘d’
The total sample sizes for the pre- and post-intervention surveys was 307 and 276 respectively
(males 235 and 204 respectively, and females 72 and 69 respectively). A common benchmark for
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calculating a study’s minimum sample size is the Cohen’s ‘d’ effect size. Cohen suggests three
categories: small (0.2), medium (0.5), or large (>0.8) [5]. Since this study is experimental and a new
area of research, with no broader guidelines for how to measure the intervention’s effect on the
respective factors, Cohen recommends using a smaller effect size to determine a sufficient minimum
sample size [5].
To illustrate, the minimum sample sizes for a two-sample, one-tail t-test, with power=0.8 and a 95%
confidence interval, are: 50 for an effect size of 0.5, and 307 for an effect size of 0.2. A sample size of
240 corresponds with an effect size of 0.225; when 140, the effect size is 0.3; when 78, the effect
size is 0.4; and when 60, the effect size 0.45.
Thus, the sample sizes of the pre- and post-intervention surveys were sufficient for analysing a small-
to-medium effect size for Total and Male comparisons, but only medium effect sizes for female
samples. However, the results for the female subgroup ‘Regularly View’ (pornography) – which in
Table 9.13 (Chapter 9) have sample sizes of n=12 (pre-intervention) and n=13 (post-intervention),
were inconclusive due to the low sample size.
5.6.5 Details of where the study was undertaken (location/site/URL)
The pilot program took place at schools, through a standard classroom arrangement, with
homework activities being completed on the student’s school-approved device. The baseline survey
was completed using RedCap via the internet, in class time, using either the student’s own device, or
school-provided device, with webpage access.
5.6.6 Details of how data was collected and analysed
The survey was conducted online via RedCap, through the University of Sydney’s RedCap portal. The
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data was analysed using Stata 16. The range of statistical analysis included frequency analysis, linear
and multiple regression analysis, and two-sample means tests.
The ongoing storage of data will comply with the Research Data Management Policy 2014. Only non-
identifiable data will be stored in perpetuity. There is no identifiable data obtained from children in
this study, as the surveys are anonymous. The survey results will be stored until at least 2039, which
is the minimum period data from psychological studies involving children in NSW.
5.6.7 Risks associated with study
It is advised by teachers consulted in 5.2 that the content of the education pilot was low risk because
of the similarities to what was already taught in the sexuality component of the HPE and PDHPE
curricula, and thus appropriate for Year 10. To manage the risk of distress or harm, schools arranged
for their counsellors to be the primary contact for managing adverse responses in students (or
others associated with them like friends or family), in consultation with the Head of PDHPE and class
teachers. Class teachers were instructed to be alert to how students were responding to and coping
with the program. Students were regularly reminded that if they felt distressed, that the school
counselling services were available. Likewise, school counselling and pastoral staff were alerted to
when the course was running, so that they could be prepared to consult with any students that may
have needed support.
5.6.8 Invitation to Principals
Principals from the target schools received an invitation to participate via letter and email. Appendix
C (“Letter to the Principal”) contains the invitation. Acceptance was made by email to the
researchers, along with a description of how the school would manage students who did not do the
study.
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5.6.9 Participation Information Statements to students, parents and teachers
Participation Information Statements (PIS) were sent to students and parents, inviting them to
partake in the study. In addition to an explanation of the study process and content, as well as
assurances that the data collected through the survey would be anonymous and confidential, the
option for withdrawal was described.
a. Parents were invited to opt-out their student at any time, which is the school’s preferred
method of communicating consent. Parents were also provided a description of the
homework activity they would be asked to join, with assurances that they were able to
decline from doing this with no adverse actions on their child (see Appendix D).
b. Students maintained agency throughout the process, and could choose not to do the survey
or course by communicating to their teachers. Students were also provided options for
raising concerns, or seeking help, in the event of distress (see Appendix E).
c. Teachers received instructions about the process of teaching, including which staff would
oversee the administration of the course, how they would manage any concerns of students
or any students who did not participate in the study. Further documentation about the
course, including the lesson content, background content, and scope and sequence overview
content, accompanied the Teacher PIS (see Appendix F).
PIS documents were sent at least three weeks before the commencement of the program, giving
ample time for students and parents to consider.
5.6.10 Teaching content
a. The final draft of the six-lesson program aligned with the Health and Physical Education
(HPE) strand of the National Curriculum, Stage 5. Each lesson consisted of a mixture of
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creative content learning, popular cultural interaction, peer-discussion groups, and personal
reflection. b. The content of the program is contained in the Teacher’s Pack, which consists of:
• The Lesson Overview – which described the scope, sequence, ethos and various elements in
the pilot (see Appendix G);
• The Lesson Background – which provided the theoretical and empirical content underlying
each lesson (see Appendix H);
• The Lesson Teaching Content – which included six printable worksheets for the students to
store in a folder, along with the full teaching content for each lesson (see Appendix I);
• The Parental Diary – which were six worksheets the student took home (either as hard or
soft copies) and was the homework component of the pilot (see Appendix J).
a. The course was taught by the school’s PDHPE teachers, under the supervision of their head
of department. Although the teaching content for six lessons were complete and self-
contained for conducting the class lesson, the Lesson Background document provided the
broader knowledge to inform teachers of concepts and ideas discussed in each lesson. b. Parents were not obligated to answer any questions from the Parental Diary, as explained in
the Parental PIS. However, they may have used the discussion opportunities to
communicate more generally about the issues raised by the content in this course. c. The homework component of the course consisted of the Parental Diary worksheets, either
hardcopy or softcopy, as befits the school’s normal homework context (i.e. done on
computers or paper). Instructions on how to use the Parental Diary were directed by the
class teacher, as explained in the “Lesson Overview” document (Appendix G). Students were
not required to share their homework with other students or the teacher, apart from the
teacher checking that parents had signed off on its weekly completion, and with the
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exception of the final question of the Week 5 lesson, which was to be discussed in the last
peer-group session of Lesson 6.
d. The students interacted with one another primarily through the peer discussion groups. As
explained in the Lesson Overview document, the teacher was to allocate students into
groups, consider the make-up of the group members and additional facilitatory roles. This
was to be done during class-time, and managed by the teacher.
5.6.11 Alternative teaching content
For students who did not participate in the study, schools were to provide appropriate alternative
supervision and learning content from the PDHPE curriculum. This process could vary from school to
school, depending on how many withdrew and what content the schools prepared. School principals
were to provide a description to the parents and students (through the PIS letters) about what
happened if they declined or withdrew from the study.
5.7 Data Analysis
5.7.1 Longitudinal analysis
The baseline survey was implemented at the commencement of Lesson 1, and again within four
weeks of completing the program. It was to be completed using RedCap via the internet, in class
time, using the student’s normal school-approved device used for lessons, or in the case of students
without such devices, on a device provided by the school.
The effectiveness of the pilot was measured through a combination of simple linear and multiple
parametric regression analysis, and comparisons of means between longitudinal samples. Table 5.1
describes how the instruments would be used to measure the effectiveness of the pilot.
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Regarding the comparisons of pre- and post-intervention surveys, only the average change of data means were analysed, since no student identifiers were kept, it was not possible to measure changes at an individual level.
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Table 5.1 Construct Themes for Baseline Survey Instruments
Scale/Inventory/Questionnaire Construct theme
Pornography Exposure Scale [2] Prevalence of exposure
Sexting and Social Media Behaviour Scale [6] Behaviours and Attitudes
Parental Mediation of Pornography Scale/ Parental engagement
Restrictive Mediation Scale [7]
Cyber Pornography Use Inventory (CPUI-9 Questions) [8, 9] Behaviour and Attitudes
Peer Descriptive/Injunctive Scales [7] Peer group influence
Women as Sex Objects [10] Behaviours and Attitudes
Attitudes Toward Uncommitted Sexual Exploration [2] Behaviours and Attitudes
Attitudes Toward Pornography [11] Knowledge
Strengths and Difficulties Scale [12, 13] Behaviours and Attitudes
• Conduct Problems Scale • Peer Problems Scale • Prosocial Scale
Self-Description Questionnaire II Sub-Scales [14] Behaviours and Attitudes
• Parent Relationships • Emotional Stability • Self-Esteem
Narcissistic Personality Index NPI-13 [15] Behaviours and Attitudes
Abstinence Efforts and Failed Abstinence Efforts [15] Behaviours and Attitudes
Social Media Behaviours [16] Behaviours and Attitudes
5.7.2 Qualitative analysis
A qualitative teacher’s feedback questionnaire was drafted in consultation with PDHPE teachers
familiar with the program (See Table 6.1). Upon receiving approval by the university’s human ethics
committee, the following actions were taken:
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a. Teachers and heads of department were asked to describe the process of preparing the
pilot, including PIS statements, rearranging curriculum teaching content, and catering for
students who opted-out of the study.
b. Teachers were provided with a weekly checklist of teaching content covered. They provided
feedback on the student engagement with content, any unexpected directions in the
student response to the content, and any difficulties in executing the teaching plan.
c. A follow-up interview via phone took place with class teachers to gather additional
feedback, including suggestions for improving the pilot.
5.7.3 Potential significance of the study
Given that the hypotheses in Chapter 9 are proven, this study will have significance for the following
reasons:
a. The pilot will have a direct impact on participants. It will reduce the negative attitudes and
behaviours associated with exposure to sexualised media. It will also increase some
positive outcomes in the participants’ lives – including wellbeing factors, and parental and
peer relationship quality.
b. The pilot will be the first empirically tested school-based education program for sexualised
media and pornography-related topics.
c. The study will demonstrate that a program that includes significant attention to parental-
student communication leads to positive changes in the student’s attitudes and
behaviours.
d. The study will demonstrate that a program that dedicates significant attention to peer-
group interaction and problem-solving will reduce the negative attitudes and behaviours
associated with exposure to sexualised media, whilst also reducing the effect of more
distant peer attitudes that students are exposed to.
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e. The study provides longitudinal evidence for cause and effect relationships between a
number of the factors, which to date is inadequately demonstrated by the bulk of cross-
sectional studies in the wider literature.
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5.8 Chapter References
1. Lim, M.S.C., et al., Young Australians' Use of Pornography and Associations with Sexual Risk Behaviours. Australian and New Zealand Journal of Public Health, 2017: p. n/a-n/a. 2. Peter, J. and P.M. Valkenburg, Adolescents' Exposure to Sexually Explicit Internet Material, Sexual Uncertainty, and Attitudes Toward Uncommitted Sexual Exploration: Is there a Link? Communication Research, 2008. 35(5): p. 579-601. 3. www.australiancurriculum.edu.au/f-10-curriculum/health-and-physical-education/ 4. ACARA. Australian Curriculum Health and Physical Education. 2017 Accessed on 14/3/2018]; Available from: https://australiancurriculum.edu.au/f-10-curriculum/health-and-physical- education/. 5. Cohen, J., Statistical Power Analysis for the Behavioral Sciences–Second Edition. 12 Lawrence Erlbaum Associates Inc. Hillsdale, New Jersey, 1988. 13. 6. Mitchell, A., et al., National Survey of Australian Secondary Students and Sexual Health 2013. Melbourne: Australian Research Centre in Sex Health and Society & La Trobe University, 2014. 7. Rasmussen, E.E., et al., The Relation Between Norm Accessibility, Pornography Use, and Parental Mediation Among Emerging Adults. Media Psychology, 2016. 19(3): p. 431-454. 8. Grubbs, J.B., et al., Internet Pornography Use: Perceived Addiction, Psychological Distress, and the Validation of a Brief Measure. Journal of Sex & Marital Therapy, 2015. 41(1): p. 83- 106. 9. Morelli, M., et al., Sexting Behaviors and Cyber Pornography Addiction Among Adolescents: the Moderating Role of Alcohol Consumption. Sexuality Research and Social Policy, 2017. 14(2): p. 113-121. 10. Peter, J. and P.M. Valkenburg, Adolescents’ Exposure to a Sexualized Media Environment and Their Notions of Women as Sex Objects. Sex Roles, 2007. 56(5): p. 381-395. 11. Evans-DeCicco, J.A. and G. Cowan, Attitudes Toward Pornography and the Characteristics Attributed to Pornography Actors. Sex Roles, 2001. 44(5): p. 351-361. 12. Goodman, R., The Strengths and Difficulties Questionnaire: A Research Note. J Child Psychol Psychiatry, 1997. 38. 13. Goodman, R., H. Meltzer, and V. Bailey, The Strengths and Difficulties Questionnaire: A Pilot Study on the Validity of the Self-report Version. European Child & Adolescent Psychiatry, 1998. 7(3): p. 125-130. 14. Marsh, H.W., et al., A Short Version of the Self Description Questionnaire II: Operationalizing Criteria for Short-form Evaluation with New Applications of Confirmatory Factor Analyses. Psychological assessment, 2005. 17(1): p. 81. 15. Gentile, B., et al., A test of Two Brief Measures of Grandiose Narcissism: The Narcissistic Personality Inventory-13 and the Narcissistic Personality Inventory-16. Psychological assessment, 2013. 25(4): p. 1120-1136. 16. Moon, J.H., et al., The Role of Narcissism in Self-promotion on Instagram. Personality and Individual Differences, 2016. 101: p. 22-25.
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Chapter 6: Qualitative Analysis of Pilot Program
6.1 Introduction
A pilot education program, designed to explore if three strategies may help reduce various negative
effects from adolescents’ pornography exposure, was implemented in four independent schools in
NSW between July 2019 and March 2020. This education program fitted within the school’s Personal
Development, Health and Physical Education (PDHPE) curriculum and aligned with the Australian
National Curriculum’s Health and Physical Education (HPE) strand. It consisted of six lessons covering
themes including: 1. sexual health; 2. the internet; 3. social media; 4. sexualised culture; 5.
pornography. The study is longitudinal, with students completing a baseline survey prior to and
again at the conclusion of the program.
As described in Chapter 5, the program deployed the three strategies of didactic education, peer-to-
peer engagement, and parental-engagement. It assessed changes in knowledge, behaviour and
attitudes.
The hypotheses of the study are found at 5.4 (Chapter 5). To evaluate the hypotheses, a qualitative
assessment of the program was conducted amongst the class teachers. A questionnaire was
provided to them, seeking a description of the teacher’s experience in delivering the program and
the students’ reception of, and participation in it. All teachers were new to the program, having had
no role in its development or past teaching of it. They were dependent solely on the documentation
provided with the program, for preparing and delivering it. The teachers’ insights reveal some
strengths of and challenges to conducting the program, and offer guidance on how to strengthen its
content and delivery.
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6.2 Aims
The aims were to explore and identify any modifying elements affecting the pilot education
program’s objectives and results. Written feedback from teachers about their experience of running
the intervention was analysed, according to a thematic analysis methodology [1], as performed by
Skinner, et al. [2].
6.3 Method
In July 2019, Year 10 students from independent schools in NSW were invited to run the intervention
between August 2019 and March 2020. Four schools participated, with 307 students completing the
baseline survey, including 232 males and 72 females (average age 15.0 and 15.6 respectively). 276
students completed the post-intervention survey, including 205 males and 69 females. Two students
indicated a gender of ‘other’ in the post-intervention survey and were included in all analyses except
when data was stratified by gender since the statistical size was too low for meaningful analysis.
The first school to run the course had 71 students in three separate classes. The second school had a
single class (n = 26); the third had two classes (n = 38 in total), and the final school (n = 213) had nine
classes, and ran the program in condensed form over three weeks with five teachers. In total, eight
teachers taught the program across 15 classes, the total number of students participating was 307.
All schools completed the baseline surveys no earlier than one week prior to commencing the course
and follow up surveys were completed in the week after the course.
A nine-question survey was developed. The nine-question survey is found in Table 6.1.
Surveys were distributed electronically to the supervising department head, who in turn distributed
to and collected from the class teachers. The researchers had no direct engagement with class
teachers, unless they were also the departmental head.
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The data were analysed in the following sequence:
a. Analyse the categorical data in Questions 1 and 2
b. Analyse the numerical data from Questions 3 and 6
c. Analyse the embedded themes from direct questions
d. Identify and analyse arising themes from open-ended questions
Finally, the data was arranged into logical themes, as reported below.
6.4 Results
6.4.1 Survey response
Three of the four schools returned the teacher feedback questionnaire. The first school that ran the
program, did not respond to requests to return it. The other schools returned their forms via email
to the school representative assigned to supervising the study. No direct interaction was made
between the researchers and the class teachers apart from the feedback questionnaire.
Questionnaires were either hand-written and scanned, or digitally edited via a word processor.
Seven teachers returned the questionnaire, one each from the two smaller schools. The following
themes were identified from analysis of the questionnaire data.
6.4.2 Teaching difficulty of lessons
Six out of seven teachers said the lessons were easy to complete. The seventh teacher indicated that
all lessons were hard to complete within the 50min time allotment. This limitation was attributed to
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the in-depth peer discussions component, which although done well, was difficult to contain. The
tension between covering content and allowing robust peer discussion was noted by other teachers.
One respondent departed from the approved curriculum for aspects of each lesson and introduced
alternative multimedia components. This teacher reported that the alternative content was more
modern and pedagogically sound than the set content. Only one teacher indicated they did not
complete the group assignment, which was a “vox-pop” video.
6.4.3 Student engagement during the six lessons
Teachers indicated much of the content was received with interest. The Introduction Lesson, which
included videos of celebrities, was particularly engaging to most classes. Classes had differing levels
of positive interest across the lessons. One class teacher reported Lesson 3 was particularly
engaging, whilst another said the final lesson on social media and legalities was a highlight. Two
respondents indicated that some content was repetitive or already known by the students.
6.4.4 Assessing the teaching experience of lessons
Teachers were asked in Question 3 to rank each of the six lessons out of five, with one being poor
and five being excellent. There were two dimensions to this (Table 6.2) – how each lesson ranked for
the seven teachers, and how each teacher ranked the complete set of six lessons.
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Table 6.1 – Teacher Questionnaire for Pilot Intervention
Question Lesson 1 Lesson 2 Lesson 3 Lesson 4 Lesson 5 Lesson 6 1. Were there components difficult to complete or incomplete? Yes/no 1.a. If so, what were they? 1.b. What was the reason for each one that was difficult?
2. Were there components of any lesson that received interest and engagement from the students? Yes/no 2.a. If so, what were they? 3. Overall, how well did each lesson go? Give your response on a scale from 1 to 5 where 1 is poor and 5 is excellent. 4. Can you give a brief assessment of how well peer discussions went, including enthusiasm, participation, and timing? 5. Can you give a brief assessment of how well the parental diary home activities went, including perceived participation, and any ad-hoc student or parental feedback? 6. What was your general assessment of the overall program? Give your response on a scale from 1 to 5 where 1 is poor and 5 is excellent. 7. Do you have any recommendations for improving the program? 8. Do you have any feedback regarding the conducting of the surveys? 9. Do you have any other feedback about the program or the process of doing this study?
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Table 6.2 Lesson scores by each Teacher
Average Teacher Lesson 1 Lesson 2 Lesson 3 Lesson 4 Lesson 5 Lesson 6 score per teacher
#1 4 4 3 3 3 3 3.3
#2 4 3 4 3 5 - 3.8
#3 4 4 3 3 4 4 3.7
#4 3 4 4 3 4 4 3.7
#5 4 4 3 4 3 4 3.7
#6 4 4 4 4 3 3 3.7
#7 3 4 4 - - - 3.7
Average score 3.7 3.86 3.6 3.3 3.7 3.6 3.6/3.7 per lesson
Note: Each lesson is ranked ‘1’ for poor, to ‘5’ for excellent. Total Columns are averages, and adjusted for blank scores.
In summary, the average score for all lessons was 3.6/5 (72%), with a range of 3.3–3.86. The average
score for all lessons combined was 3.7 (72%), with a range of 3.3–3.8.
In addition to these lesson scores, Question 6 asked teachers their overall ranking for the course.
Four teachers gave a response. The average score was 3.4/5 (67.5%). The content was described as
“interesting”, “important” or “needed information”. A range of teaching difficulties were noted:
a. The course was difficult to prepare given the unfamiliar content and time-restrictions;
b. The content felt long at times, and some of the activities were not engaging;
c. Better resources were accessible on the topics for teachers to use;
d. The content was sometimes difficult to deliver because the topic was sensitive.
There was no uniform opinion about the teachability of the program, but the rankings were
consistent across the individual lessons and the overall impressions.
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6.4.5 Peer discussions
Teachers reported that peer discussions went well for most classes, although this opinion was not
uniform. For example, two classes saw the level of participation increase over the six lessons, whilst
two had levels of enthusiasm decrease for the second half. Less effective peer discussions occurred
in the face of occasional difficulties — including classroom interruptions, occasional relocations, and
timetable alterations. Also, the occasional dominating student personality in the class resulted in
reduced enthusiasm from other students in the discussion times.
6.4.6 Parental diary home activity
The parental diary was not done well. Six of the seven teachers reported that this component was
incomplete, the other conceding they didn’t know if students completed the diary. When enquiry by
the teacher was made to students about their diary progress, four out of seven of the teachers said
students felt uncomfortable with and awkward about the parental discussions. Only two teachers
said positive feedback was received from the students who engaged with the parental diary activity.
6.4.7 Ideas for improving the program
When teachers were asked how the program may be improved, the following ideas were put
forward:
a. The program was too long and could be condensed, possibly to four lessons. It was observed
that Lessons 5 and 6 (on social media, sexting and legal issues) were topics previously
covered in the PDHPE curriculum.
b. The lesson format was seen to be repetitive and predictable, reducing student interest over
the course of the lesson, and may benefit from a richer variety of activities, teaching style,
and a more student-tailored “strength-based” approach. The overarching pedagogy could be
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strengthened by adopting other already developed resources that “evidence best practice”
(although no specific curriculum was suggested).
c. The class videos and supplementary online resources could be improved with more modern
alternatives, for example the materials provided by not-for-profit website Fight the New
Drug [3].
d. Teachers and researchers could have had better alignment for designing and teaching the
lessons. For example, familiarising teachers with the teaching content, or the researcher’s
aims and outcomes, would help. Also, one teacher reported that it was unclear what the
benefit of doing the course was to the students.
e. Some feedback about the student responses suggested that the program felt unbalanced
because it largely presented the negative side of the issue. More research about the positive
side of engaging in sexualised materials could have been included.
6.4.8 Ad-hoc feedback
Additional observations from some teachers included: the researcher’s communication was always
prompt and helpful (from a teacher who was also departmental head); and there was a cost to the
schools for printing out the workbooks and diary, which should be accounted for in future.
6.5 Discussion
The analysis of the questionnaire data provides useful insights about the intervention’s
effectiveness. The intervention’s primary objective is to positively change knowledge, attitudes and
behaviours through the three strategies of didactic education, peer-to-peer critical engagement, and
parental engagement. Keeping this in mind, the results are presented below.
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6.5.1 Content and delivery of lessons
a. Teachers reported positivity about the overall content and teachability of the lessons. All
students received the core teaching components in each lesson and no teacher indicated
they couldn’t or didn’t deliver the content.
b. Teachers reported that lessons were well participated in and received by students. There is
no reason to suppose that the subsequent quantitative analysis of the student surveys failed
to provide an objective assessment of the didactic education strategy of the pilot program.
Several teachers believed there were some shortcomings to the lessons. For example:
c. The amount of content per lesson made them difficult to complete. Guidance on how to
time manage or content manage would help. The choice of multimedia content could have
been improved, although it should be noted that the original lessons were written by the
author in 2018, reviewed by a number of PDHPE teachers from various schools with
feedback being that they seemed appropriate for what was available at the time. For any
future iterations or revisions of the program, updating material and avoiding too much
content should be taken into account.
d. Teachers felt the direct communication from the researchers was not ideal. Teachers did not
always understand the task, despite the information provided in the teaching
documentation. For example, the expectation of having parents sign-off each when their
child completed the Parental Diary activity, as explained in the Lesson Overview document
(Appendix G), seemed to elude the teachers.
e. Monitoring the intervention’s hands-on progress was difficult. Most class teachers were a
step removed from the researchers since the approval process by the HREC limited
communication through a school contact person, rather than the actual teachers. It was not
possible to accurately gauge when the Teacher Pack was distributed in advance of the
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lessons, if teachers had read all the instructions, had adequately prepared background
content, or understood the suite of requirements including the take-home parental diary
and the “vox-pop” questions. This was despite weekly contact with the approved school
contact person to evaluate progress.
f. The purpose of the program, and how it would benefit the students, was reported as being
unclear even though the Teacher’s Participation Information Statement (PIS) stated the
program could “impart the most up-to-date and scientifically-based content, whilst
challenging the attitudes and behaviours of them and their peers”, and also “the program
will be carefully assessed for effectiveness … and knowledge of whether this unique
combination of teaching elements can contribute to meaningful change in students’ lives”.
6.5.2 Peer discussions
The peer discussions were conducted well. This was reported across all teachers and schools, and
thus provides confidence that an objective analysis of the peer-engagement hypotheses was
possible.
6.5.3 Parental diary
The Parental Diary activity was conducted poorly. Communication deficiencies may have contributed
to teachers not understanding this aspect of the intervention. Teachers reported that students often
felt awkwardness in discussing sexuality with their parents, which likely attributed to its non-
completion. Compounding this, the parents were informed in their PIS that they did not have to
participate if they did not want to. The Parental Diary questions were not personal or invasive and
had previously been trialled with groups of parents to ensure they felt comfortable with them
(Chapter 5), yet parents may have felt awkward too. Also, just as there were limitations in
monitoring class teachers, there was no way to engage with parents to learn if they had read the
directions in their PIS, understood it, agreed with it, and then participated in the activity. After the
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study, it was not possible to survey parents about their understanding of how they were to
participate, as this would require both a new HREC application, plus school and parent consent,
which time did not permit. It is likely that when neither the teachers nor the parents were driving
the process, the students had no motivation for this section. With the Parental Diary activity mostly
incomplete, the third strategy of the intervention remains untested.
6.6 Conclusion
The teacher questionnaire produced helpful data about the intervention’s implementation amongst
three of the four schools. The majority of feedback suggested that the program was easy to deliver,
well received by students, and consistently engaged with. There were areas the program could be
strengthened, including better communication with teachers in preparation for the intervention, as
well as clearer guidance on delivery, research concepts, aims and outcomes. The Peer Discussions
were well received by students. The Parental Diary activity was poorly executed, compromising the
intervention’s core strategy of increasing parental-student engagement.
We wish to acknowledge the schools, their students and families for generously participating in this
study, with particular gratitude for the class teachers that dedicated their time to preparing and
delivering the lessons.
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6.7 Chapter References
1. Braun, V. and V. Clarke, Using Thematic Analysis in Psychology. Qualitative Research in Psychology, 2006. 3(2): p. 77-101. 2. Skinner, S., et al., HPV.edu Study Protocol: A Cluster Randomised Controlled Evaluation of Education, Decisional Support and Logistical Strategies in School-based Human Papillomavirus (HPV) Vaccination of Adolescents. BMC Public Health, 2015. 15: p. n/a. 3. https://fightthenewdrug.org/
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Chapter 7: Data Integrity
7.1 Introduction
The next three chapters evaluate the effectiveness of the program by comparing and analysing the
pre- and post-intervention survey data. Chapter 8 examines the interaction between social media
behaviours, narcissism, self-esteem, and sexualised media engagement. Chapter 9 compares the
pre- and post-intervention surveys, to describe how the intervention impacted the students’
knowledge, attitudes and behaviours.
This chapter aims to confirm that the pre-intervention survey data are reliable and suitable to
evaluate the hypotheses from Chapter 5. Since the program leant heavily on the results of the 2018
survey data in its design and methodology, it is important to confirm that the cohort is a good fit for
the intended audience. This will be established two ways: 1. an analysis of the sample size, to ensure
there is enough statistical power for meaningful analysis; 2. a comparison of pre-intervention data
with the 2018 survey data. This will confirm hypothesis 10 of the Study Protocol (Chapter 5), which
posits that:
• the intervention student sample would behave consistently with the 2018 survey group, both
in prevalence data (H10a) and factor correlation (H10b), meaning the intervention is an
appropriate fit for them, and datasets may be combined for future studies.
The pre-intervention survey had an additional 24 items including the Narcissism (NPD-13) scale, plus
a single item on abstinence efforts, a single item on short-term (past 14-days) pornography viewing
habits (that replaced a redundant item from the original survey), and 10 questions related to social
media behaviours. 23 of these new items will be validated in Chapter 8. All other items, including
control variables, and predictor and outcome factors, have been maintained per the 2018 survey,
and will be the reference for comparative analysis in this chapter.
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Another advantage of comparing the pre-intervention and 2018 survey data is that if they are
consistent, they may be combined into a larger dataset for future research.
7.2 Aim
a. To compare data from 2018 survey and pre-intervention survey.
b. To assess if the pre-intervention sample is sufficient to evaluate an intervention built largely
from the 2018 survey.
c. To establish if data samples can be combined for future studies.
7.3 Method
The control, prevalence, predictor and outcome variables in Chapter 4 were compared by four
methods: 1. chi-squared proportions tests for categorical variables; 2. Wald chi-squared tests on
regression coefficients for all comparable correlations; 3. t-test comparisons of means; and 4. a
comparison of correlation significance levels (p values) in the inter-factor bivariate correlation
matrixes.
For the t-tests analysis across all three chapters, an independent two-sample t-test was used since
data is not paired. This post-intervention dataset analysed in Chapter 9 was also not paired, because
student responses were anonymous and could not be matched across datasets. For the t-tests in
Chapter 7, two-tail significance tests were used because there is no theoretical reason to assume a
directional change. However, in Chapter 9, one-tail t-tests were used whenever there is an
expectation that a factor would change because of the intervention, otherwise tests were two-
tailed.
7.4 Results
The study method and participation response is described in Chapter 6, Section 3.
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7.4.1 2018 Survey and Pre-Intervention Data Comparison
Chi-Squared proportions tests were used to compare the categorical control and prevalence
variables between the pre-intervention and 2018 surveys in Tables 7.1 to 7.8. The following
observations can be made:
a. The Parental Marital status between surveys (Table 7.1) had no significant differences
between each martial category.
b. There was no significant difference in each employment category for variable Parental
Employment Status (Table 7.2).
c. The differences in the Six-Monthly Viewing Prevalence factor categories (Table 7.3) were
insignificant, except for the “Never” category, where there was a significant difference
between proportions for the “Male” and “Total” categories. That is, the pre-intervention
survey sample had proportionally more males who have never seen pornography.
d. The Religion factor proportions in Table 7.4 were not significantly different except for males
in the “Always” category, where there was a moderate difference (p = 0.077). That is, more
male students in the pre-intervention survey were more “highly” religious than the 2018
data set.
e. There was no proportional difference in Preferred Viewing Device (Table 7.5), for either
males, females, or in total.
f. The Viewing Intentionality proportions did not significantly vary for either the separate
genders or in total (Table 7.6).
g. Lastly, the comparison of proportions for the Sexualised Social Media Behaviours (SSMB)
questions, in Table 7.7, were mostly similar, with more males in the pre-intervention survey
having never sent a sexually explicit written text message (p = 0.02); less total students in
the pre-intervention survey having never received a sexually explicit written text message
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(p = 0.00); and less females (and total students) in the pre-intervention survey saying that
sending and receiving naked pictures is a normal thing their friends do.
Overall, the control and prevalence data are highly consistent between the surveys. This contributes
to confidence that the intervention group are statically similar to the larger 2018 survey sample in
demographics and pornography-related prevalence behaviours.
Table 7.1
Proportions Comparison of Parental Marital Status between Pre-Intervention and 2018 Surveys Pre-Intervention 2018 Survey mean diff p-value Married 250 81.4% 616 82.6% -0.01 0.675 Divorced 38 12.4% 76 10.2% 0.02 0.723 De Facto 8 2.6% 20 2.7% 0.00 0.988 Widowed 4 1.3% 7 0.9% 0.00 0.950 Other 7 2.3% 27 3.6% -0.01 0.864 Total (n=) 307 100% 746 100% Note: p-value is for the null hypothesis that there is equality of proportions between survey categories. As all p-values are insignificant, the conclusion is that survey proportions do not differ.
Table 7.2
Proportions Comparison of Parental Employment between Pre-Intervention and 2018 Surveys
Pre-Intervention 2018 Survey mean diff p-value
One 62 20.2% 174 23.3% -0.03 0.616
Both 241 78.5% 560 75.1% 0.03 0.301
None 4 1.3% 12 1.6% 0.00 0.966
Total (n=) 307 100% 746 100%
Note: p-value is for the null hypothesis that there is equality of proportions between survey categories. As all p-values are insignificant, the conclusion is that survey proportions do not differ.
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Table 7.3 Proportions Comparison of Pornography Viewing between Pre-Intervention and 2018 Surveys
Pre-Intervention Survey 2018 Survey Prevalence Table Male Female Total Male mean diff p-value Female mean diff p-value Total mean diff p-value Never 76 32.8% 49 68.1% 127 41.4% 82 14.5% 0.19 0.006 101 55.5% 0.13 0.143 183 24.5% 0.17 0.002 Less than monthly 39 16.8% 11 15.3% 50 16.3% 86 15.2% 0.02 0.798 43 23.6% -0.09 0.538 129 17.3% -0.01 0.873 Monthly 37 15.9% 4 5.6% 41 13.4% 110 19.5% -0.04 0.636 24 13.2% 0.02 0.838 134 18.0% -0.05 0.492 More than once/month but less than once/week 19 8.2% 5 6.9% 24 7.8% 122 21.6% -0.14 0.166 7 3.8% 0.03 0.804 129 17.3% -0.10 0.242 Weekly 45 19.4% 2 2.8% 48 15.6% 117 20.7% -0.02 0.809 7 3.8% -0.01 0.957 124 16.6% -0.01 0.874 More than once/week but less than every day 5 2.2% 0 0.0% 5 1.6% 37 6.6% -0.05 0.686 0 0.0% - - 37 5.0% -0.03 0.736 Daily 11 4.7% 1 1.4% 12 3.9% 10 1.8% 0.03 0.689 0 0.0% - - 10 1.3% 0.03 0.709
Total 232 100% 72 100% 307 100% 564 100% 182 100% 746 100% Note: p-value is for the null hypothesis that there is equality of proportions between survey categories. There is a significant difference between proportions for Males and the Total in the “Never” category, meaning there are proportionality more males, and subsequently overall, who have never seen pornography in the Pre-Intervention study. As other p-values are insignificant, the conclusion is that survey proportions do not differ except for the “Never” category.
Table 7.4 Proportions Comparison of Religion Factor between Pre-Intervention and 2018 Surveys
Pre-Intervention Survey 2018 Survey Total Religious Activity Male Female Total Male mean diff p-value Female mean diff p-value Total mean diff p-value Never 52 22.4% 27 37.5% 80 26.1% 162 28.7% -0.06 0.374 42 23.1% 0.14 0.197 204 27.3% -0.01 0.838 Rarely 46 19.8% 16 22.2% 62 20.2% 130 23.0% -0.03 0.653 36 19.8% 0.02 0.843 166 22.3% -0.02 0.732 Sometimes 24 10.3% 8 11.1% 32 10.4% 68 12.1% -0.02 0.813 28 15.4% -0.04 0.760 96 12.9% -0.03 0.709 Mostly 45 19.4% 8 11.1% 54 17.6% 112 19.9% -0.01 0.943 34 18.7% -0.08 0.609 146 19.6% -0.02 0.749 Always 65 28.0% 13 18.1% 79 25.7% 92 16.3% 0.12 0.077 42 23.1% -0.05 0.703 134 18.0% 0.08 0.182 Total 232 100% 72 100% 307 564 100% 182 100% 746 100%
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Table 7.5 Proportions Comparison of Preferred Viewing Device between Pre-Intervention and 2018 Surveys
Pre-Intervention Survey 2018 Survey Preferred Device Table Male Female Total Male mean diff p-value Female mean diff p-value Total mean diff p-value Phone 100 58.5% 13 46.4% 115 57.2% 282 58.0% 0.01 0.931 33 38.4% 0.08 0.619 315 55.1% 0.02 0.698 Tablet/iPad 26 15.2% 3 10.7% 29 14.4% 60 12.3% 0.03 0.715 10 11.6% -0.01 0.966 70 12.2% 0.02 0.766 Laptop 25 14.6% 2 7.1% 27 13.4% 92 18.9% 0.01 0.877 21 24.4% -0.17 0.578 113 19.8% -0.06 0.442 Desktop 2 1.2% 0 0.0% 2 1.0% 6 1.2% 0.00 1.000 1 1.2% - - 7 1.2% 0.00 0.981 TV 5 2.9% 1 3.6% 6 3.0% 12 2.5% 0.00 0.963 6 7.0% - - 18 3.1% 0.00 0.990 Other 13 7.6% 9 32.2% 22 10.9% 34 7.0% 0.01 0.943 15 17.4% 0.15 0.407 49 8.6% 0.02 0.758 Total 171 100% 28 100% 201 100% 486 100% 86 100% 572 100%
Table 7.6 Proportions Comparison of Viewing Intentionality between Pre-Intervention and 2018 Surveys
Pre-Intervention Survey 2018 Survey Viewing Intentionality Male Female Total Male mean diff p-value Female mean diff p-value Total mean diff p-value Never 25 14.2% 20 64.5% 45 21.7% 46 9.2% 0.05 0.520 53 57.6% 0.07 0.614 99 16.7% 0.05 0.501 Rarely 26 14.8% 4 12.9% 30 14.5% 78 15.6% -0.01 0.922 19 20.7% -0.08 0.711 97 16.4% -0.02 0.843 Sometimes 34 19.3% 5 16.1% 39 18.8% 97 19.4% 0.00 0.990 7 7.6% 0.08 0.663 104 17.6% 0.01 0.912 Usually 55 31.3% 1 3.2% 56 27.1% 150 30.0% 0.01 0.858 6 6.5% - - 156 26.4% 0.01 0.873 Always 36 20.5% 1 3.2% 37 17.9% 129 25.8% -0.05 0.514 7 7.6% - - 136 23.0% -0.05 0.506 Total 176 100% 31 100% 207 100% 500 100% 92 100% 592 100%
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Table 7.7 Proportions Comparison of Sexualised Social Media Behaviours between Pre-Intervention and 2018 Surveys
Pre-Intervention Survey 2018 Survey mean mean p- mean p- Male Female Total Male p-value Female Total Sexualised Social Media Behaviour diff diff value diff value Never 164 70.7% 47 65.3% 211 69.4% 340 60.3% 0.10 0.023 124 68.1% -0.03 0.727 464 62.2% 0.07 0.070 Have you ever sent a sexually Don't know 30 12.9% 13 18.1% 43 14.1% 52 9.2% 0.04 0.599 18 9.9% 0.08 0.508 70 9.4% 0.05 0.442 explicit written text message? Yes 38 16.4% 12 16.7% 50 16.4% 172 30.5% -0.14 0.080 40 22.0% 0.22 0.691 212 28.4% -0.12 0.082 Never 122 52.6% 21 29.2% 143 47.0% 275 48.8% 0.04 0.485 86 47.3% -0.18 0.109 361 48.4% -0.34 0.000 Have you ever received a sexually Don't know 25 10.8% 5 6.9% 30 9.9% 45 8.0% 0.03 0.695 12 6.6% 0.00 0.982 57 7.6% 0.02 0.713 explicit written text message? Yes 85 36.6% 46 63.9% 131 43.1% 244 43.3% -0.07 0.280 84 46.2% 0.18 0.053 328 44.0% -0.01 0.861 Have you ever sent a sexually Never 193 83.2% 51 70.8% 244 80.3% 441 78.2% 0.05 0.150 152 83.5% -0.13 0.048 593 79.5% 0.01 0.794 explicit nude or nearly nude photo Don't know 19 8.2% 7 9.7% 26 8.6% 29 5.1% 0.03 0.666 3 1.6% 0.08 0.651 32 4.3% 0.04 0.500 or video of yourself? Yes 20 8.6% 14 19.4% 34 11.2% 94 16.7% -0.08 0.361 27 14.8% 0.05 0.795 121 16.2% -0.05 0.472 Have you ever sent a sexually Never 199 85.8% 65 90.3% 264 86.8% 498 88.3% -0.03 0.366 167 91.8% -0.02 0.715 665 89.1% -0.02 0.324 explicit nude or nearly nude photo Don't know 20 8.6% 3 4.2% 23 7.6% 24 4.3% 0.04 0.558 6 3.3% 0.01 0.946 30 4.0% 0.04 0.571 or video of someone else? Yes 13 5.6% 4 5.6% 17 5.6% 42 7.4% -0.02 0.824 9 4.9% 0.01 0.958 51 6.8% -0.01 0.862 Have you ever received a sexually Never 144 62.1% 32 44.4% 176 57.9% 330 58.5% 0.04 0.463 101 55.5% -0.11 0.273 431 57.8% 0.00 0.982 explicit nude or nearly nude photo Don't know 19 8.2% 2 2.8% 21 6.9% 38 6.7% 0.02 0.836 7 3.8% 0.04 0.947 45 6.0% 0.01 0.888 or video of someone else? Yes 69 29.7% 38 52.8% 107 35.2% 196 34.8% -0.05 0.440 74 40.7% 0.12 0.223 270 36.2% -0.01 0.855 Never 163 70.3% 63 87.5% 226 74.3% 383 67.9% 0.02 0.580 159 87.4% 0.00 0.984 542 72.7% 0.02 0.648 Have you ever used a social media Don't know 23 9.9% 5 6.9% 28 9.2% 50 8.9% 0.01 0.891 9 4.9% 0.05 0.876 59 7.9% 0.01 0.838 site for sexual reasons? Yes 46 19.8% 4 5.6% 50 16.4% 131 23.2% -0.03 0.634 14 7.7% -0.02 0.886 145 19.4% -0.03 0.639 Is sending and receiving naked Never 169 72.8% 51 70.8% 220 72.4% 412 73.0% 0.00 0.961 156 85.7% -0.15 0.016 568 76.1% 0.28 -0.037 pictures a normal thing your Don't know 48 20.7% 17 23.6% 65 21.4% 102 18.1% 0.03 0.705 19 10.4% 0.13 0.288 121 16.2% 0.05 0.379 friends do with each other? Yes 15 6.5% 4 5.6% 19 6.3% 50 8.9% -0.02 0.768 7 3.8% 0.02 0.889 57 7.6% -0.01 0.850 Is sending naked pictures Never 137 59.1% 35 48.6% 172 56.6% 279 49.5% 0.10 0.065 98 53.8% -0.05 0.597 377 50.5% 0.06 0.184 acceptable amongst close friends Don't know 53 22.8% 26 36.1% 79 26.0% 139 24.6% -0.02 0.865 47 25.8% 0.10 0.355 186 24.9% 0.01 0.850 or people who are in a relationship? Yes 42 18.1% 11 15.3% 53 17.4% 146 25.9% -0.08 0.298 37 20.3% -0.05 0.711 183 24.5% -0.07 0.279 Total 232 72 304 564 182 746
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7.4.2 Predictor Variable Comparison
In this section, the predictor factors (as listed in Table 4.1), were compared between the 2018
Survey and Pre-Intervention data. The comparisons were made in four ways:
a. The multiple regression equations (replicated from Table 4.10) were compared using a
Wald Chi Squared test to assess the variance of the independent predictor variables
when regressed on Viewing Prevalence (Table 7.8). The test was applied to both the
overall multiple regressor slope, and for each independent variable within the multiple
regression.
b. The Wald test was repeated separately for each factor in a simple linear regression
(Table 7.9).
c. Two-tail t-tests were conducted to compare variability in the means for each predictor
factor (Table 7.10).
d. A visual comparison of the bivariate correlation matrix from the pre-intervention survey
was made with the 2018 bivariate correlation matrix in Chapter 4 (Table 4.9).
In Table 7.8, there was a significant difference in the overall multiple regression coefficient
(p = 0.043), and a significant variation in the contribution that the factor Parental Rules correlates
with Viewing Prevalence (p = 0.00). That is, Parental Rules contributed to less of the variability in
Viewing Prevalence in the pre-intervention data set, and overall, the multiple-regression model
contributed less to the variability in Viewing Prevalence in the pre-intervention data set.
In Table 7.9, there were significant differences in simple-linear regression coefficients in four of the
11 factors. For the 1st-Time Exposure factor, there was an increase in correlation for the age of first-
time exposure to pornography in the pre-intervention results (p = 0.04). For the Parent Rules factor,
there was a decrease in the correlation between parental rules about pornography access in the pre-
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intervention results (p = 0.00). For the Compulsivity factor, there was less of a correlation between compulsive viewing behaviours in the pre-intervention data (p = 0.01). And for the Distress factor, there was a directional change in the correlation with Viewing Prevalence, where students in the pre-intervention cohort saw an increase in pornography viewing as distress (about their viewing behaviours) increased (p = 0.04).
In Table 7.10, which measures a difference in predictor factor means, there was significant variation in four of the 12 factors. For the Viewing Prevalence factor, there was a significant reduction in average amount of pornography viewed per student (p = 0.01). As previously observed in Table 7.3, this was likely explained by the higher proportion of male students who have never viewed pornography before. For the Religion factor, there was a significant increase in the average religious activity in the life of the student (p = 0.05). The Parent Rules factor was significantly higher in the pre-intervention data set (p = 0.00), meaning students experienced high levels of parental monitoring in relation to pornography and social media access. Lastly, the Peer Behaviours factor mean was lower for the pre-intervention group (p = 0.01), meaning the students believed their close friends viewed less pornography.
In Table 7.11, the bivariate correlation matrix (which includes outcome variables also) was compared with the 2018 Survey correlation matrix in Table 4.9. The blue-coloured cells indicate a difference in coefficient correlation significant levels (where p < 0.05). 39 out of 153 (25.5%) of bivariate relationships differ in significance, with 12 of these experiencing a coefficient directional change
(7.8%). Parent Relationships and Peer Relationships had the greatest number of altered coefficients
(where both the significance level and coefficient direction changed), with three each. However, and consistent with Tables 7.8 and 7.9, the correlations with Viewing Prevalence were mostly unchanged, and therefore it can be concluded that the differences in bivariate matrix relationships are mostly similar.
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Table 7.8 Coefficient Comparisons of Predictor Regressors in Pornography Viewing Multiple Regression Equation
2018 Survey Pornography Viewing Multiple Pre-Intervention Pornography Viewing Multiple Coefficient Regression Table Regression Table Equality Test Std. Std Std. Std Independent Factor Variable β Coeff t-score p-value Coef. t-score p-value Chi2 p-value Err. Beta* Err. Beta* Gender -0.91 0.11 -7.93 0.00 -0.24 -0.56 0.18 -3.08 0.00 -0.15 2.24 0.13 Religion -0.04 0.03 -1.2 0.23 -0.03 0.03 0.06 0.45 0.65 0.02 0.84 0.36 Parent Communication 0.00 0.01 0.18 0.86 0.01 0.00 0.03 0.12 0.90 0.01 0.00 0.98 Parent Rules -0.49 0.18 -2.74 0.01 -0.09 0.02 0.04 0.39 0.70 0.02 8.29 0.00 Peer Behaviours 0.23 0.04 6.41 0.00 0.23 0.29 0.05 5.8 0.00 0.30 0.97 0.33 Peer Attitudes 0.13 0.03 3.96 0.00 0.16 0.19 0.06 3.33 0.00 0.23 0.80 0.37 Attitudes Towards Pornography -0.02 0.00 -3.61 0.00 -0.13 -0.02 0.01 -2.51 0.01 -0.15 0.16 0.69 Sexualised Social Media 0.07 0.01 6.65 0.00 0.19 0.08 0.02 4.08 0.00 0.20 0.20 0.65 Behaviours Model fit: R2=0.50 F= 91.60 N=746 Model fit: R2=0.43 F=27.62 N=307 15.97 0.043 Note: *Standardised Beta coefficients are also provided, to better describe which factors contribute more to Pornography Viewing.
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Table 7.9 Simple Linear Regression of Predictor Variables on Pornography Viewing Frequency
2018 Survey Pornography Viewing Simple Pre-Intervention Pornography Viewing Simple Coefficient Linear Regression Table Linear Regression Table Equality Test Independent Predictor Variable n= Coef Std. Err. t p-value R2 n= Coef Std. Err. t p-value R2 Chi2 p-value 1st Exposure 601 -0.23 0.03 -8.44 0.00 0.11 229 -0.35 0.04 -8.73 0.00 0.25 4.02 0.04 Religion 746 -0.24 0.04 -5.44 0.00 0.04 307 -0.10 0.07 -1.51 0.13 0.01 2.64 0.10 Parent Communication 746 -0.05 0.02 -3.37 0.00 0.02 307 -0.01 0.03 -0.52 0.60 0.00 1.71 0.19 Parent Rules 746 -1.53 0.19 -7.91 0.00 0.08 307 -0.13 0.04 -3.11 0.00 0.03 56.24 0.00 Peer Attitudes 746 0.45 0.03 17.33 0.00 0.29 307 0.42 0.04 9.98 0.00 0.25 0.35 0.55 Peer Behaviours 746 0.55 0.03 19.08 0.00 0.33 307 0.48 0.05 10.09 0.00 0.25 1.75 0.19 Sexualised Social Media Behaviours 746 2.50 0.20 12.41 0.00 0.17 307 0.15 0.02 6.61 0.00 0.13 0.02 0.89 Compulsivity 596 3.35 0.30 11.16 0.00 0.17 229 0.13 0.04 9.98 0.00 0.31 6.03 0.01 Distress 596 -0.03 0.01 -2.59 0.01 0.01 229 0.10 0.02 4.87 0.00 0.00 4.13 0.04 Attitudes to Pornography 746 -0.06 0.00 -14.10 0.00 0.21 307 -0.05 0.01 -7.34 0.00 0.15 0.59 0.44 Intentionality 592 0.63 0.03 19.33 0.00 0.39 209 0.73 0.06 11.92 0.00 0.41 1.57 0.21
Table 7.10 Mean Comparisons of Predictor Variables between 2018 Survey and Pre-intervention Survey 2018 Survey Pre-intervention Mean comparison Predictor Variable n1= x1=̅ SD1 n2= x2=̅ SD2 t-score p-value Viewing Prevalence 746 1.94 1.60 307 1.64 1.73 2.62 0.01 1st Exposure 601 12.12 2.02 229 11.97 2.40 0.88 0.38 Religion 746 1.81 1.33 307 1.99 1.42 -1.94 0.05 Parent Communication 746 3.63 3.64 307 3.48 3.58 0.60 0.55 Parent Rules 746 0.31 0.29 307 2.40 2.25 -24.86 0.00 Peer Attitudes 746 3.05 1.92 307 2.87 2.06 1.36 0.17 Peer Behaviours 746 4.35 1.66 307 4.05 1.79 2.62 0.01 Sexualised Social Media Behaviours 746 4.47 4.25 307 4.04 4.01 1.53 0.13 Compulsivity 596 0.15 0.18 229 0.16 0.20 -0.14 0.89 Distress 593 0.25 0.25 229 0.25 0.28 0.06 0.95 Attitudes to Pornography 746 43.55 12.65 307 43.83 12.99 -0.33 0.75 Intentionality 592 2.22 1.40 209 2.05 0.10 1.56 0.12 158
Table 7.11 Pre-Intervention Bivariate Correlation Matrix
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Viewing Prevalence 1 * Uncommitted Sexual Exploration 2 0.30* * Sexual Objectification of Women 3 0.34* 0.55* * Attitudes to Porn 4 -0.39* -0.50* -0.51* * Parent Communication 5 -0.03 -0.15* -0.04 0.28* * Parental Rules 6 -0.18* -0.30* -0.17* 0.42* 0.54* * Peer Behaviour 7 0.50* 0.14* 0.24* -0.15* 0.14* -0.04 * Peer Attitudes 8 0.50* 0.47* 0.32* -0.62* -0.29* -0.43* 0.40* * Distress from Viewing 9 0.27* -0.16* 0.05 0.22* 0.32* 0.27* 0.23* -0.17* * Compulsivity 10 0.63* 0.16* 0.32* -0.16* 0.06 0.03 0.32* 0.19* 0.46* * Religion 11 -0.09 -0.23* 0.02 0.22* 0.31* 0.29* -0.04 -0.40* 0.24* 0.07 * Parent Relationships 12 -0.10 0.01 0.03 -0.03 0.08 -0.03 0.03 -0.09 -0.00 -0.05 0.05 * Self-Esteem 13 -0.03 0.01 0.09 0.00 0.07 0.08 0.08 -0.01 -0.09 -0.00 0.11* 0.47* * Emotional Stability 14 0.09 0.07 0.21* -0.11* 0.09 -0.01 0.13* 0.00 -0.06 0.03 0.19* 0.19* 0.36* * Social Empathy 15 -0.07 -0.11 -0.06 0.10 0.20* 0.24* 0.08 -0.08 0.03 -0.07 0.20* 0.22* 0.27* 0.116 * Social Conduct 16 -0.16* -0.15* -0.17* 0.09 -0.02 0.01 0.01 -0.14* -0.02 -0.16* -0.03 0.34* 0.21* 0.19* 0.18* * Peer relationships 17 0.012 0.08 0.19* -0.13* 0.13* 0.02 0.08 0.02 -0.02 -0.01 0.11 0.23* 0.37* 0.40* 0.13* 0.21* * Sexualised Social Media Behaviour 18 0.35* 0.23* 0.30* -0.27* -0.01 -0.19* 0.22* 0.28* 0.08 0.25* -0.02 -0.17* -0.01 -0.07 0.01 -0.26* 0.07 * Narcissism 19 0.12* 0.17* 0.28* -0.12* 0.05 0.01 0.12* 0.07 -0.03 0.10 0.11 -0.04 0.24* 0.14* -0.02 -0.34* 0.19* 0.24* * Note: *p < 0.05; blue coloured cells indicate a difference in significance level with respective coefficient from the 2018 bivariate correlation matrix in Table 4.9.
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7.4.3 Outcome Variable Comparison
Two tests were conducted to compare variability in the outcome variables between the pre-
intervention and 2018 studies:
a. A Wald Chi Squared test of coefficient variability for each outcome factor, in a simple
linear regression model where Viewing Prevalence was the independent variable (Table
7.12)
b. Two-tail t-tests were conducted to compare variability in the means for each outcome
factor (Table 7.13).
In Table 7.12, no outcome variable experienced a significant change in coefficient correlation when
regressed on Viewing Prevalence in a simple linear regression.
In Table 7.13, four wellbeing factors had a significant decline in means in the pre-intervention data
set. The mean change in Peer Relationships (p = 0.02), Self-Esteem (p = 0.01), and Emotional Stability
(p = 0.02) all contributed to the fourth final decline, the Super Wellbeing Total (p = 0.01), which is
made up of the six wellbeing factors.
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Table 7.12 Mean Comparisons of Outcome Variables between 2018 Survey and Pre-Intervention Survey
2018 Survey Pornography Viewing Simple Pre-Intervention Pornography Viewing Coefficient Linear Regression Table Simple Linear Regression Table Equality Test p- Independent Outcome Variable n= Coef Std. Err. t p-value R2 n= Coef Std. Err. t R2 Chi2 p-value value Women as Sex Objects 746 0.13 0.02 8.79 0.00 0.09 307 0.16 0.03 6.39 0.00 0.12 1.05 0.31 Uncommitted Sexual Exploration 746 0.17 0.02 9.71 0.00 0.11 307 0.16 0.03 5.39 0.00 0.09 0.10 0.75 Parent Relationships 746 -0.02 0.02 -1.15 0.25 0.00 307 -0.05 0.03 -1.74 0.08 0.01 0.96 0.33 Peer Relationships 746 0.01 0.03 0.18 0.86 0.00 307 0.02 0.06 0.26 0.79 0.00 0.02 0.89 Self-Esteem 746 0.00 0.01 0.32 0.75 0.00 307 -0.01 0.02 -0.51 0.61 0.00 0.33 0.56 Emotional Stability 746 0.02 0.01 2.27 0.02 0.01 307 0.03 0.02 1.51 0.13 0.01 0.09 0.77 Social Conduct 746 -0.17 0.06 -2.89 0.00 0.03 307 -0.17 0.06 -2.89 0.00 0.03 0.04 0.84 Empathy 746 -0.13 0.03 -4.19 0.00 0.02 307 -0.07 0.06 -1.30 0.19 0.01 0.90 0.34 Super Wellbeing Total 746 -0.81 0.50 -1.63 0.10 0.00 307 -0.96 0.88 -1.09 0.28 0.00 0.02 0.88
Table 7.13 Mean Comparisons of Outcome Variables between 2018 Survey and Pre-Intervention Survey
2018 Survey Pre-intervention Mean Comparison Independent Outcome Variable n1= x1=̅ SD1 n2= x2=̅ SD2 t-score p-value Women as Sex Objects 746 7.91 0.13 307 7.96 0.21 -0.01 0.99 Uncommitted Sexual Exploration 746 6.20 0.12 307 6.30 0.19 -0.46 0.65 Parent Relationships 746 16.25 0.14 307 16.17 0.21 0.30 0.76 Peer Relationships 746 7.85 0.06 307 7.59 0.09 2.31 0.02 Self-Esteem 746 21.64 0.20 307 20.72 0.30 2.56 0.01 Emotional Stability 746 12.07 0.21 307 11.20 0.30 2.28 0.02 Social Conduct 746 7.90 0.07 307 7.71 0.10 1.54 0.13 Empathy 746 7.53 0.07 307 7.52 0.10 0.09 0.92 Super Wellbeing Total 746 0.72 0.00 307 0.70 0.01 2.57 0.01
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7.5 Discussion
The comparison between the 2018 Survey results and the pre-intervention survey data
demonstrated that the datasets were mostly consistent. There were very few differences in the
control variable prevalence tables, with more males having never viewed pornography, never sent a
“sext”, and were more religious in the pre-intervention dataset.
The predictor variables were compared both in how they correlated with pornography viewing
prevalence, and how their means compared across the two surveys. Again, there was little statistical
difference, with only Parent Rules, Peer Behaviours, Compulsivity and Distress behaving differently.
Of those four, only Distress displayed a major difference, with the coefficient changing from having a
negative to positive effect on viewing prevalence. These changes may be explained by the increase
in Parent Rules mean in Table 7.10, which in turn correlates with lower Compulsivity and higher
viewing Distress, as demonstrated in both the 2018 (Table 4.9) and pre-intervention bivariate
correlation matrixes (Table 7.11). Therefore, as the Parent-Rules mean has increased, there has been
an amplified response in the Compulsivity and Distress correlations with Viewing Frequency.
The outcome variables had no variation in coefficient correlations. The t-tests comparisons for both
predictor and outcome factors showed little variation in the key factors, notably the increase in
Parent Rules, and reduction in three wellbeing factors.
This study did not seek to explain these differences. Rather, the aim was to assess if these
differences were sufficient to raise concerns about the suitability of the intervention cohort. Since
the intervention was designed to apply its three specific strategies (didactic teaching, peer
engagement and parental engagement) on a cohort typical of the students who did the 2018 survey,
these final observations could be made:
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a. The statistical sample size for the pre- and post-intervention surveys were sufficiently
large to measure a small to medium effect size.
b. The demographic and prevalence data between both survey groups were very similar.
c. The predictor variables behaved mostly the same for both survey groups in correlations
and mean-scores.
d. The outcome variables behaved mostly the same for both survey groups in correlations
and mean-scores, especially the primary outcome factors (Women as Sex Objects,
Uncommitted Sexual Exploration, Attitudes to Pornography and Compulsivity).
The potential for behaviour change from the intervention may be less because of the higher
proportion of unexposed (to pornography) male students, or for students who have parents with a
more rigorous rule-environment. It will be important to stratify the comparison of pre- and post-
intervention outcomes by pornography viewing frequency, to avoid discrepancies from the higher
proportion of males with healthier behaviours towards pornography and sexualised social media
behaviours. Otherwise, nothing suggested that the intervention cohort was not typical of the
intended audience for the pilot program.
Lastly, since these data sets are so similar, it is reasonable to combine them in future studies. This
was done for this thesis, but that may be useful for additional research afterwards.
7.6 Conclusion
The comparison of data between the 2018 survey and the pre-intervention survey showed they
were mostly consistent, providing confidence that the pilot program is suitable for the intervention
cohort. Overall, the consistent correlation behaviours between pornography viewing and the other
study factors, and similarities in factor mean scores, means that the three education strategies can
be applied to the intervention students in the same way as they were designed to apply to the
earlier 2018 students. 163
Chapter 8: Validating and Exploring the Narcissism and Social Media Factors
8.1. Introduction
This chapter follows from the recommendation of Chapter 4 to introduce a Narcissism scale, along
with some survey instruments describing self-promoting social media usage, to explore if narcissistic
behaviours relate to social media behaviours, and if narcissism mediates the interplay between
pornography viewing, sexualised social media behaviours, and self-esteem.
8.1.1. Why is narcissism in adolescents a concern?
Narcissism concerns the “feelings and attitudes towards one’s own self”, often described as a
personality trait spanning normal (healthy) to pathological (intermittent/situational) and disordered
(constant), spectrum disorder [1]. The distinction between healthy and pathological is the
“dysregulation in self-esteem”. It primarily consists of a grandiose self-concept, with behaviours
intended to maintain that self-concept [2]. It has long been associated with excessive sexual
preoccupation, including pornography use, where through fantasy of grandiosity and self-
admiration, a domain of control is enabled over objects of gratification [3]. The relationship between
pornography viewing and higher self-esteem has been observed [3]. However, other studies suggest
that self-esteem reduces as pornography viewing increases [4-6].
Although narcissism associates with high self-esteem [7-9], it characteristically lacks a moral bias,
such that narcissists are often less caring, agreeable, conscientiousness, or moral [7]. The pre-
intervention bivariate matrix in Chapter 7 (Table 7.11) partially supports this — where it is observed
that narcissism highly correlates with positive self-esteem, whilst accompanied by poorer social
conduct.
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Moreover, the narcissist displays a volatile and defensive self-esteem, lacking in relational care and
commitment, whilst desiring admiration. Their interpersonal relationships may lack in commitment
and caring, since they seek admiration but not acceptance [10]. Their romantic relationships are
often fragile, where selfishness and the need for self-praise leads to partner selection skewed to
supplying adulation and idolisation (or, indirectly, a partner who enhances the narcissist by supplying
attractive qualities like appearance, popularity, success). These relationships are marked by
competitiveness, lack of long-term commitment, and seeking out alternative partners [2].
The narcissist often has poor interpersonal skills, but this does not equate to being socially reclusive.
Indeed, they usually are gregarious and entertaining, yet their behaviours target self-enhancement.
They are often extraverted, skilled at cultivating a well-groomed, fashionable appearance to
maintain a self-image consistent with their belief in their attraction [11].
The advent of social media networking sites, apps and tools, has provided an outlet for narcissistic
behaviours. The online environment allows the user to manage a desirable appearance, through
large, albeit superficial, relationship networks [11]. One meta-analysis on social media use and
narcissism observed a consistent pattern of online behaviours prioritising self-presentation, but less
time spent online [12]. Furthermore, the association with grandiose narcissism and self-promoting
behaviours like “selfies”, profile picture ratings, and accumulating followers, is repeatedly confirmed
[2, 7, 8, 11, 13, 14]. Each year, as more self-promoting apps like Instagram, Snap Chat, and Tik Tok,
are released, the risks associated with increasing narcissistic traits amongst adolescents increases,
justifying a study of the associations between narcissism and self-promoting social media
behaviours, sexualised social media behaviours, pornography use, and self-esteem.
8.1.2. The present study
The hypotheses for this study are that social media use is prevalent amongst young people, and this
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correlates with increased narcissistic traits, which mediates the relationship between self-esteem,
pornography viewing, and sexualised social media behaviours.
There are six hypotheses for this study:
1. That earlier first-time access to social media apps (SMAs) would correlate with more
frequent time (H1a), self-postings (H1b), and follower networking (H1c).
2. That more daily time spent on SMAs would correlate with more frequent self-promotion
updates — both profile and selfie updates (H2).
3. Narcissism would increase with more self-profiling (more followers and people following
[H3a]), self-promotion behaviours (selfies and profile updates [H3b]), and profile picture
rating (H3c).
4. Narcissism would correlate with higher self-esteem (H4a), more pornography viewing (H4b),
and more sexualised social media behaviours (H4c).
5. Narcissism would mediate the relationships between self-esteem and both pornography
viewing (H5a), and sexualised social media behaviours (H5b).
6. Sexualised Social Media Behaviours (SSMBs) would correlate with all social media factors in
a positive direction, except for 1st-Time Age of Account Access, which would be reversed
(H6).
8.2. Aim
The study requires three distinct activities to arrive at the goal of assessing narcissism’s mediating
effect on self-esteem.
1. Validate the Narcissism (NPD-13) scale and the social media latent factors and describe the
frequency data for social media usage.
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2. Assess the correlation between the social media variables and narcissism.
3. Assess if narcissism mediates the relationship between pornography viewing, sexualised
social media behaviours, and self-esteem.
8.3. Method
8.3.1. Measures
The instruments selected for this study included the Narcissistic Personality Inventory 13 (NPI-13),
which is a well validated [8, 15, 16] short version of the 40 item Narcissistic Personality Inventory.
Gentile notes that this measure is “the most widely used measure of grandiose narcissism” [15]. For
the social media measures, items from Moon’s study were adapted, including frequency of selfie and
profile picture updates, time spent on social media per day (in minutes), the self-rating of the
student’s most recent selfie, the student’s number of followers, and the amount of people they
follow. These items can be found in Appendix K. This study did not seek to replicate Moon’s analysis,
particularly of the correlation between the narcissism subscales and the individual social media
items used. Only the whole NPI-13 scale was explored. Social media items were condensed into
larger factors, to streamline the investigation.
An additional item measuring the age of 1st-time social media access has been included. It is labelled
“1st-Time Account Age” — similar to the “Age of 1st-Time Viewing” item in Chapter 4. Its addition
helps explore if earlier social media access also increased undesirable behaviours (just as
pornography viewing correlated with, 1st-time exposure age). It is hypothesised that 1st-time social
media access age will correlate with more frequent social media use, more narcissism, high self-
esteem, and increased sexualised social media behaviours.
The description of the pre-intervention study design is described in Chapter 6, Section 3.
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8.3.2. Validating the NPI-13 Scale
The items in the NPI-13 scale are located in Appendix K. Confirmatory factor analysis and Cronbach
alpha analysis were used to validate the Narcissism scale, consistent with scale validation methods in
Chapter 3. Exploratory factor analysis (EFA) was not used since this is already a well-validated
narcissism scale [8]. The NPI-13 comprises three subscales [15]:
a. the Entitlement/Exploitativeness subscale (EE): a maladaptive type of narcissism (“I find it
easy to manipulate people”);
b. the Grandiose/Exhibitionism subscale (GE): also a maladaptive behaviour (“I like to look at
myself in the mirror”);
c. the Leadership/Authority subscale (LA): an adaptive type of narcissism (social boldness,
optimism, and a focus on interpersonal relations with others).
8.3.3. Social media behaviour items
The social media behaviour questions are located in Appendix K. Ten items were used, including
eight from Moon’s study, which helpfully isolate typical self-promoting behaviours [8], and also an
item on 1st-Time Account Age (either “never” or 5–17), and a “most used social media app” item
(options were Instagram, Snap Chat, Facebook, and Other). The choice of social media app was
based on current popularity, although it should be noted that this is a rapidly changing space for
adolescents. For example, in early 2020, after the completion of the intervention in three of the
schools, new social media apps have risen to prominence, including Tik Tok and Vero, whilst
YouTube, Pinterest and Twitter remain highly popular [17]. EFA and principle components analysis
(PCA) was conducted to identify any latent factors.
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8.3.4. Correlation analysis
A bivariate correlation matrix was used to explore the relationships between narcissism, social
media behaviours, and sexualised social media behaviours.
8.3.5. Structural equation modelling (SEM)
Lastly, SEM models were used to describe the mediating effect of Narcissism on the relationships
between self-esteem and pornography viewing and sexualised social media behaviours (SSMBs)
respectively.
8.4. Results
8.4.1. Validation of NPI-13
The Cronbach Alpha score for all items in the NPI-13 was 0.73, which is lower than Moon’s score of
α = 0.85 [8], but the same as Gentile’s score of α = 0.73 [15]. The GE subscale (five items) alpha was
α = 0.65, the LA subscale (four items) was 0.69, and the EE subscale (four items) was 0.43. Gentile
observed that the EE subscale consistently scores low, but concludes that “lower reliability in this
subscale is not uncommon and does not appear to limit its correlations with important external
criteria” [15]. However, considering this weak EE subscale, confirmatory factor analysis was
performed using Stata 16.1.
The scale was validated using confirmatory factor analysis. The model contained four latent factors,
three for each of the subscales, and a higher order latent factor called “Narcissism” made from the
three subscale latent factors. The model was a strong fit, with all subscale items correlating
significantly to their respective latent factor (all were p < 0.05), and the three latent factors were
significantly co-dependent (p < 0.05). For an overall model fit, the RMSEA was 0.03, TLI was 0.95, and
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Coefficient of Determination was 0.96, meaning that the Narcissism factor is a reliable scale when all
13 items are included [18].
8.4.2. Factor analysis of social media items
EFA and PCA was conducted on eight of the 10 social media items (excluding 1st-Time Account
Access Age, and the user’s Preferred App). Following the same validation methodology in Chapter 3,
the loading values were 0.3, and oblique rotations were used. Three factors emerged from the
process:
• Factor 1 (two items): Frequency of “weekly profile picture updates” and “selfie posting”
items
• Factor 2 (three items): “Fashionable”, “Cool”, and “Attractive” profile picture rating items
• Factor 3 (three items): Daily time spent on SMAs (mins), number of followers and people
following items.
Although the daily time spent correlated highly with number of followers and following in factor 3, it
does not logically belong with the following/followers items. So, it remains a separate item.
Thus, the final factors have been relabelled as: Profile Picture Rating (α = 0.88), Networking Depth
(number of followers and people following — α = 0.77), and Selfie Updates (α = 0.64). The single
item factors are 1st-Time Account Age, and Daily Time.
8.4.3. Frequency results
This analysis is only from the pre-intervention data. Of the 307 students (m = 235, f = 72), 289
indicated having had a social media account (94.1%), including 218 males (94%) and 71 females
(98.6%). The average age of First-Time Account Age was 11.8 (m = 11.9, f = 11.6). Table 8.1 shows
that the preferred social media apps for both males and females are Instagram and Snap Chat, with
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a combined preference of 85.7% for males and 98.6% for females. Although males are relatively split
between the two, 75% of females prefer Snap Chat. Table 8.2 shows the average number of
followers and people following. Median results were included because the high standard deviations
show the distribution is very broad.
Table 8.1 Preferred Social Media App
Preferred Social Media Account Male % Female % Total %
Don't have one 5 2.3% 0 0.0% 5 1.7%
Instagram 99 45.6% 17 23.9% 116 40.3%
Snap Chat 87 40.1% 53 74.6% 140 48.6%
Facebook 2 0.9% 0 0.0% 2 0.7%
Twitter 8 3.7% 0 0.0% 8 2.8%
Other 16 7.4% 1 1.4% 17 5.9%
Total 217 100% 71 100% 288 100%
Table 8.2 Followers, Following and Minutes Online
Other Frequency Metrics Males Females Total n= M SD Median n= M SD Median n= M SD Median Number Following 201 411.9 300.0 367 66 547.3 312.3 500 267 445.3 308.1 400 Number of Followers 202 446.2 337.6 390 66 474.2 298.7 390 268 453.1 328.1 390 Minutes Online a Day 203 96.6 117.4 60 60 125.5 100.8 120 263 103.2 114.3 60
8.4.4. Correlation analysis
Table 8.3 shows the correlation between Narcissism, the social media factors, and Sexualised Social
Media Behaviours (SSMBs). Each relationship is considered below.
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Table 8.3 Bivariate Correlation Matrix
Pre-Intervention Bivariate Correlation Matrix of Narcissism and Social Media Factors 1 2 3 4 5 6 7 Narcissism (NPD-13) 1 * Profile Picture Ratings 2 0.37* * Networking Depth 3 0.23* 0.30* * Selfie Updates (weekly) 4 0.09 0.20* 0.29* * Daily Time (min/day) 5 0.11 0.17* 0.28* 1.00* * 1st-Time Account Age 6 -0.13* -0.15* -0.27* -0.20* -0.22* * Sexualised Social Media Behaviours (SSMB) 7 0.24* 0.22* 0.21* 0.19* 0.22* -0.14* * Note: * p>0.05
a. 1st-Time Account Age
The 1st-Time Account Age negatively and significantly correlated with all factors. This supports
hypotheses H1a, H1b and H1c, meaning that students with an earlier exposure to social media
accounts will spend more time on social media, and have higher rates of self-promoting social media
behaviours. Early account access also correlates with increased narcissism and sexualised social
media behaviours.
b. Daily Time
The more time spent per day on social media accounts, the more the other social media behaviours
increased. This supports the hypothesis H2, namely that the frequency of self-promoting postings
would increase when more time was spent daily. The correlation between time spent per day and
narcissism was not significant. This supports Gnambs’ [12] and Bergman’s [19] findings that
narcissism is more associated towards self-promoting behaviours, but less with online duration.
c. Narcissism (NPD-13)
The Narcissism factor was significantly correlated with an increase in Networking Depth (more
followers and people following) supporting H3a, and Profile Picture Rating, supporting H3c.
However, the correlation between Narcissism and weekly Selfie Updates was not significant.
Therefore, hypothesis H3b is rejected.
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d. Sexualised Social Media Behaviour
The SSMB factor correlated with all other factors. The direction of each correlation supports
hypothesis H6.
8.4.5. Path Analysis of Self-Esteem, Narcissism, Pornography and Sexualised Social Media Behaviours
To assess hypotheses H5a and H5b, that Narcissism would mediate the relationships between the
baseline survey’s Pornography Viewing and SSMB factors and Self-Esteem, structural equation
modelling (SEM) was performed. The model used full latent factors, rather than simpler path
analysis (using pre-computed factors), to better account for measurement errors.
To remain consistent with Chapter 4 analysis, this analysis was stratified into three groups: Low
Pornography Use (meaning viewing frequency is “less than monthly”), Regular Pornography Use
(meaning “monthly or more”), as well as a combined total (All Students). Table 8.4 analyses the
direct and indirect effect of Pornography Viewing on Self-Esteem, and Table 8.5 analyses the direct
and indirect effect of SSMB on Self-Esteem, each with Narcissism as the mediator.
8.4.6. Direct and Indirect Effect of Pornography Viewing on Self-Esteem
a. In Table 8.4, Narcissism was observed to have a significant and positive effect on Self-Esteem
in all three groups (as it is in Table 8.5). This proves hypothesis H4a.
b. The direct effect of Pornography Viewing on the mediator Narcissism was significant for All
Students, which supports the findings in Chapter 7. However, the correlation was
insignificant for the two subgroups. Hypothesis H4b was supported overall (p=0.3), but was
not proven for the Low and Regular User subgroups.
c. The direct effect of Pornography Viewing on Self-Esteem across groups was statistically
significant. For Regular Pornography Users, the direct effect approached, but did not reach,
significance. Also, the coefficients between the two subgroups were reversed.
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d. The indirect effect of Pornography Viewing for All Students was significant (p = 0.04), but
insignificant for the Low and Regular subgroups.
e. The total effect of Pornography Viewing on Self-Esteem was insignificant for the All Students
and the Low User groups, but was significant for Regular Users, and negatively correlated.
In assessing hypothesis H5a, that Narcissism would mediate the relationship between Pornography
Viewing and Self-Esteem, we conclude that H5a is upheld for All Students. However, at a subgroup
analysis, it is rejected.
8.4.7. Direct and Indirect Effect of Sexualised Social Media Behaviours on Self-Esteem
a. In Tale 8.5, Narcissism had a significant and positive direct effect on Self-Esteem on all
groups as it did in Table 8.4.
b. The direct effect of SSMBs on the mediator Narcissism was significant and positive for the All
Student and Regular user groups, which was consistent with findings in Chapter 7,
supporting hypothesis H4c. However, for Irregular Viewers the effects were insignificant.
c. The direct effect of SSMBs on Self-Esteem was significant, and negatively correlated, for
both All Students and Irregular Users, but insignificant for Regular Users.
d. The indirect effect of SSMBs was significant and positively correlated for both All Students
and Regular User, but insignificant for Irregular Users.
e. The total effect of SSMBs on Self-Esteem was insignificant for the All Students and Regular
User groups, but significant and negatively correlated for the Irregular User subgroup.
In assessing hypothesis H5b, that Narcissism would mediate the relationship between Sexualised
Social Media Behaviours and Self-Esteem, we conclude that H5b is upheld for the All Students and
Regular User groups, where the indirect effect is significant. However, H5b is rejected for the Low
User subgroup.
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Table 8.4 SEM Pathway Analysis of the Effect of Pornography on Self-Esteem with Narcissism as a Moderator with Latent Factors
All Students n=307 Low Pornography Users (Less than Monthly) n=177 Regular Pornography Users (Monthly or More) n=130 Coef SD z-score p-value Coef SD z-score p-value Coef SD z-score p-value Direct Effect (Pornography – Self-Esteem) -0.04 0.03 -1.51 0.13 0.02 0.13 0.18 0.86 -0.10 0.06 -1.68 0.09 Direct Effect (Pornography – Narcissism) 0.01 0.01 2.16 0.03 0.02 0.02 1.05 0.29 -0.02 0.03 -0.79 0.43 Indirect Effect (Pornography – Self-Esteem) 0.02 0.01 2.07 0.04 0.03 0.03 1.01 0.31 -0.02 0.04 -0.63 0.53 Total Effect (Pornography – Self-Esteem) -0.02 0.03 -0.71 0.48 0.06 0.13 0.43 0.66 -0.12 0.06 -1.93 0.05 Total Effect (Narcissism – Self-Esteem) 1.53 0.44 3.52 0.00 1.41 0.73 1.93 0.05 1.73 0.65 2.65 0.01 Note: Standardised coefficients, R2= 0.02 RMSEA = 0.067 (CI 0.57 – 0.076)
Table 8.5 SEM Pathway Analysis of the Effect of Sexualised Social Media Behaviours on Self-Esteem with Narcissism as a Moderator with Latent Factors
All Students n=307 Low Pornography Users (Less than Monthly) n=177 Regular Pornography Users (Monthly or More) n=130 Coef SD z-score p-value Coef SD z-score p-value Coef SD z-score p-value Direct Effect (SSMB – Self-Esteem) -0.03 0.01 -2.07 0.04 -0.06 0.02 -2.89 0.00 0.00 0.02 -0.21 0.83 Direct Effect (SSMB – Narcissism) 0.01 0.00 3.71 0.00 0.00 0.00 1.10 0.27 0.02 0.01 3.04 0.00 Indirect Effect (SSMB – Self-Esteem) 0.02 0.01 3.32 0.00 0.01 0.01 1.08 0.28 0.03 0.01 2.65 0.01 Total Effect (SSMB – Self-Esteem) -0.01 0.01 -0.45 0.66 -0.05 0.02 -2.55 0.01 0.03 0.02 1.59 0.11 Total Effect (Narcissism – Self-Esteem) 1.68 0.47 3.60 0.00 1.56 0.74 2.09 0.04 1.84 0.73 2.53 0.01 Note: Standardised coefficients, R2= 0.85, RMSEA = 0.063 (CI 0.06 – 0.07)
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8.5. Discussion
This study sought to show that self-promoting social media use is high amongst adolescents and
commences at a young age. Across the study, females engaged more with social media. They were
more likely to have a social media account, be younger when having their first account, use the self-
promoting apps Instagram and Snap Chat, have more followers and people following, spend more
time per day on social media, and receive sexualised content. All students found that with more
social media use, their self-promoting behaviours increased. This then increased likelihood of
Narcissism, which mediated the effects of online sexualised behaviours on Self-Esteem.
Relationships between social media access and usage were observed to strongly associate with
Narcissism, which mediated the effect that pornography viewing and SSMBs had on self-esteem.
The study hypothesised that social media behaviours correlated with increased Narcissism, and that
Narcissism mediated the effects of pornography viewing and sexualised social media behaviours
with self-esteem. The results confirmed all hypotheses 1–4, except for H3b, where the correlation
between Narcissism and weekly Selfie Updates was not significant. Still, this was consistent with
observations by Gnambs [12] and Bergman [19] — that both quantities of time or profile postings
are far less important to the narcissist than the quality of self-presentation and larger social reach. It
is concerning that earlier age for account access correlates across all other factors, as this simple
measure can indicate increased risk to the wellbeing of the adolescent. However, knowing that
earlier age access raises the risks, this provides guidance to those concerned with the welfare and
behaviour of young people about potential benefits of age-restriction. Furthermore, the clear
correlation between narcissism and self-promoting social media behaviours should give immediate
pause on any indifference about the adolescent’s use of social media apps like Instagram and Snap
Chat. These are not just entertainment or communication tools, but potential catalysts for
narcissistic behaviour.
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The hypotheses that Narcissism would mediate the relationship between Pornography Viewing and
Self-Esteem (H5a) was upheld for the All Students group (with an indirect effect through the
Narcissism mediator of p=0.4). Since the primary concern of this thesis is reducing the negative effects of Pornography Viewing on attitudes and behaviours, the Regular User subgroup was particularly relevant. For, although there was no indirect effect through the Narcissism mediator, the total effect of Pornography Viewing on Self-Esteem for Regular Users was negatively and significantly correlated (p=0.01). This both supports the earlier research observed in Chapter 1, that
Self-Esteem does reduce when more pornography is consumed, and also highlights that the relationship between Self-Esteem and pornography does behave differently when stratified into low and regular users. Future research should ensure that adolescent studies on narcissism and online sexualised behaviours stratify the data by the frequency of undesirable behaviours (which in this study was pornography viewing). However, regarding the primary question about how Narcissism affects the relationship – it overall had a small but significant effect.
The hypotheses that Narcissism would mediate the relationship between SSMBs and Self-Esteem was also partially upheld — in this case for the All Students and Regular User groups. Unsurprisingly, the indirect effect was greater for SSMBs than for Pornography Viewing (p < 0.00), most likely because narcissistic opportunities occur more in a public forum. That is, sexualised social media behaviours are visible to others, even if a singular audience through sexting. Narcissism seeks out self-promotion, which social media provides, whilst pornography viewing is essentially a private behaviour. Another observation is that total effect for SSMBs on Self-Esteem was insignificant for All
Students and Regular Users, whilst significant (and negatively correlated) for Low Users (as was the
Low User’s SSMB direct effect). Either way, the coefficient for all groups has become more negative once Narcissism was included as a mediator. Thus, Narcissism appears to have inflated and distorted
Self-Esteem, especially in the Regular User group, where it perfectly mediates the relationship with
Self-Esteem. For, although the bivariate correlation matrixes in both Chapters 4 and 7 showed a
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significant and positive relationship between SSMBs and Self-Esteem, this study shows that once we
account for the mediating effect of Narcissism, this is not true. SSMBs do not increase Self-Esteem,
even if the adolescent, prima facie, feels empowered by such behaviours. It is indicative of a false
Self-Esteem, driven by persistent self-promotion.
More broadly, these observations confirm that social media is a playfield for narcissism, which
promotes sexualised behaviours, presenting additional risks associated with sexting behaviours
including: legal consequences, from the circulation of underaged material, lack of consent, revenge
porn, cyberbullying, and general behaviour [20]. Education against these risks should also include
addressing underlying narcissistic behaviours and attitudes, and also the activities that feed
narcissistic growth, including social media access and self-promoting behaviours.
8.6. Study Limitations
There are limitations to this study, including it being a cross-sectional design. For although the SEM
path analysis explored a theoretical causal relationship, there were no true causal descriptions
described. However, the correlations between 1st-Time Account Access, Narcissism and social media
behaviours (including SSMBs) did suggest causation. Future studies should include analysis on the
effect of 1st-time age of social media use on narcissism and the social media behaviours explored in
this study. Echoing Gnambs [12], they should also include longitudinal designs, to better understand
any causality between social media use, narcissism, and online sexualised behaviours (sexting and
pornography related). Also, since this study shows associations between self-promoting social media
behaviours and harmful effects (including negative sexualised behaviours, reduced self-esteem, and
sexualised social media behaviours often associated with narcissism), interventional studies should
be designed to reduce these negative outcomes.
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Another potential limitation was that the choice of stratifying subgroups in the SSMB/Self-Esteem
exploration by pornography viewing frequency was not theoretically driven, but rather a pragmatic
process matching previous chapter analysis. Other stratifying options could have been used,
including various categories of sexualised behaviours from the SSMB scale, or by gender etc.
Nonetheless, since the primary purpose of the thesis was to explore the effects of, and interplay
between, pornography exposure and the other factors, maintaining the consistent stratifying
method was helpful.
8.7. Conclusion
A high proportion of students in this study use social media apps. The earlier they started, and the
more they self-promoted, the more likely they were to possess narcissistic traits. In turn, narcissism
can have a distorting effect on their self-esteem, cloaking the otherwise negative effects that regular
pornography-use or sexualised social media behaviours would have on self-esteem. Future
interventions designed to address adolescent pornography usage and sexualised social media
behaviours should also address social media behaviours and narcissism.
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8.8. Chapter References
1. Ronningstam, E., A Brief Overview of Identifying, Diagnosing and Treating Narcissistic Personality Disorder. 2016, Harvard Medical School McLean Hospital. 2. McCain, J.L. and W.K. Campbell, Narcissism and Social Media Use: A Meta-Analytic Review. 2016. 3. Kasper, T.E., M.B. Short, and A.C. Milam, Narcissism and Internet Pornography Use. Journal of Sex & Marital Therapy, 2015. 41(5): p. 481-486. 4. Doornwaard, S.M., et al., Lower Psychological Well-Being and Excessive Sexual Interest Predict Symptoms of Compulsive Use of Sexually Explicit Internet Material Among Adolescent Boys. Journal of Youth and Adolescence, 2016. 45(1): p. 73-84. 5. Bélanger, R.E., et al., A U-Shaped Association Between Intensity of Internet Use and Adolescent Health. Pediatrics, 2011. 127(2): p. e330-e335. 6. Wilt, J.A., et al., Associations of Perceived Addiction to Internet Pornography with Religious/Spiritual and Psychological Functioning. Sexual Addiction & Compulsivity, 2016. 23(2-3): p. 260-278. 7. Campbell, W.K., E.A. Rudich, and C. Sedikides, Narcissism, Self-Esteem, and the Positivity of Self-Views: Two Portraits of Self-Love. Personality and Social Psychology Bulletin, 2002. 28(3): p. 358-368. 8. Moon, J.H., et al., The Role of Narcissism in Self-promotion on Instagram. Personality and Individual Differences, 2016. 101: p. 22-25. 9. Pantic, I., et al., Association Between Physiological Oscillations in Self-esteem, Narcissism and Internet Addiction: A Cross-sectional Study. Psychiatry Research, 2017. 258: p. 239-243. 10. Raskin, R., J. Novacek, and R. Hogan, Narcissistic Self-esteem Management. Journal of Personality and Social Psychology, 1991. 60(6): p. 911. 11. Ong, E.Y.L., et al., Narcissism, Extraversion and Adolescents’ Self-presentation on Facebook. Personality and Individual Differences, 2011. 50(2): p. 180-185. 12. Gnambs, T. and M. Appel, Narcissism and Social Networking Behavior: A Meta‐analysis. Journal of Personality, 2018. 86(2): p. 200-212. 13. Antle, B.J. and C. Regehr, Beyond Individual Rights and Freedoms: Metaethics in Social Work Research. Social Work, 2003. 48(1): p. 135-144. 14. Clifton, A., E. Turkheimer, and T.F. Oltmanns, Personality disorder in social networks: Network position as a marker of interpersonal dysfunction. Social networks, 2009. 31(1): p. 26-32. 15. Gentile, B., et al., A test of Two Brief Measures of Grandiose Narcissism: The Narcissistic Personality Inventory-13 and the Narcissistic Personality Inventory-16. Psychological assessment, 2013. 25(4): p. 1120-1136. 16. Brailovskaia, J., H.-W. Bierhoff, and J. Margraf, How to Identify Narcissism With 13 Items? Validation of the German Narcissistic Personality Inventory–13 (G-NPI-13). Assessment, 2017: p. 107319111774062. 17. Robinson, R. The 7 Top Social Media Sites You Need to Care About in 2020: And how to know where to invest your time. 2020 [cited 2020 26 May]; Available from: https://spark.adobe.com/make/learn/top-social-media-sites/. 18. Schermelleh-Engel, K., H. Moosbrugger, and H. Müller, Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-fit Measures. Methods of Psychological Research Online, 2003. 8(2): p. 23-74. 19. Bergman, S.M., et al., Millennials, Narcissism, and Social Networking: What Narcissists Do on Social Networking Sites and Why. Personality and Individual Differences, 2011. 50(5): p. 706- 711. 20. Office_of_the_eSafety_Commissioner, Sexting: Social and Legal Consequences ed. C. Schmidt. 2016: Australian Government.
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Chapter 9: Comparison of Pre- and Post-Intervention Data
9.1. Introduction
In this final chapter of post-intervention analysis, changes in prevalence variables, predictor factors,
and outcome factors are conducted to determine if the intervention was effective. This follows
Chapter 7’s analysis which compared the smaller study cohort with the 2018 urvey study, where it
was confirmed that these students behaved similarly, and are good candidates for the intervention.
In Chapter 8, the analysis of narcissism, which correlated with self-promoting social media
behaviours, mediated the effect that pornography viewing and sexualised social media behaviours
had on self-esteem. Other important questions were raised from the qualitative teacher feedback in
Chapter 6 about the Parental Diary activities, especially whether this was effectively done.
The primary objective of this chapter is to assess if the three strategies deployed in the program
(didactic education, peer-to-peer activities, and parental engagement home activities) have
contributed to a reduction in negative effects from pornography and sexualised social media
behaviours. Secondary areas of interest include whether the levels of narcissism and self-promoting
social media activities responded to the intervention.
The didactic teaching strategy was conducted through multimedia, evidence-based content and
critical-thinking class discussion; the peer-to-peer activities through weekly small-group discussion
sessions; and parental engagement through the weekly parental diary homework.
Through these strategies, the program addressed topics around how pornography affects: the user
(neurologically, attitudinally, and behaviourally); society (including exploitation of participants, pop-
culture, and objectification of women); and relationships (including the impact on intimacy,
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sexuality, trust, and long-term success). Additional lessons addressed problematic social media
behaviours, including self-promotion, sexting, cyberbullying and legal considerations.
The methodology of presenting the content through these two strategies is a new theory, built from
a comprehensive survey of the literature, where some evidence indicated some major negative
effects of pornography exposure and sexualised social media behaviours could be reduced.
9.2. Aim
This study aims to assess changes in knowledge, attitudes and behaviour in students after
participating in the pilot program. The following hypotheses will help assess if the three education
strategies were deployed effectively.
9.2.1. Chapter Hypotheses
Hypothesis 1 – Prevalence change. In terms of prevalence changes, it was hypothesised that:
1a – the six-monthly prevalence would be unaltered; but that
1b – the 14-day viewing would decline;
1c – efforts to reduce viewing would increase in the Regular User (monthly or more) viewing
frequency group;
1d – self-promoting social media behaviours would decline;
1e – the proportion of positive Sexualised Social Media attitudes would improve; and
1f – no prevalence measures would be worse following the intervention.
Hypothesis 2 – Predictor Factor Change. There are four hypotheses for the predictor factors:
2a – the Peer Attitudes would decrease in the factor’s mean score;
2b – the Peer Behaviours would decrease in factor mean score;
2c – Parent Communication would increase in mean score;
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2d – Parental Rules would increase in mean score.
Hypothesis 3 – Outcome factor change. These are primary outcome factor changes expected from
the intervention:
3a – there would be no significant change in the correlation coefficient between outcome
factors and Pornography Viewing;
3b – the Negative Attitudes to Pornography mean score would increase (relflecting higher
negativity about pornography);
3c – the Women as Sex Objects mean score would decrease;
3d – the Attitudes to Uncommitted Sexual Exploration mean score would decrease;
3e – the Viewing Distress mean score would increase (reflecting increased discomfort about
pornography).
In addition to these specific hypotheses, consideration was given to how Compulsivity responds to
the intervention. Was it merely a perceived behaviour, or indicative of actual behavioural
compulsions akin to other behavioural addictions? As previously discussed in Chapter 4, another
interventional study by Fernandez concluded that the Compulsivity scale described an objective,
rather than perceived, behaviour since the efforts to abstain in more compulsive people correlated
in increased failed efforts to abstain [1]. This study can explore similar patterns.
Lastly, although there are no present theories how general wellbeing factors should be affected by
such an intervention, these were observed in the analysis.
9.3. Method
The following measures were used to analyse the data:
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• Chi-squared tests assessed changes in the proportions of categorical data;
• Wald test (chi-squared) assessed mean change in correlation coefficients;
• One and two-tail t-tests assessed mean changes — one-tail tests used when there was a
hypothesised direction change in factor means;
• SEM Path Analysis for direct and indirect relationships.
9.3.1. Prevalence Changes
There are four prevalence areas that can be measured: 1. the frequency of pornography viewing; 2.
the frequency of efforts to abstain from viewing pornography; 3. the frequency of self-promoting
social media behaviours (SSMBs); and 4. the change in attitudes about SSMBs. As can be seen in
Tables 9.1 and 9.2, the data have been stratified into total, low, and regular pornography viewers, as
well as by gender (consistent with the Chapter 4 analysis of the 2018 Survey).
There are two variables that measured viewing prevalence: the six-monthly prevalence factor and
14-day viewing frequency item. Students were asked at the time of each survey (pre- and post-
intervention) how frequently they viewed pornography in both the preceding six months and 14
days. It was not predicted that the six-monthly viewing results would change, since all schools
completed the course in under seven weeks. However, the 14-day viewing was a variable that could
theoretically change over the period of the intervention. The Effort to Reduce Viewing item asked
how often in the last 14-days the students tried not to view pornography.
To assess change in social media self-promotion behaviours, the three factors analysed were Profile
Picture Ratings, Networking Depth, and Selfie Updates (weekly). Since “time online” was not
correlated with narcissism (Chapter 7), it is excluded from this current analysis. T-test comparisons
were used, since these are also continuous variables.
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To assess changes in SSMB attitudes, one question from the SSMB scale describing the student’s
sexualised behaviour on social media, plus two questions about the attitude to normalised
sexualised behaviours, were used. The other SSMB scale questions are historical, and unlikely to
have changed in the study’s intervening period. For this analysis, chi-square proportion tests were
done, since the questions are categorical.
9.3.2. Predictor Factor Changes
There are three ways the predictor factors were measured between pre- and post-intervention: a
comparison of the bivariate correlation matrix, a comparison of coefficient changes for multiple and
single linear regression models, and a comparison of factor means, using t-tests.
The specific areas of interest for predictor factor change included the correlation between Parent
Communication and Parental Rules with Viewing Prevalence, the correlation between Peer Attitudes
on Viewing Prevalence, and mean changes in Negative Attitudes Towards Pornography.
SEM path analysis was used to interrogate the interplay between Negative Attitudes to Pornography
and Compulsivity and their effect on Viewing Prevalence. This may provide future guidance for
students struggling to reduce undesirable viewing behaviours.
9.3.3. Outcome Factor Changes
All primary outcome factors were assessed for correlation changes (with Viewing Prevalence) and
mean change (using t-tests). Of interest are key changes in negative attitudes towards Women as
Sex Objects, Uncommitted Sexual Exploration, Viewing Distress, and Compulsivity.
The secondary outcome factor observations included changes in all six wellbeing factors, both in the
correlation to pornography viewing, and mean changes using t-tests.
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9.3.4. Additional Observations
Other areas of interest for analysis included changes in means of Narcissism, Sexualised Social Media
Behaviours (SSMB), Viewing Prevalence stratified by Low and Regular User students and by Gender,
and changes in self-promoting social media activities.
9.4. Results
9.4.1. Prevalence Variables
a. Viewing over the last six-months
As predicted, Table 9.1 shows no change in the proportions for six-monthly viewing categories
(for males, females and in total). This was also confirmed in Table 9.2, where the frequency of
viewing did not significantly change for all frequency groups. Both a one-tail t-test in Table 9.2
(anticipating a decline) and a two-tail t-test (where p = 0.40, 0.43, and 0.81 for Total, Lower
User and Regular User respectively) showed no significant change. Therefore, hypothesis H1a is
accepted.
b. Viewing over the last 14-days
The more critical metric for short-term viewing behaviour change is the 14-days viewing
frequency item. Since the hypothesis was that this would reduce post-intervention, a one-tail t-
test was preferred for the mean comparison. The change in viewing frequency over the
previous 14-days was insignificant for all frequency groups, and genders, except for the female
low-user group, where a decline just reached a level of significance. Therefore, the hypothesis
that 14-day viewing frequency would decline (H1b) is rejected, except for the subgroup Low
User Females, where there was a significant decline.
c. Efforts to reduce viewing
The hypothesised post-intervention change for this metric was that it would increase, especially
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for more frequent pornography viewers. Infrequent viewers would not be expected to try
harder to abstain, considering they are already low pornography viewers. Table 9.2 shows that
the change in Efforts to Reduce Viewing for all students was insignificant. However, for the
Regular User group, it barely was significant (p = 0.04), meaning that for Regular Viewers,
hypothesis H1c is upheld. d. Viewing intentionality
Additional analysis on the control variable Viewing Intentionality (reported in Chapter 4, Table
4.4) was compared using two-tail t-tests. The comparison was stratified by viewing frequency.
For the total students, the mean change for viewing motivation was insignificant (t = 0.73, p =
0.47). For Low Users (less than once monthly), the mean change in viewing motivation was
insignificant (t = 0.69, p = 0.49). For Regular Users (viewing monthly or more), the mean change
for viewing motivation was insignificant (t = 0.80; p = 0.43). The observation is that viewing
motivation is not impacted by the intervention for all viewing groups. e. Self-promoting social media behaviours
Table 9.3 shows the comparison of social media behaviours, stratified by gender and
pornography viewing frequency. The factor Networking Depth (followers and people following)
significantly reduced for females in the Low User category (p < 0.05). The factor Profile Picture
Ratings also experienced moderate decline (p < 0.1) for the same subgroup (low using females).
Therefore, hypothesis H1d is upheld for females in the Low User subgroup, but rejected for all
males, Regular User females, and in total. f. Sexualised social media behaviours
Chi-squared proportion tests were applied on these categorical questions in Table 9.4. No
significant change was observed in student attitudes about Sexualised Social Media Behaviours,
therefore hypothesis H1e is rejected g. Lastly, there was no increase in prevalence of negative behaviour for any measure, therefore
hypothesis H1f is upheld.
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Table 9.1
Proportions Comparison of Six-Monthly Viewing Prevalence by Gender
Pre-Intervention Survey Post-Intervention p- p- p- Prevalence Table Male Female Total Male mean diff Female mean diff Total mean diff value value value Never 76 32.8% 49 68.1% 127 41.4% 60 29.3% 0.04 0.66 44 63.8% 0.19 0.85 104 38.0% 0.03 0.60 Less than monthly 39 16.8% 11 15.3% 50 16.3% 33 16.1% 0.01 0.94 12 17.4% -0.02 0.89 45 16.4% 0.00 0.99 Monthly 37 15.9% 4 5.6% 41 13.4% 31 15.1% 0.01 0.93 4 5.8% 0.00 0.99 35 12.8% 0.01 0.94 More than once/month but less than once/week 19 8.2% 5 6.9% 24 7.8% 27 13.2% -0.52 0.60 6 8.7% -0.02 0.91 33 12.0% -0.04 0.61 Weekly 45 19.4% 2 2.8% 48 15.6% 38 18.5% 0.10 0.92 1 1.4% 0.01 0.94 39 14.2% 0.01 0.86 More than once/week but less than every day 5 2.2% 0 0.0% 5 1.6% 7 3.4% -0.12 0.90 0 0.0% - - 7 2.6% -0.01 0.91 Daily 11 4.7% 1 1.4% 12 3.9% 9 4.4% 0.00 0.97 2 2.9% - - 11 4.0% 0.00 0.99 Total 232 100% 72 100% 307 100% 205 100% 69 100% 274 100% Note: Two students indicated an “other” gender in the post-intervention source, and have been excluded from this table
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Table 9.2 Pre and Post Intervention Comparisons of Frequency Variables
T-Test Comparisons of Viewing Variables for All Students Frequency Variables Total Low Pornography User (less than monthly) Regular Pornography User (monthly or more) n1= x̅1= n2= x̅2= t-score p-value n1= x̅1= n2= x̅2= t-score p-value n1= x̅1= n2= x̅2= t-score p-value Viewing prevalence of last 6-mths 307 1.64 276 1.77 -0.85 0.80 177 0.35 149 0.40 -0.79 0.78 130 3.40 127 3.37 0.24 0.41 Viewing for previous 14-Days 229 3.37 214 3.44 -0.16 0.56 99 0.97 87 0.62 1.07 0.14 130 5.20 127 5.37 -0.28 0.61 Efforts to Reduce Viewing 214 2.66 202 2.71 -0.24 0.41 86 2.98 76 2.37 1.50 0.93 128 2.45 126 2.92 -1.75 0.04 T-Test Comparisons of Viewing Variables for Male Students Viewing prevalence of last 6-mths 235 1.93 205 2.06 -0.80 0.79 117 0.41 93 0.46 -0.56 0.71 118 3.43 112 3.39 0.24 0.41 Viewing for previous 14-Days 196 3.76 172 4.05 -0.60 0.73 78 1.17 60 0.88 0.65 0.26 118 5.47 112 5.75 -0.43 0.67 Efforts to Reduce Viewing 184 2.72 163 2.79 -0.30 0.38 67 3.07 52 2.60 1.02 0.85 117 2.51 111 2.88 -1.39 0.09 T-Test Comparisons of Viewing Variables for Females Viewing prevalence of last 6-mths 72 0.72 69 0.81 -0.42 0.66 60 0.23 56 0.30 -0.80 0.79 12 3.17 13 3.00 0.34 0.37 Viewing for previous 14-Days 33 1.06 40 0.50 1.02 0.16 21 0.24 27 0.04 1.80 0.04 12 2.50 13 1.46 0.69 0.25 Efforts to Reduce Viewing 30 2.30 37 2.22 -0.13 0.55 19 2.63 24 1.88 -0.91 0.82 11 1.73 13 2.85 1.05 0.15 Note: One-tail tests reported.
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Table 9.3 Pre and Post Intervention Comparisons of Social Media Behaviours
T-Test Comparisons of Social Media Behaviours for All Students Frequency Variables Total Low Pornography User (less than monthly) Regular Pornography User (monthly or more) n1= x̅1= n2= x̅2= t-score p-value n1= x̅1= n2= x̅2= t-score p-value n1= x̅1= n2= x̅2= t-score p-value Profile Picture Rating 289 9.4 246 9.4 -0.08 0.53 162 9.1 130 8.6 0.82 0.21 127 9.8 116 10.4 -0.91 0.82 Networking Depth 289 831.6 246 795.5 0.69 0.24 162 818.3 130 728.3 1.28 0.10 127 848.6 116 870.8 -0.29 0.61 Selfie Updates (weekly) 289 94.4 246 98.2 -0.39 0.65 162 79.5 130 84.6 -0.43 0.67 127 113.4 116 113.5 -0.01 0.50 T-Test Comparisons of Social Media Behaviours for Male Students Profile Picture Rating 216 9.4 177 9.8 -0.60 0.72 102 9.0 77 8.8 0.24 0.40 114 9.9 110 10.5 -0.96 0.83 Networking Depth 216 799.2 177 797.2 0.03 0.49 102 740.9 77 693.3 0.54 0.30 114 851.3 110 877.1 -0.31 0.62 Selfie Updates (weekly) 216 90.2 177 92.0 -0.16 0.56 102 66.0 77 70.6 -0.31 0.62 114 111.8 110 108.5 0.19 0.43 T-Test Comparisons of Social Media Behaviours for Female Students Profile Picture Rating 71 9.4 66 8.41 1.3 0.10 59 9.4 53 8.2 1.31 0.10 12 9.7 13 9.1 0.33 0.37 Networking Depth 71 949.5 66 796.33 1.5 0.07 59 966.0 53 779.1 1.66 0.05 12 868.3 13 866.6 0.01 0.50 Selfie Updates (weekly) 71 106.7 66 114.59 -0.5 0.68 59 102.8 53 104.8 -0.10 0.54 12 125.7 13 154.5 -0.69 0.75
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Table 9.4 Proportion Comparison in Sexualised Social Media Behaviour Attitude Questions
Sexualised Social Media Male Female Total Behaviour Question mean p- mean p- mean p- n1=232 % n2=204 % n1=72 % n2=69 % n1=304 % n2=273 % diff value diff value diff value Never 163 70.3% 134 65.7% 0.05 0.40 63 87.5% 55 79.7% 0.08 0.25 226 74.3% 189 69.2% 0.05 0.25 6. Have you ever used a Don't social media site for sexual 23 9.9% 31 15.2% 0.15 0.57 5 6.9% 11 15.9% -0.09 0.62 28 9.2% 42 15.4% -0.06 0.45 know reasons? Yes 46 19.8% 39 19.1% 0.01 0.94 4 5.6% 3 4.3% 0.01 0.94 50 16.4% 42 15.4% 0.01 0.90 7. Is sending and receiving Never 169 72.8% 144 70.6% 0.02 0.63 51 70.8% 50 72.5% -0.02 0.85 220 72.4% 194 71.1% 0.01 0.77 naked pictures a normal Don't 48 20.7% 39 19.1% 0.02 0.85 17 23.6% 16 23.2% 0.00 0.98 65 21.4% 55 20.1% 0.01 0.86 thing your friends do with know each other? Yes 15 6.5% 21 10.3% -0.04 0.69 4 5.6% 3 4.3% 0.01 0.94 19 6.3% 24 8.8% -0.03 0.76
8. Is sending naked pictures Never 137 59.1% 120 58.8% 0.00 0.96 35 48.6% 45 65.2% -0.17 0.14 172 56.6% 165 60.4% -0.04 0.48 acceptable amongst close Don't 53 22.8% 43 21.1% 0.02 0.84 26 36.1% 19 27.5% 0.09 0.54 79 26.0% 62 22.7% 0.03 0.65 friends or people who are know in a relationship? Yes 42 18.1% 41 20.1% -0.20 0.82 11 15.3% 5 7.2% 0.09 0.62 53 17.4% 46 16.8% 0.01 0.94
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9.4.2. Preliminary bivariate correlation matrix comparison
The post-intervention bivariate matrix, Table 9.5, was a useful metric to assess change from the
intervention. It was compared to the pre-intervention bivariate matrix in Table 7.11. The blue-
coloured cells highlight where correlations differ in significance levels (p < 0.05) across the two
studies. Of the 171 combinations, 33 correlations differed in significance (19.3%). Thus 80.7% of
correlations were similar in terms of significance across all three tables. The red-coloured text
indicates that the correlation direction has changed between pre and post intervention (six in total,
3.5%).
On the surface, most factors correlated consistently across the three surveys, most notably Self-
Esteem and Emotional Stability. However, five factors — Peer Behaviours; Peer Relationships; Parent
Communication; Compulsivity; Narcissism; and Attitudes towards Pornography — had five or more
relationships that behaved significantly differently. Although no definitive conclusions can be drawn
from these observations, as the study was primarily concerned with the relationships between these
factors and Pornography Viewing, it draws attention to factors that may require closer analysis,
including any with additional (and even unforeseen) responses to the intervention.
9.4.3 Predictor Variables
The analysis of the change in predictor variables between pre- and post-intervention follows two
processes:
1. A comparison of coefficient changes for multiple and single linear regression models
2. A comparison of means, using t-tests.
a. Multiple regression comparison
The multiple regression equation used for Table 4.10 was repeated for this analysis, noting that the
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factors Compulsivity and Intentionality were excluded because they would reduce the sample size by
over 25%. A Wald chi-squared test for coefficient change was used to assess if factors correlated
similarly with six-monthly viewing prevalence (Table 9.6). Overall, there was no significant change in
the model (p = 0.35) and R2 = 0.43 (pre) and R2 = 0.44 (post).
Some variations in the individual independent variables were observed, where Gender, Parent
Communication, Parental Rules, and Peer Attitudes experienced change. Only Parental Rules
experienced overall significant coefficient change. Also, prior to the intervention, the Parental Rules
coefficient was not significant with Prevalence Viewing, but post intervention it was. The coefficients
for Gender and Peer Attitudes changed such that they became insignificant post intervention, whilst
the Parent Communication coefficient became significant, when prior to the intervention it was not. b. Simple linear regression comparison
The comparison of coefficients for each predictor variable when observed in a single linear
relationship with Viewing Prevalence (Table 9.7) showed no significant change for any of the factors.
Since Parental Rules was a significant predictor of Viewing Prevalence in the simple linear analysis,
the conclusion about the observed change in Parental Rules for the multiple regression (Table 9.6) is
that it had become more of a contributing factor for Viewing Prevalence post intervention. In other
words, after the intervention, the way parents managed their child’s internet access accounts for
more effect on student viewing behaviours. c. Additional multiple regression observations
In two additional multiple regression analyses of just post-intervention data (Table 9.9), where the
dependent variable was either the six-monthly Viewing Prevalence factor, or the 14-Day Viewing
frequency item, additional predictor independent variables (Compulsivity and Attitudes to
Pornography) were added to the model. Although this lowered the sample size by 22% (n = 214), the
relative contribution of all predictor factors on Viewing Prevalence can be observed. In this model,
the factors Gender, Religion and Parent Communication had no significant effect on either viewing
category, whilst Compulsivity accounted for the most variation in viewing frequency in six-monthly
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and 14-day viewing. Also, Peer Behaviours accounted for 30% of long-term viewing (six-monthly),
whilst Peer Attitudes accounted for 21% of recent (14-day) viewing. Lastly, the six-monthly model
accounted for 54% (R2 = 0.54) of the overall variation in six-monthly viewing, while the 14-day
model only accounted for 36% (R2 = 0.36) of the variation in short-term viewing. This suggests that
the predictor factors will have a greater effect on long-term viewing behaviour, rather than short-
term. d. Mean comparisons of predictor variables
Table 9.8 shows the mean comparisons of the predictor variables. Some of the predictors were
excluded because they also appeared in the Outcome Factor t-Test tables (Tables 9.B, 9.C, and 9.D).
Only one predictor had a significant mean decline – Peer Attitudes, which occurred in the “Regular”
and “All Students” pornography viewing groups. It can be concluded that after completing the
program, students who regularly viewed pornography reduced their belief that the wider peer
culture approved of or engaged with pornography. e. Hypothesis evaluation for predictor variables
Regarding the four predictor factor hypotheses (H2), the following conclusions are made:
• For Peer Attitudes, the decrease in mean score was significant. Therefore, H2a is upheld.
• For Peer Behaviours, the decrease in mean score was insignificant. Therefore, H2b is
rejected.
• For Parent Communication, the increase in mean score was not significant
(p = 0.12 for Regular Users). Therefore, H2c is rejected. However, there was an increase in
correlation with Viewing Prevalence was significant.
• For Parental Rules, the increase in mean score was not significant. Therefore, H2d is
rejected.
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f. Additional observations for predictor variables
• For Peer Attitudes, there was a decreasing trend in the correlation with Viewing Prevalence,
but it was not significant.
• For Parent Communication, there was a significant increase in correlation with Viewing
Prevalence.
• For Parental Rules, there was an increasing trend in correlation with Viewing Prevalence, but
it was not significant.
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Table 9.5 Post-Intervention Bivariate Correlation Matrix 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Viewing Prevalence 1 * Uncommitted Sexual Exploration 2 0.17* * Sexual Objectification of Women 3 0.19* 0.46* * Attitudes to Porn 4 -0.39* -0.47* -0.47* * Parent Communication 5 0.06 -0.07 0.00 0.15* * Parental Rules 6 -0.17* -0.14* -0.02 0.25* 0.54* * Peer Behaviour 7 0.53* 0.11 0.12* -0.16* 0.03 -0.10 * Peer Attitudes 8 0.38* 0.40* 0.26* -0.57* -0.15* -0.32* 0.31* * Distress from Viewing 9 0.34* -0.13* 0.02 0.09 0.33* 0.26* 0.22* -0.13* * Compulsivity 10 0.53* 0.11 0.27* -0.22* 0.23* 0.18* 0.27* 0.06 0.58* * Religion 11 -0.02 -0.27* 0.09 0.13* 0.23* 0.29* -0.01 -0.35* 0.17* 0.13* * Parent Relationships 12 -0.13* -0.11 -0.10 0.15* 0.06 0.00 -0.01 -0.05 -0.05 -0.20* 0.08 * Self-Esteem 13 -0.07 -0.02 0.01 0.11 0.02 0.00 0.06 -0.06 -0.02 -0.02 0.16* 0.46* * Emotional Stability 14 0.11 0.08 0.17* -0.12* 0.03 0.00 0.07 0.06 -0.02 0.11 0.19* 0.12 0.35* * Social Empathy 15 -0.08 -0.08 -0.17* 0.17* 0.09 0.13* 0.01 -0.10 -0.03 -0.13* 0.21* 0.29* 0.35* 0.04 * Social Conduct 16 -0.21* -0.24* -0.30* 0.18* -0.09 -0.01 -0.03 -0.08 -0.15* -0.30* 0.05 0.37* 0.22* 0.18* 0.32* * Peer relationships 17 0.10 0.05 0.00 -0.06 -0.03 -0.06 0.14* 0.13* -0.02 -0.08 -0.01 0.23* 0.28* 0.24* 0.17* 0.20* * Sexualised Social Media Behaviour 18 0.41* 0.23* 0.28* -0.26* -0.08 -0.10 0.24* 0.25* 0.16* 0.34* -0.00 -0.25* -0.07 -0.02 -0.06 -0.35* -0.00 * Narcissism 19 0.13* 0.21* 0.29* -0.15* 0.13* 0.07 0.09 0.018 0.15* 0.24* 0.16* -0.06 0.24* 0.26* -0.05 -0.37* 0.01 0.28* * Note: * means P < 0.05; Blue cells mean either the correlation was a. not significant post-intervention but was significant pre-intervention, or b. was significant post-intervention but not in the pre-intervention bivariate matrix (Table 7.11). Red text means the correlation direction has changed between pre and post intervention.
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Table 9.6 Multiple Regression of Predictor Variables and Viewing Prevalence (Six-Monthly) Comparison
Pre-Intervention Pornography Viewing Multiple Post-Intervention Pornography Viewing Multiple Coefficient Regression Table Regression Table Equality Test Std. Std Std. Std Independent Factor Variable Coef. t-score p-value Coef. t-score p-value Chi2 p-value Err. Beta* Err. Beta* Gender -0.56 0.18 -3.08 0.00 -0.15 -0.22 0.18 -1.21 0.23 -0.06 1.02 0.31 Religion 0.03 0.06 0.45 0.65 0.02 0.06 0.06 1.01 0.32 0.05 0.13 0.72 Parent Communication 0.00 0.03 0.12 0.90 0.01 0.05 0.03 1.95 0.05 0.11 1.54 0.21 Parent Rules 0.02 0.04 0.39 0.70 0.02 0.08 0.04 1.95 0.05 0.11 3.10 0.08 Peer Behaviours 0.29 0.05 5.8 0.00 0.30 0.38 0.05 7.36 0.00 0.38 1.34 0.25 Peer Attitudes 0.19 0.06 3.33 0.00 0.23 0.07 0.06 1.21 0.23 0.08 2.06 0.15 Attitudes Towards Pornography -0.02 0.01 -2.51 0.01 -0.15 -0.03 0.01 -3.35 0.00 -0.19 0.33 0.57 Sexualised Social Media Behaviours 0.08 0.02 4.08 0.00 0.20 0.11 0.02 5.08 0.00 0.25 0.52 0.47 Model fit: R2=0.43 F=27.62 N=307 Model fit: R2=0.44 F=26.24 N=276 8.9 0.35 Note: * Standardised Beta Coefficients included. Table 9.7 Simple Linear Regression of Predictor Variables and Viewing Prevalence (Six-Monthly) Comparison
Pre-Intervention Pornography Viewing Simple Linear Post-Intervention Pornography Viewing Simple Linear Coefficient Regression Table Regression Table Equality Test Independent Predictor Variable n= Coef Std. Err. t p-value R2 n= Coef Std. Err. t p-value R2 Chi2 p-value 1st Exposure 229 -0.35 0.04 -8.73 0.00 0.25 214 -0.23 0.04 -5.50 0.00 0.12 2.48 0.12 Religion 307 -0.10 0.07 -1.51 0.13 0.01 276 -0.03 0.07 -0.40 0.69 0.00 0.59 0.44 Parent Communication 307 -0.01 0.03 -0.52 0.60 0.00 276 0.01 0.03 0.25 0.80 0.00 0.33 0.57 Parent Rules 307 -0.13 0.04 -3.11 0.00 0.03 276 -0.13 0.04 -2.93 0.00 0.03 0.00 0.95 Peer Attitudes 307 0.42 0.04 9.98 0.00 0.25 276 0.35 0.05 6.72 0.00 0.14 0.97 0.32 Peer Behaviours 307 0.48 0.05 10.09 0.00 0.25 276 0.53 0.05 10.22 0.00 0.28 0.58 0.44 Sexualised Social Media Behaviours 307 0.15 0.02 6.61 0.00 0.13 276 0.17 0.02 7.54 0.00 0.17 0.39 0.53 Compulsivity 229 0.13 0.04 9.98 0.00 0.31 214 0.10 0.04 7.01 0.00 0.19 2.48 0.12 Distress 229 0.10 0.02 4.87 0.00 0.00 214 0.11 0.02 5.94 0.00 0.02 0.25 0.61 Attitudes to Pornography 307 -0.05 0.01 -7.34 0.00 0.15 276 -0.05 0.01 -6.84 0.00 0.15 0.01 0.94 Intentionality 209 0.73 0.06 11.92 0.00 0.41 200 0.67 0.07 10.30 0.00 0.35 0.34 0.56 197
Table 9.8 One or Two-Tail T-Test Comparisons of Predictors Variables
Total Students Low User (Less than monthly) Regular User (Monthly or more) Predictor Variable n1= x̅1= n2= x̅2= t-score p-value n1= x̅1= n2= x̅2= t-score p-value n1= x̅1= n2= x̅2= t-score p-value Religion 307 2.0 276 2.0 0.17 0.87 177 2.1 149 2.0 -0.36 0.72 130 1.9 127 2.0 0.76 0.45 Parent Communication 307 3.5 276 3.7 0.88 0.19* 177 3.5 149 3.6 0.13 0.45* 130 3.4 127 3.9 1.17 0.12* Parent Rules 307 2.4 276 2.4 0.06 0.47* 177 2.7 149 2.7 0.16 0.56* 130 2.0 127 2.1 0.49 0.31* Peer Attitudes 307 2.9 276 2.5 -2.18 0.02* 177 2.1 149 2.0 -0.61 0.27* 130 3.9 127 3.2 -3.36 0.00* Peer Behaviours 307 4.1 276 4.1 -0.62 0.27* 177 3.3 149 3.4 0.37 0.36* 130 5.1 127 5.0 -0.21 0.58* Intentionality 209 2.0 200 1.9 -0.73 0.47 82 1.1 76 0.9 -0.69 0.49 127 2.7 124 2.6 0.80 0.43 Note: *=means one-tail test
Table 9.9 Exploratory Multiple Regression of Key Viewing Predictors on Two Viewing Variables
Six-Monthly Viewing 14-Day Viewing Predictor Variable Std β t-score p-value Std β t-score p-value Gender -0.05 -1.17 0.24 -0.09 -1.44 0.15 Religion 0.04 0.76 0.45 0.05 0.84 0.40 Compulsivity 0.37 7.62 0.00 0.36 5.39 0.00 Parent Communication 0.04 0.81 0.42 0.10 1.42 0.16 Parent Rules -0.16 -3.10 0.00 -0.09 -1.32 0.19 Attitudes to Pornography -0.10 -1.81 0.07 -0.11 -1.44 0.15 Peer Behaviours 0.30 6.38 0.00 0.07 1.10 0.27 Peer Attitudes 0.13 2.24 0.03 0.21 2.66 0.01 Sexualised Social Media Behaviours 0.15 3.11 0.00 0.10 1.62 0.11 R2 0.54 0.36 Note: Using standardised coefficients, n=214
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9.4.4 Outcome Variables
a. Regression comparison
The simple linear regressions in Table 9.10 show how the correlation of outcome factors with
pornography viewing changed post intervention, using Wald chi-squared tests. The change in
correlations were insignificant for all factors (when p < 0.05) but there were moderate changes for
Women as Sex Objects (p = 0.06) and Uncommitted Sexual Exploration (p = 0.11), with each factor
having a reduced impact on pornography viewing (R22 < R21). In evaluating hypothesis H3a, there
was no significant changes on how any outcome factor correlated with Pornography Viewing (when
p < 0.05). Therefore, H3a is upheld.
b. Primary outcome factors t-tests
Three tables describe the changes in outcome factors. Table 9.11 shows the changes in mean for all
students, stratified by gender. Table 9.12 shows changes for the Low User group (meaning that over
the previous six months, they viewed pornography less than once per month) and stratified by
gender. Table 9.13 shows the Regular User viewing group (monthly of more), by gender. For the
primary outcome factors Attitudes to Pornography, Women as Sex Objects, Attitudes to
Uncommitted Sexual Exploration, and Viewing Distress, significant change was experienced, which is
reported separately below.
c. Negative Attitudes to Pornography
This factor (where the higher score indicates a healthier, more negative attitude about pornography
and its culture) significantly increased for all three tables and for both genders, with the exception of
Regular User Females (where the sample size was 13). This confirms hypothesis H3b, that negative
attitudes about pornography would increase after the intervention.
This factor can also be considered a predictor factor, since it is well established in past studies that
attitudes are a precursor to behaviour [2-4]. Yet short-term viewing (14-day viewing) did not
decrease for Regular Users post-intervention, even when negative attitudes increased.
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Diagrams 9.1 and 9.2 consider the effect Negative Attitudes to Pornography have on six-monthly and
14-day viewing behaviours using structural equation modelling (SEM) path analysis with
Compulsivity as a mediator. When evaluating the effect of Attitudes to Pornography on Six-Monthly
Viewing Prevalence with Compulsivity as a mediator, for the Regular User group, the total effect of
Attitudes to Pornography on Six-Monthly Viewing was (β = -0.03, t =-3.48, p = 0.00), where the direct effect of Compulsivity on Six-Monthly Viewing was (β = 0.03, t=2.18, p = 0.03). There was no correlation between Negative Attitudes to Pornography and Compulsivity (p = 0.774). Therefore, an increase in Negative Attitudes to Pornography does reduce long-term viewing behaviours. However, this effect was negated by the effect Compulsivity had in increasing six-monthly viewing behaviours.
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Diagram 9.1 Post-Intervention Path Analysis for Attitudes to Pornography and Six-Monthly Viewing Prevalence with Compulsivity as a Mediator for Regular Users
Compulsivity
-0.03 0.18
-0.29
Attitudes to Pornography Six-Monthly Viewing
Diagram 9.1 shows the effect of Attitudes to Pornography on Six-Monthly viewing with Compulsivity as a mediator. The direct effect, using standardised coefficients, was -0.29, while the indirect effect was -0.005. The total effect of Attitudes to Pornography on Six-Monthly Viewing was -0.03 (t = -3.48 p = 0.00)
Diagram 9.2 Post-Intervention Path Analysis for Attitudes to Pornography and 14-Day Viewing Prevalence with Compulsivity as a Mediator for Regular Users
Compulsivity
-0.03 0.31
-0.23
Attitudes to Pornography 14-Day Viewing
Diagram 9.2 shows the effect of Attitudes to Pornography on 14-Day Viewing with Compulsivity as a mediator. The direct effect, using standardised coefficients, was -0.23, while the indirect effect was -0.009. The total effect of Attitudes to Pornography on 14-Day Viewing was -0.09 (t = -3.48 p=0.00)
When evaluating the relationship between Negative Attitudes to Pornography and 14-day Viewing
Prevalence for the Regular User group, with Compulsivity as a mediator, the total effect of Negative
Attitudes to Pornography on 14-day Viewing was (β = -0.09, t = -2.71, p = 0.01), where the direct effect of Compulsivity was (β =0.19, t = 3.75, p = 0.00). Again, there was no correlation between
Negative Attitudes to Pornography and Compulsivity (p = 0.774). Therefore, an increase in Negative
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Attitudes to Pornography does reduce short-term viewing behaviours. However, this effect is
negated by the effect Compulsivity has in increasing 14-day viewing behaviours. d. Women as Sex Objects
There was a reduction in means for the Women as Sex Objects factor for the All Student and Male
subgroups in the Regular User (Table 9.13), but not for any female subgroups or Low User males.
This is partial support for hypothesis H3c, which anticipated a decline in viewing women as sex
objects. e. Uncommitted Sexual Exploration
There was a reduction in means for the Uncommitted Sexual Exploration factor for the All Student
and Male groups in the Regular User results (Table 9.13), but not for any female subgroups or Low
Male users. For all students (Table 9.11) there was a moderate reduction in this factor (p < 0.1).
Therefore, there is support for hypothesis H3d in the Regular Viewing subgroup, which anticipated a
decline in student desires for uncommitted sexual exploration. f. Distress from Viewing
There was a significant increase in Viewing Distress for the Male and All Student Regular User groups
in Table 9.13. Overall, regular pornography viewers experienced more distress about their viewing
after the intervention. This supports hypothesis H3e, that students would feel more uncomfortable
about pornography viewing post-intervention. g. Wellbeing factor and social media behaviour change
Of the six wellbeing factors, there were two factors declined, using two-tail t-tests, contrary to
expectations: Parent Relationships and Peer Relationships. In detail, Parent Relationships declined
for all students in Tables 9.11, 9.12, and almost reached significance in Table 9.13 (p = 0.06). Males
accounted for most of this change, since no female subgroup in any of the three tables had a
significant change in mean for Parent Relationships. h. Peer Relationships
This experienced a significant reduction in the Low User total and female subgroups. No male group
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had a significant reduction in this (Table 9.12). No Regular User group had a reduction in this factor
(Table 9.13). The moderate but insignificant mean declines were experienced by both the female (p
= 0.06) and all students (p = 0.07) groups in Table 9.11.
No other wellbeing factor had a significant change, and importantly, the Super-Wellbeing Total
factor experienced no significant change, meaning that the intervention did not reduce the students’
overall wellbeing. i. Self-promoting social media behaviours
Profile Picture Rating and Follower-and-Following scores for females trended towards decline
(p < 0.1) in Tables 9.11 and 9.12, but not significantly.
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Table 9.10 Ward Test for Coefficient Change in Simple Linear Regression Models
Pre-Intervention Pornography Viewing Simple Linear Post-Intervention Pornography Viewing Simple Linear Coefficient Regression Table Regression Table Equality Test Independent Outcome Variable n= Coef Std. Err. t p-value R2 n= Coef Std. Err. t p-value R2 Chi2 p-value Women as Sex Objects 307 0.16 0.03 6.39 0.00 0.12 276 0.09 0.03 3.22 0.00 0.04 3.55 0.06 Uncommitted Sexual 307 0.16 0.03 5.39 0.00 0.09 276 0.09 0.03 2.90 0.00 0.03 2.55 0.11 Exploration Parent Relationships 307 -0.05 0.03 -1.74 0.08 0.01 276 -0.05 0.02 -2.13 0.03 0.02 0.01 0.92 Peer Relationships 307 0.02 0.06 0.26 0.79 0.00 276 0.10 0.06 1.70 0.09 0.01 1.07 0.30 Self-Esteem 307 -0.01 0.02 -0.51 0.61 0.00 276 -0.02 0.02 -1.12 0.26 0.00 0.17 0.68 Emotional Stability 307 0.03 0.02 1.51 0.13 0.01 276 0.04 0.02 1.86 0.06 0.01 0.13 0.71 Social Conduct 307 -0.17 0.06 -2.89 0.00 0.03 276 -0.20 0.06 -3.51 0.00 0.04 0.19 0.66 Empathy 307 -0.07 0.06 -1.30 0.19 0.01 276 -0.08 0.06 -1.39 0.17 0.00 0.01 0.93 Super Wellbeing Total 307 -0.96 0.88 -1.09 0.28 0.00 276 -1.04 0.89 -1.16 0.25 0.00 0.00 0.95 Narcissism 307 0.07 0.04 2.12 0.04 0.01 276 0.08 0.04 2.13 0.03 0.02 0.00 0.99
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Table 9.11 Mean Change in Outcome Variables for All Students
All Students Males Females t- p- Outcome Factor n1= x̅1= n2= x̅2= t-score p-value n1= x̅1= n2= x̅2= t-score p-value n1= x̅1= n2= x̅2= score value Attitudes to Pornography 307 43.8 276 48.6 4.47 0.00* 232 43.0 204 46.8 3.00 0.00* 72 46.1 69 54.7 4.8 0.00* Women as Sex Objects 307 7.9 276 7.7 0.76 0.22* 232 8.6 204 8.3 0.86 0.19* 72 5.6 69 5.7 -0.1 0.53* Uncommitted Sexual Exploration 307 6.3 276 5.9 1.27 0.10* 232 6.4 204 6.2 0.81 0.21* 72 5.8 69 5.3 1.1 0.15* Parent Relationships 307 16.2 276 15.4 -2.38 0.02 232 16.4 204 15.7 -1.87 0.05 72 15.4 69 14.6 -1.1 0.29 Peer Relationships 307 7.6 276 7.3 -1.84 0.07 232 7.6 204 7.5 -0.90 0.39 72 7.4 69 6.9 -1.9 0.06 Self-Esteem 307 20.7 276 20.8 -0.12 0.90 232 21.0 204 21.3 -0.49 0.69 72 19.6 69 19.5 0.1 0.92 Emotional Stability 307 11.2 276 11.3 0.25 0.80 232 12.1 204 12.4 0.52 0.63 72 8.1 69 8.0 0.0 0.99 Social Conduct 307 7.7 276 7.6 -0.51 0.61 232 7.7 204 7.7 0.15 0.99 72 7.7 69 7.5 -0.9 0.99 Empathy 307 7.5 276 7.4 -0.96 0.34 232 7.5 204 7.4 -1.01 0.34 72 7.5 69 7.5 0.0 0.98 Super Wellbeing Total 307 0.7 276 0.7 -1.29 0.20 232 0.7 204 0.7 -0.57 0.52 72 0.7 69 0.6 -1.1 0.85* Compulsivity 229 5.6 214 5.5 0.14 0.44* 193 6.0 171 6.2 -0.26 0.60* 33 2.8 40 1.9 0.6 0.29* Distress from Viewing 229 4.5 214 5.1 -1.27 0.10* 193 4.6 171 5.4 1.48 0.07* 33 3.9 40 3.9 0.0 0.51* Sexualised Social Media Behaviours 307 4.0 276 4.1 -0.33 0.63* 232 3.8 204 4.0 -0.36 0.64* 72 4.8 69 4.5 0.5 0.31* Profile Picture 289 9.4 246 9.4 -0.08 0.53* 216 9.4 177 9.8 -0.60 0.72* 71 9.4 66 8.4 1.3 0.10* Followers and Following 289 831.6 246 795.5 0.69 0.24* 216 799.2 177 797.2 0.03 0.49* 71 949.5 66 796.3 1.5 0.07* Profile Weekly Updates 289 94.4 246 98.2 -0.39 0.65* 216 90.2 177 92.0 -0.16 0.56* 71 106.7 66 114.6 -0.5 0.68* Narcissism 307 3.8 276 3.8 0.03 0.49* 232 4.1 204 4.0 0.11 0.46* 72 3.2 69 3.7 0.0 0.48* Note: * t-tests are one-tail. Wellbeing factors are two-tail, since no theory suggests they will change from the intervention.
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Table 9.12 Mean Change in Outcome Variables for Low Pornography Users (less than monthly)
All Students Males Females Outcome Factor n1= x̅1= n2= x̅2= t-score p-value n1= x̅1= n2= x̅2= t-score p-value n1= x̅1= n2= x̅2= t-score p-value Attitudes to Pornography 177 47.1 149 52.4 4.05 0.00* 115 47.3 93 50.2 1.61 0.06 60 46.6 56 56.2 5.40 0.00 Women as Sex Objects 177 7.0 149 7.3 -0.61 0.73* 115 7.8 93 8.1 -0.61 0.73 60 5.4 56 5.8 -0.67 0.75 Uncommitted Sexual Exploration 177 5.6 149 5.5 0.33 0.37* 115 5.5 93 5.6 -0.16 0.57 60 5.7 56 5.3 0.73 0.23 Parent Relationships 177 16.5 149 15.8 1.65 0.05 115 17.0 93 16.2 1.61 0.11 60 15.5 56 15.0 0.53 0.60 Peer Relationships 177 7.6 149 7.2 -2.16 0.02 115 7.7 93 7.4 -1.06 0.30 60 7.3 56 6.7 -2.16 0.03 Self-Esteem 177 20.7 149 21.1 0.74 0.23 115 21.3 93 21.9 0.94 0.16 60 19.7 56 19.8 0.20 0.84 Emotional Stability 177 10.9 149 10.9 -0.05 0.52 115 12.6 93 12.4 0.32 0.78 60 7.9 56 7.9 0.04 0.97 Social Conduct 177 8.0 149 7.9 -0.38 0.65 115 8.1 93 8.2 0.42 0.72 60 7.7 56 7.4 0.99 0.32 Empathy 177 7.6 149 7.5 -0.38 0.65 115 7.7 93 7.6 -0.51 0.72 60 7.4 56 7.4 -0.08 0.94 Super Wellbeing Total 177 0.7 149 0.7 -0.91 0.37 115 0.7 93 0.7 -0.26 0.80 60 0.7 56 0.6 -0.91 0.36 Compulsivity 99 2.2 87 2.0 0.40 0.65* 76 2.6 60 2.7 -0.21 0.42* 21 1.0 27 0.4 1.26 0.11* Distress from Viewing 99 4.5 87 3.8 0.90 0.82* 76 4.9 60 4.3 0.62 0.73* 21 3.6 27 2.7 0.62 0.73* Sexualised Social Media Behaviours 177 2.9 149 3.0 -0.28 0.39* 115 2.2 93 2.3 -0.40 0.35* 60 4.2 56 4.0 0.36 0.64* Profile Picture 162 9.1 130 8.6 0.82 0.21* 102 9.0 77 8.8 0.24 0.40* 59 9.4 53 8.2 1.31 0.10* Followers and Following 162 818.3 130 728.3 1.28 0.10* 102 740.9 77 693.3 0.54 0.30* 59 966.0 53 779.1 1.66 0.05* Profile Weekly Updates 162 79.5 130 84.6 -0.43 0.67* 102 66.0 77 70.6 -0.31 0.62* 59 102.8 53 104.8 -0.10 0.54* Narcissism 177 3.5 149 3.6 -0.21 0.58* 115 3.7 93 3.8 -0.34 0.63* 60 3.1 56 3.1 -0.01 0.50* Note: * t-tests are one-tail. Wellbeing factors are two-tail, since no theory suggests they will change from the intervention.
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Table 9.13 Mean Change in Outcome Variables for Regular Pornography Users (monthly or more)
All students Males Females
Outcome Factor n1= x̅1= n2= x̅2= t-score p-value n1= x̅1= n2= x̅2= t-score p-value n1= x̅1= n2= x̅2= t-score p-value Attitudes to Pornography 130 39.4 127 44.2 2.97 0.00* 117 38.7 111 44.0 3.11 0.00* 12 43.6 13 48.0 0.79 0.22 Women as Sex Objects 130 9.1 127 8.2 2.08 0.02* 117 9.4 111 8.5 1.93 0.03* 12 6.8 13 5.2 0.98 0.17 Uncommitted Sexual Exploration 130 7.2 127 6.5 1.78 0.04* 117 7.3 111 6.7 1.49 0.07* 12 6.4 13 5.2 0.89 0.19 Parent Relationships 130 15.8 127 14.9 -1.60 0.06 117 15.8 111 15.2 -0.98 0.28 12 15.2 13 12.9 -1.25 0.22 Peer Relationships 130 7.6 127 7.5 -0.33 0.63 117 7.6 111 7.5 -0.19 0.88 12 7.7 13 7.7 0.05 0.96 Self-Esteem 130 20.7 127 20.3 -0.54 0.70 117 20.8 111 20.8 -0.10 0.85 12 19.3 13 18.0 0.51 0.62 Emotional Stability 130 11.6 127 11.8 0.34 0.37 117 11.9 111 12.2 0.48 0.64 12 8.9 13 8.6 -0.20 0.85 Social Conduct 130 7.3 127 7.3 0.10 0.46 117 7.4 111 7.3 -0.13 0.99 12 7.8 13 7.7 -0.08 0.94 Empathy 130 7.4 127 7.2 -0.79 0.79 117 7.8 111 7.8 0.02 0.39 12 7.4 13 7.2 -0.92 0.99 Super Wellbeing Total 130 0.7 127 0.7 -0.84 0.40 117 0.7 111 0.7 -0.37 0.64 12 0.7 13 0.7 -0.55 0.59 Compulsivity 130 8.2 127 7.9 0.28 0.39* 117 8.2 111 8.1 0.15 0.44* 12 5.8 13 5.0 0.22 0.41* Distress from Viewing 130 4.5 127 6.0 2.42 0.01* 117 4.4 111 5.9 2.40 0.01* 12 4.3 13 6.2 -0.80 0.22* Sexualised Social Media Behaviours 130 5.6 127 5.6 0.17 0.43* 117 5.5 111 5.4 0.20 0.42* 12 7.7 13 6.6 0.60 0.28* Profile Picture 127 9.8 116 10.4 -0.91 0.82* 114 9.9 110 10.5 -0.96 0.83* 12 9.7 13 9.1 0.33 0.37* Followers and Following 127 848.6 116 870.8 -0.29 0.61* 114 851.3 110 877.1 -0.31 0.62* 12 868.3 13 866.6 0.01 0.50* Profile Weekly Updates 127 113.4 116 113.5 -0.01 0.50* 114 111.8 110 108.5 0.19 0.43* 12 125.7 13 154.5 -0.69 0.75* Narcissism 130 4.3 127 4.2 0.43 0.33* 117 4.4 111 4.2 0.57 0.28* 12 3.7 13 3.5 0.17 0.44* Note: * t-tests are one-tail. Wellbeing factors are two-tail, since no theory suggests they will change from the intervention.
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Table 9.14 Summary of Significant Results for Factor Mean Score Change
Table Factor P-value
9.2 Efforts to reduce viewing – All Student Regular User group 0.04
9.2 Reduced Viewing over previous 14-Days – Low User Female group 0.04
9.3 Reduced Networking Depth (followers and following) – Low User Female group 0.05
9.8 Reduced Peer Attitudes mean score – Total Student and Regular User groups 0.02; 0.00
9.11 Increased (negative) Attitudes to Pornography mean score – All groups 0.00
9.13 Decreased Women as Sex Objects mean score – Regular User Male and Regular All Students groups 0.02, 0.03
9.13 Decreased Uncommitted Sexual Exploration mean score – Regular All Students group 0.04
9.13 Increased Distress from Viewing mean score – Regular User Male and Regular All Students groups 0.01, 0.01
9.11–12 Decreased Parent Relationships mean score – All Students/Male Total, All Students Low User groups 0.02, 0.05
9.12 Decreased Peer Relationships mean score – All Students and Female Low User groups 0.02, 0.03
9.12 Reduced Followers and Following (Networking Depth) – Low User Female group 0.05
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Table 9.15 Summary of Hypotheses Results
Hypothesis Proven Not Proven
H1a Six-monthly prevalence will be unaltered Proven for all groups
H1b The 14-day viewing would decline Proven for Low User Not proven for all other Female group groups
H1c Efforts to reduce viewing would increase in the Proven for Regular User Regular User group
H1d Self-promoting social media behaviours would Proven for Low User Not proven for all other decline Female group groups
H1e Proportion of positive Sexualised Social Media Not proven for all groups attitudes would improve
H1f No prevalence measures would be worse Proven for all groups following the intervention
H2a Peer Attitudes will decrease in mean score Proven for the Total Not proven for Low User Students and Regular User group groups
H2b Peer Behaviours will decrease in mean score Not proven for all groups
H2c Parent Communication will increase in mean Not proven for all groups score
H2d Parental Rules increase in mean score Not proven for all groups
H3a There will be no significant change in the Proven correlation coefficient between outcome factors and Pornography Viewing
H3b (Negative) Attitudes to Pornography mean Proven for all groups Not proven for Regular score would increase except one User Females
H3c The Women as Sex Objects mean score would Proven for Regular User Not proven for all Female, decrease Male and Regular All Low User Males, or All Students groups Students groups
H3d The Attitudes to Uncommitted Sexual Proven for Regular All Not proven for all Female, Exploration mean score would decrease Students groups Low User Males, or All Students groups
H3e The Viewing Distress mean score would Proven for Regular User Not proven for all Female, increase Male and Regular All Low User Males, or All Students groups Students group
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9.5 Discussion
The study examined whether the education program could reduce the negative effects of
pornography exposure and sexualised social media behaviours, through the three strategies of
didactic education, peer-to-peer activities, and parental engagement home activities. The
quantitative results confirm that many negative behaviours were improved and some of the
strategies were enhanced by the intervention.
9.5.1 The positive behaviour changes
The increase in efforts to reduce viewing for regular pornography users is an important indicator
that students desired and attempted behaviour change. Intentions are important indicators for
future behaviour change [4]. Additionally, the four primary outcome factors did significantly improve
after the program. All students experienced an increase in negative attitudes towards pornography,
regardless of their viewing frequency. And for regular pornography users, they experienced a
decreased desire for uncommitted sexual relationships, belief that women are sex objects, and an
increase in distress from viewing. Thus, knowledge, attitudes and beliefs were successfully changed,
and the program was particularly effective for current pornography users.
The increase in distress for students who regularly view pornography is not a negative outcome from
the intervention. Rather, it indicates that students felt increased unease and discomfort about their
amount of pornography viewing. Since Distress negatively correlates with Pornography Viewing, this
is a potential contributor to future reduction in pornography viewing.
In addition, promising changes to self-promoting social media behaviours occurred in females. Since
females are less likely to view pornography, yet more likely to: have a social media account, be
younger when having their account, use the self-promoting apps Instagram and Snap Chat, have
more followers and people following, spend more time per day on social media, and receive
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sexualised content — the components of the program addressing problematic social media
behaviours appeared to have resonated with them.
One fear from completing the program would be that it increased negative behaviours or reduced
wellbeing. There was no evidence of this. Pornography viewing did not increase, but for the Low
User female subgroup, declined in 14-day frequency. Considering that students encountered
prolonged discussion on the pornography topic, there was a risk that this could entice more
engagement. Concerns that exposing students to a program on pornography might induce excessive
curiosity have been waylaid. Overall, positive changes were experienced across the entire study
population, with no observable adverse effects.
9.5.2 Long-term effect of the intervention
In terms of the longer-term effects of the program, it is not possible within the limitations of the
study to perform further surveys. However, some clues about the potential for long-term change
were observed in the expanded multiple regression models in Table 9.9. When comparing the effect
of all predictor factors on longer (six-monthly) and short-term viewing (14-day) behaviours, short-
term viewing frequency was less determined by the combined predictor factors (R2 = 0.36), with
only Compulsivity and Peer Attitudes being the contributing factors. Yet, for six-monthly behaviours,
most predictor factors had a significant effect, and a larger overall effect (R2 = 0.54). These
observations offer clues to the ongoing effectiveness of changes to these predictor factors. So,
although it can be concluded that any modification to predictor factors from the intervention will
have little influence on short-term behaviours, they may have significance for longer-term influence.
An outstanding theoretical question about relationship between Attitudes to Pornography and
Pornography Viewing is whether it is a predictor or outcome factor. Since this factor increased after
the intervention, with no change in Viewing Prevalence (Tables 9.1 and 9.2), it follows that it is not
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just an outcome factor. There is an opportunity for future studies to focus on the long-term effects
of all predictor factor change on student behaviours, including Negative Attitudes to Pornography as
a predictor factor, that could resolve these questions.
9.5.3 The unsuccessful viewing behaviour change
A central aim for the study was that short-term viewing prevalence would decline for regular
viewers. This did not happen. On the surface this seems that the program was inadequate for
achieving this aim. However, there are further considerations that can be made.
There may not have been enough time prior to the post-intervention survey to allow for behaviour
change. Most schools performed this within a week from the final lesson of intervention. Also, the
largest school (contributing about two-thirds of the study sample) completed the two surveys within
28 days of each other. However, this “lack-of-time” reason is unlikely, because increased Efforts to
Reduce Viewing, Viewing Distress, and Negative Attitudes Towards Pornography amongst the post-
intervention Regular User group significantly increased. The students were unable to convert efforts
to reduce viewing into success.
The most likely reason for this is that compulsive behaviours in frequent viewers were too potent to
offset the desire to change. This was supported in Table 9.9 where Compulsivity contributed most to
viewing behaviours. Furthermore, the SEM pathway analysis (Diagrams 9.1 and 9.2), confirmed there
was a significant direct effect on reduced pornography viewing from an increase in Negative
Attitudes to Pornography, but this was offset by Compulsivity. Both factors had approximately equal
and opposite effects on Viewing Prevalence, and yet Compulsivity and Attitudes to Pornography did
not correlate. What this suggests is that education programs are not enough to adjust negative
viewing behaviours in compulsive subjects.
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Regarding the nature of the compulsive behaviours, the increase in efforts to reduce viewing but
with no reduction in viewing frequencies supports the previous research by Fernandez [1] that
compulsive pornography viewing is not merely perceived, but objectively real, consistent with other
behavioural addictions. Strengthening the addiction behavioural argument is the parallel between
questions on the Compulsivity scale and various prerequisite conditions for Internet Gambling
Disorder (addiction) in the DSM-5. Appendix L contains the nine criteria for conditions, any four of
which are required for a diagnosis. Alongside seven of the DSM-5 conditions are either the baseline
survey Compulsivity scale questions (which have similarities), or post-intervention survey results
showing how Efforts to Reduce Viewing and Viewing Distress positively correlate with Compulsivity.
Thus, when applying similar criteria to similar DSM-5 guidelines, coupled with the study’s main
observations that Compulsivity impedes the influence of Negative Attitudes to Pornography, whilst
increased Efforts to Reduce Viewing are ineffective at reducing actual viewing frequency, it seems
reasonable to define compulsive pornography use as an actual behavioural addiction. At any rate,
students, by age 15, are exhibiting compulsive behaviours that intrude on their intentions and
efforts, suggesting they require additional support to address the specific compulsivity problem,
through specialist therapy or other evidence-based addictive behaviour interventions. Future studies
may consider adapting a questionnaire with items similar to the DSM-5 Gambling addiction criteria.
9.5.4 Effectiveness of the three strategies
a. The effect of the didactic education strategy
The intervention was effective in various ways, notably increasing a negative view about
pornography, but it is not possible to distinguish how each of the three-education strategies
contributed to this. There were some change in knowledge about pornography, as indicated by the
rise in Negative Attitudes Towards Pornography – which had elements corresponding to the first
four lessons. There were mild changes to social media behaviours, which corresponded to the last
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two lessons. So, it is likely the teaching content (didactic education strategy) contributed to that. But
the data also supports some contribution from the other two strategies.
b. The effect of the parental-engagement strategy
Parental activities were anticipated to have a minimal impact, in light of the teacher feedback that
the Parental Diary component was poorly done (Chapter 6). However, two observations suggest this
strategy was not ineffective: 1. both Parent Communication and Parental Rules became more
correlated with Viewing Prevalence after the intervention. This shows that students became more
sensitive to their parent’s contribution to their attitudes and behaviours. 2. The students, especially
males, believed their relationship quality with parents declined after the intervention. This
observation may illuminate why teachers reported parental engagement was difficult. It is plausible
that students found the Parental Diary activity was a catalyst for tension, especially if parents
attempted to elevate their concerns or increase monitoring and restrictions. Additionally, some
teachers reported that students felt uncomfortable about the parental conversations. Thus, the
parental strategy may have stalled after it was attempted, rather than just ignored from the outset.
For future iterations of the programs, these challenges should be anticipated, and additional
resources should be considered to prepare and guide parents, students, and teachers through the
activities.
c. The effect of the peer-engagement strategy
The reduction in the Peer Attitudes factor mean score can be attributed to the concentrated peer-
engagement activities throughout the program. The process of peer discussions, debates, and
trouble-shooting questions together, achieved the goal of students being less influenced by the
backdrop of peer pressure, wider trends, and normalised culture. Peer discussions provided
opportunity to challenge Peer Attitudes, empowering the student’s agency over their thinking. It is
noted that the activities of closer friendship contacts, measured in the Peer Behaviours factor, had
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no significant change following the intervention (both in correlation to pornography viewing, and
mean differences). This is unsurprising, since the intervention did not attempt to address or alter
who the students associated with outside of class. However, since the outcome factor Peer
Relationships had a moderate decline for female students (Tables 9.11 and 9.12), understanding why
this occurred can inform future iterations of the program. Did females find their relationships
reduced because they were required to discuss uncomfortable issues that they have no personal
problem with? Did debate produce fundamental disagreements? Did they have a reduced view of
peers with potential pornography behaviour problems? These questions should be pursued in future
research. One plausible explanation is related to the program’s social media content, which may
have redefined what real friendships were, since it was Low User females who also experienced a
significant reduction in the Networking Depth factor (measuring friends and followers). Without
direct student qualitative data, the only guide to how they responded to the peer discussions was via
teacher feedback, which was positive. This also should be investigated in future studies.
9.5.5 Study Limitations
There were several limitations to this study. The student sample sizes were not large, especially for
females in the Regular Viewing subgroup. Students were from independent schools in NSW,
Australia – and although the demographic analyses of Chapters 4 and 7 suggested they were
otherwise typical, there is little known about how generalisable their ethnic, academic, and socio-
demographic situations are. The students were not randomly allocated, nor was there a true control
group, which would have improved the reliability of the findings. The period between the pre- and
post-intervention surveys was not long. A longer period before follow-up would have strengthened
this study. Lastly, it was not possible to isolate the unique impact of the three education strategies.
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9.6 Conclusion
This study found that the pilot program contributed to a reduction in various negative effects from
pornography exposure. Students improved in their negative attitudes towards pornography, whilst
regular pornography viewers developed more positive views towards women, and more responsible
attitudes towards relationships. Additionally, regular pornography users increased their efforts to
reduce viewing, while feeling more distressed about using pornography. In addition, female students
experienced small reductions in self-promoting social media behaviours and pornography viewing
frequency, whilst experiencing moderate declines in peer relationships. Not all hypotheses were
proven, and there were small reductions in peer and parental relationships for some subgroups.
However, no student developed problematic behaviours or attitudes after doing the course.
The three education strategies were observed to bring about these changes, with increased
knowledge, and a reduction in the influence of wider peer culture, the most notable. There was
some evidence that the parental engagement strategy did increase the effect of parental
communication and rules on problematic viewing behaviours.
Three challenges also arose from the study:
1. Compulsive viewing behaviours had a serious influence on students, negating the positive
gains of improved attitudes and increased efforts to reduce undesirable behaviours.
2. Parent-student relationships may face tension from the home engagement activities.
3. Female peer-relationships may face tension from the peer discussions or from the social
media teaching content.
Overall, this pilot program, targeting the reduction of negative effects from pornography exposure,
sexualised social media behaviours, and self-promoting social media behaviours, using the three
strategies of didactic education, peer-to-peer engagement, and parental activities, was effective.
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For future studies, the following should be considered:
1. An examination of the longer-term effect of predictor factors on behaviour change.
2. Encouragement of students with compulsivity behaviours to receive additional therapeutic
help.
3. Exploration of each education strategy in isolation from each other.
4. Development of a questionnaire with components similar to the DMS-5 criteria for other
behaviour disorders/addictions.
5. Conducting of qualitative feedback with students and parents.
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9.7 Chapter References
1. Fernandez, D.P., E.Y.J. Tee, and E.F. Fernandez, Do Cyber Pornography Use Inventory-9 Scores Reflect Actual Compulsivity in Internet Pornography Use? Exploring the Role of Abstinence Effort. Sexual Addiction & Compulsivity, 2017. 24(3): p. 156-179. 2. Wood, R.T.A. and M.D. Griffiths, Adolescent Lottery and Scratchcard Players: Do Their Attitudes Influence Their Gambling Behaviour? Journal of Adolescence, 2004. 27(4): p. 467- 475. 3. Neighbors, Foster, and C.D.N.W. Fossos, Peer Influences on Addiction. 2013. p. 323-331. 4. Bagozzi, R.P., J. Baumgartner, and Y. Yi, An Investigation into the Role of Intentions as Mediators of the Attitude-behavior Relationship. Journal of Economic Psychology, 1989. 10(1): p. 35-62. 5. Association, D.-A.P., Diagnostic and statistical manual of mental disorders. Arlington: American Psychiatric Publishing, 2013. 6. Grubbs, J.B., et al., Internet Pornography Use: Perceived Addiction, Psychological Distress, and the Validation of a Brief Measure. Journal of Sex & Marital Therapy, 2015. 41(1): p. 83- 106.
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Chapter 10: Conclusion
10.1 Introduction
This study sought to demonstrate how a new methodology using three strategies could reduce a
number of negative behaviours and attitudes associated with pornography exposure and sexualised
social media behaviours. The study commenced with a review of the literature on the positive and
negative effects, which were arranged in personal, relational and social categories. The research was
largely cross-sectional, limiting the understanding of causation between pornography exposure and
these effects, but the proportion of studies from the literature showing negative effects of
pornography exposure was greater than the proportion showing positive effects.
10.2 Study Summary
What then followed was an examination of the available research on interventions designed to
reduce the negative effects from pornography exposure. This included exploring school-programs,
pornography-related interventions, and general adolescent behaviour change studies. The review of
research on these topics found that there were very few interventional studies designed to reduce
pornography-related negative effects, and none of the school programs had been empirically
assessed. Therefore, it was proposed that a new intervention be designed and conducted to look for
evidence of behaviour and attitude change in adolescents exposed to pornography.
Two studies were conducted to achieve this goal: 1. a baseline survey was designed, implemented
and validated, as the instrument that assessed the efficacy of the intervention; and 2. a six-lesson
program was developed, implemented and assessed.
In preparing the study design, it was decided to conduct a pre-intervention measure, the program
(with lessons conducted weekly), then a post-intervention measure, using the baseline. The pre-
intervention measure was conducted no earlier than a week before the first lesson, the post-
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intervention measure within a week of completing the program, with a maximum of eight weeks
between the two.
The sequence and process for conducting the baseline and program studies were:
10.2.1 Development of Methodology
The process for developing a program commenced in Chapter 2. After concluding that there were
insufficient theoretical frameworks to draw from, an exploratory methodology was proposed,
building on the Chapter 1 literature, using three strategies — 1. didactic education; 2. peer-to-peer
engagement; and 3. parental engagement — to reduce negative effects associated with individual,
relational and societal dimensions of an adolescent’s pornography exposure. Knowledge, attitude
and behaviour constructs were selected as areas the program should address, and predictor
constructs measuring the three strategies were also included, to measure the efficacy of the
individual strategies.
10.2.2 Baseline Study
As a first step, a baseline survey was developed, validated and analysed. The survey consisted of four
categories: socio-demographic control variables; prevalence variables; predictor variables; and
outcome variables. These variables, selected from the constructs in Chapter 2, were measured using
validated instruments from previous studies, with a small number of original items added to
strengthen the analysis. The baseline variables were:
a. Control and prevalence variables: Age of 1st-Time Viewing, Viewing Prevalence, Preferred
Viewing Device, Parental Relationship, Parental Employment, Religion, and Gender.
b. Outcome variables: Attitudes to Pornography, Attitudes to Uncommitted Sexual Exploration,
Women as Sex Objects and six Wellbeing Scales (Parent Relationships, Self-Esteem, Emotional
Stability, Social Conduct, Peer Relationships, and Empathy).
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c. Predictor variables: Peer Attitudes, Peer Relationships, Parental Communication, Parent Rules,
Compulsivity, Distress from Viewing, and Sexualised Social Media Behaviours.
The baseline study was conducted on 746 Year 10 students (aged 14 to 16 years) from NSW independent schools. It was validated using Cronbach alpha, principal components, and exploratory and confirmatory factor analyses. Data analysis confirmed that the students behaved similarly to other published research in this area, giving confidence that a program using the methodology described in Chapter 2 would be applicable. The data demonstrated how pervasive pornography and sexualised social media behaviours were amongst adolescents.
The baseline study found that for most males and many females pornography exposure negatively influenced their attitudes, behaviours, and general wellbeing. One observation was that once regular pornography viewing was accounted for, gender became irrelevant. Females were just as likely as males to experience negative effects, including increased female objectification attitudes, with frequent pornography exposure. These results emphasised the importance of addressing these potentially negative findings with empirically validated evidence, particularly in the context of a society sensitive to objectifying women, sexual harassment, domestic violence, and unlawful sexual conduct via social media.
There were some anomalies in the baseline observations, including some wellbeing factors correlating irregularly with pornography viewing, prompting questions about the relationships between pornography exposure, social media behaviours, narcissism, and self-esteem. Additional items were included in the baseline and also used to inform the program’s content. These new variables measured: Narcissism, Self-Promoting Social Media Behaviours, and Efforts to Reduce
Viewing.
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10.2.3 Program study design and implementation
In Chapter 5, a six-lesson school program was designed for Year 10 students in accordance with the
Australian National Curriculum’s Health and Physical Education (HPE) strand. The six lessons were: 1.
Porn, An Introduction; 2. Porn and the User; 3. Porn and the Society; 4. Porn and Relationships; 5.
Social Media and Identity; and 6. Social Media and Sexualised Behaviour Online. Each lesson included
a set of critical-thinking questions for peer discussions, and a homework activity called the Parental
Diary, where the student would interview their parents with a set of questions about the parent’s
experiences as a teenager.
Iterations of the draft program were reviewed by teachers, parents and equivalent-aged students,
resulting in a final program that was implemented on 347 students from four independent schools in
NSW.
10.3 Data Analysis of the Program
10.3.1 Qualitative Analysis of the Program
Qualitative analysis of the program was performed amongst seven class teachers, who were positive
about the program’s teachability, observing that students were responsive to the teaching content,
and engaged enthusiastically in the peer discussions.
The activities involving parent-student engagement were not carefully monitored. Six of the seven
teachers reported these were not completed, four out of seven teachers said students felt
uncomfortable about the process, and only two teachers reported positive feedback about the
parental activities from students. This meant the protocol for the parent-engagement strategy could
have been better designed and implemented.
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10.3.2 Preliminary program analysis
In Chapters 7–9, quantitative analysis was performed between the pre- and post-intervention
surveys, providing insights into the effectiveness of the program. The preliminary Chapter 7 analysis
compared the interventional data with the baseline survey data, confirming that the students in the
intervention study were representative of the baseline survey students, giving confidence that the
program was an appropriate fit, while enabling a combining of the pre-intervention dataset with the
baseline data for future research.
10.3.3 Narcissism and social media analysis
Chapter 8 analysed the additional survey items added after the Chapter 4 baseline analysis. After
validating the NPI-13 narcissism scale and collating the social-media items into factors, the
relationships between self-promoting social media behaviours, narcissism, pornography exposure,
and self-esteem were investigated.
It was found that 94% of males and 98.6% of females in this study use social media apps. The earlier
they started, and the more they self-promoted, the more likely they are to possess narcissistic traits,
although the daily time spent on social media apps was unrelated. In turn, narcissism can have a
distorting effect on their self-esteem, cloaking the otherwise negative effects that regular
pornography use or sexualised social media behaviours would have on self-esteem. This was
demonstrated by the analysis that showed that although the bivariate correlations between
pornography viewing and sexualised social media behaviours with self-esteem were insignificant,
there was a significant negative correlation once the mediating effect of narcissism was accounted
for.
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The additional risk of developing narcissistic traits from self-promoting social media behaviours, and
the subsequent effects on adolescent attitudes and behaviours, justified the inclusion of elements
addressing social media in the program.
10.3.4 Efficacy of program for knowledge, attitude and behaviour change
The final analysis of the program, in Chapter 9, assessed changes in the students’ knowledge,
attitudes and behaviours from participating in the program.
The study hypothesised that the prevalence of negative behaviours in viewing pornography,
engaging in sexualised social media behaviours, and self-promoting social media behaviours would
decrease, accompanied by an increase in efforts to reduce pornography viewing and unease about
viewing pornography.
Additionally, it was hypothesised that by engaging in peer-discussions and parental activities, a
change in the influence of closer peer groups and parents could be measured.
Lastly, it was hypothesised that the program would increase more responsible attitudes related to
pornography, improve student’s views about women, and promote more responsible attitudes
towards relationships, all while having no adverse effects on wellbeing.
10.4 Outcomes confirming the study hypotheses
A number of positive behaviour and attitude changes were observed:
a. Regarding prevalence behaviours, regular users of pornography increased their efforts to
reduce viewing. Accompanying this was an increase in viewing distress, indicating that students
felt uneasy about and dissatisfied with their current volume of pornography viewing.
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b. Some change was observed in the parents’ influence on students, with an increase in the
correlation between pornography viewing and both parental communication and rules. This
was despite teachers observing a low completion of the parental diary activities. It was also
observed that parent relationships with male students experienced slight (but insignificant)
declines, suggesting some students may have become more sensitive to the interaction with
parents about pornography and technology. c. Change was observed in the influence of the student’s peer culture, seen in the mean-score
reduction of peer attitudes, indicating that the normative peer worldview, as perceived by the
student, had less influence post-intervention. One significant contributor to this change was the
peer discussion activities, which teachers reported as being robust and enthusiastic. d. In terms of change in attitudes, all students experienced a significant increase in negative
attitudes towards pornography, showing that:
• knowledge about the risks and negative effects of pornography increased;
• all students engaged with the program, including students with low pornography
exposure;
• the program could increase the chance of long-term student health, since studies have
shown attitudes are a precursor to behaviour change [1-3]. e. Additionally, the students with regular viewing habits experienced changes to two other high-
risk outcome factors:
• a decreased desire for uncommitted sexual relationships;
• a reduced belief that women are sex objects. f. It was observed in Chapter 1 (Section 1.4.2) that sexual objectification of women is associated
with domestic violence, harassment, and discrimination. Thus, this shift in student attitudes has
a potential benefit for females who associate with males who have undertaken the intervention
described in this study.
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g. Females experienced a reduction in self-promoting social media behaviours. As observed in
Chapters 4, 7, 8 and 9, females are less likely to view pornography, yet more likely to: 1. have a
social media account; 2. be younger when having their account; 3. use the self-promoting apps
Instagram and Snap Chat; 4. have more followers and people following; 5. spend more time per
day on social media, and; 6. receive sexualised content. A reduction in these behaviours
decreases the risk of developing unhealthy levels of narcissism.
h. Lastly, students who participated in the intervention did not increase in any negative
behaviours, nor did their wellbeing reduce.
10.5 Notable Unconfirmed Study Hypotheses
Some of the hypotheses were not proven, contrary to expectation, including:
a. There was a lack of reduction in 14-day viewing prevalence amongst regular pornography users.
This is most likely because of student compulsivity, which was highly correlated with viewing
prevalence.
b. Self-promoting social media behaviours did not decline for males, although they did for
females.
c. The proportion of positive sexualised social media attitudes did not significantly improve.
d. The mean score of the Peer Behaviours factor, which measured the influence of closer peers on
pornography viewing prevalence, did not decrease.
e. The mean score of the Parent Communication factor, which measured the volume of parental
conversation about pornography, did not increase.
f. The mean score of the Parental Rules factor, measuring the level of restrictions and limitations
parents place on their child’s access to the internet, devices, sexualised media and social media,
did not increase
g. There was a trend of increased tension in male-parent relationships after the home
engagement activities, although this was not significant.
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h. Lastly, female students experienced slight reductions in peer relationships after the program.
10.6 Outcomes Not Related to The Study Hypotheses
There were some useful unforeseen outcomes from this study:
a. Chapter 8 explored the relationships between self-promoting social media behaviours,
narcissism, and self-esteem. These ideas were not raised in the literature review (Chapter 1),
and only arose from the analysis of the baseline data in Chapter 4. However, this study has now
described the risks of excessive social media use, including increased narcissism, while
explaining why adolescent engagement with sexualised media appears to have less effect on
self-esteem than in past studies.
b. Compulsivity was shown to be an objective behaviour, akin to other behavioural addictions,
since students with higher compulsivity were unable to change their viewing behaviours despite
an increase in efforts and intentions to reduce viewing. Many students, by age 15, were
exhibiting compulsive behaviours that prevented behaviour change, which may require
additional support, through specialist addiction-themed therapies or interventions, to assist in
reducing compulsive pornography viewing.
c. The degree to which compulsivity inhibits effective change was also unanticipated, since no
other study, with the exception of Fernandez [4], has assessed the relationship between
compulsivity and interventions seeking to reduce viewing frequency. The Structural Equation
Model (SEM) pathway analysis between the Attitudes to Pornography and Viewing Prevalence
factors, when mediated by the Compulsivity factor, showed they had approximately equal and
opposite effects on viewing prevalence, possibly explaining why there was no behaviour change
to 14-day viewing prevalence.
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These unforeseen outcomes of the current study have provided new insights that may benefit future
research, while illuminating the complexities of adolescent behaviour change, which will assist carers
and educators of young people.
10.7 Study Limitations
Study limitations to the various studies within this thesis are discussed in Chapter 3 (Section 3.4.3),
Chapter 8 (Section 8,6), and Chapter 9 (Section 9.5.5)
10.8 Future Iterations of the Intervention Program
There were some areas in which the program could be improved:
a. The schools could have been better instructed on how to monitor and facilitate the at-home
parental activities. Parents would benefit from clearer instructions on how to proceed with
these activities. Repeating the study with better preparation of the student-parent component,
accompanied by qualitative student and parent feedback, would improve the understanding of
the efficacy of parental communication.
b. The peer discussions require closer monitoring, to ensure discussions are respectful, and not
dominated by strong personalities.
In addition, the program may benefit from these considerations:
c. Perform supplementary studies involving additional addictive behavioural therapies on
adolescents with high compulsivity.
d. Isolate the three strategies into separate studies to help qualify whether any one of these three
strategies is more effective than the others.
e. Adapt the program for different age-groups, to explore when students are most likely to
develop problematic attitudes and behaviours, while assessing if intervening earlier may reduce
or prevent the onset of negative effects by Year 10.
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f. Adapt this study’s methodology for other contexts. Since this study is original and exploratory,
its methodology has not been adapted for adolescent studies unrelated to pornography or
social media. Other adolescent interventions may consider incorporating the three strategies,
to assess their efficacy for producing knowledge, attitudinal and behavioural change in other
fields.
g. Lastly, obtain data about the long-term effectiveness of the intervention. This would assist how
to develop future iterations of the program.
10.9 Conclusion
This study developed a new methodology, derived from the literature, where three strategies —
didactic teaching, peer-to-peer engagement, parental engagement — were used to reduce negative
effects from pornography exposure, and sexualised and self-promoting social media behaviours, in
relation to the individual, relational and social spheres. To assess changes in negative effects, two
studies were conducted.
In the first study, a baseline survey was designed, validated, analysed, and used to inform the
development of an intervention program. In the intervention study, a six-lesson program was
developed for an Australian school context, in accordance with the National Curriculum’s HPE
strand, and in consultation with teachers, parents, and teenagers. Teachers reported it was easy to
implement, however improvements to conducting the parental diary and peer-engagement activities
could be made.
The students in the intervention study behaved similarly to those in both the baseline study and
previous research, making them appropriate subjects for the program. Additional exploration of
social media behaviours showed a relationship between self-promotion, narcissism, self-esteem and
student engagement with pornography and sexualised social media behaviours.
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The program was effective in reducing a number of negative effects from pornography exposure, sexualised social media behaviours, and self-promoting social media behaviours, using the three strategies of didactic education, peer-to-peer engagement, and parental activities. Compulsive behaviours impeded efforts to reduce pornography viewing in some students, while earlier and more frequent self-promoting social media use may produce excess narcissistic traits, effecting self- esteem, and altering their interaction with pornography and sexualised social media behaviours.
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10.10 Chapter References
1. Wood, R.T.A. and M.D. Griffiths, Adolescent Lottery and Scratchcard Players: Do Their Attitudes Influence Their Gambling Behaviour? Journal of Adolescence, 2004. 27(4): p. 467- 475. 2. Neighbors, Foster, and C.D.N.W. Fossos, Peer Influences on Addiction. 2013. p. 323-331. 3. Bagozzi, R.P., J. Baumgartner, and Y. Yi, An Investigation into the Role of Intentions as Mediators of the Attitude-behavior Relationship. Journal of Economic Psychology, 1989. 10(1): p. 35-62. 4. Fernandez, D.P., E.Y.J. Tee, and E.F. Fernandez, Do Cyber Pornography Use Inventory-9 Scores Reflect Actual Compulsivity in Internet Pornography Use? Exploring the Role of Abstinence Effort. Sexual Addiction & Compulsivity, 2017. 24(3): p. 156-179.
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Appendix A: Review of Some Current Pornography Curriculum
What You Should Know about Porn
This is a single unit for Years 8 (and above on pornography, accompanied by a 5-minute video, by the Australian Research Centre in Sex, Health and Society. It is recommended that it is used in conjunction with their broader curriculum: The Practical Guide to Love, Sex and Relationships for Years 7 to 10, although it can be stand alone.
Central to this content is the proposition that pornography does not portray real sexuality, but rather makes the ‘penis’ the centre of the show, and relegates women to being objects of pleasure, even if they are uncomfortable. It also addresses the lack of intimacy and relationship, as well as the lack of consent and gender imbalance in pornography. There is also emphasis on not feeling guilty for watching porn, rather that this is a normal part of curiosity, and that young people are sexual by nature.
There is no scholarship or external references within the teaching content, only assertions. There is no justification for why the themes of ‘real-life’ sex, gender, and consent are chosen. Nor is it clear how the wider Practical Guide curriculum addresses the many problematic effects of pornography as described in the wider literature. The authors concede that it is introductory, and does not address broader issues like the ethics of pornography production, cybersafety, or addictive behaviours [29].
Catching On Later
This curriculum broadly addresses sexual health and respectful relationships. The primary reference to pornography is in chapter 12, ‘Did I Really Press Send?’ Aimed at year 8, it deals with the Victorian laws on sexting and child pornography, in particular the problem of filming, sending and receiving sexual images of people under 18 (pp. 312–20). There is no information about transmitting naked pictures of adults without their consent, nor about general pornography viewing, presumably because the only concern in this curriculum is illegal behaviour, not exposure to legal pornography.
Sexting Curriculum – Office of the eSafety Commissioner
This short lesson plan is intended to educate on sexting, with clear explanations of the legal consequences of engaging with underaged materials and transmitting content without consent. Although it addresses the problem of peer pressure and ethical conduct, including respectful relationships, this curriculum does not otherwise address pornography [26].
We Need To Talk About Pornography Curriculum
This British 2016 publication is designed for Sex and Relationship Education (SRE), and aimed at Key Stage 3 (age 11–14) and 4 (age 14–16) pupils. It conforms with various guidelines and policies from the National Curriculum in the UK, and broadly seeks to develop the three skill areas for effective learning: knowledge, attitudes and skills [30].
There are 5 lesson plans, which can be either taught in sequence or standalone. The content addresses: definitions of pornography; a basic exploration of the UK laws on pornography
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production; accessibility; child-pornography; sexting; naked selfies; revenge porn and industry versus homemade porn – in the context of what is legal conduct. It addresses themes around the sexualisation of culture and how that impacts the student’s attitudes and behaviours; gender stereotyping; body image; real relationships; and sexting, revenge porn and online sexual bullying.
There is little scholarship supporting the content, and no evidence that it delivers effective education.
In The Picture
This curriculum is a comprehensive guide for schools to implement a holistic community response to ‘sexually explicit images’. The curriculum sits under the Health and Physical Education, and Civics and Citizenship, sections of the Australian National Curriculum, and justifies itself as fulfilling the 7 General Capabilities required by the national curriculum. It defines pornography as ‘sexually explicit images (pictures or videos) intended to arouse’. The core learning component is 10 independent activities, addressing 8 learning outcomes: Pornography; Sexting; Body image; Sexual health; Gender and identity; Power and aggression; Consent; and Diversity [28].
There is minimal scholarship within the curriculum, although it seems to capture much of the evidence about the ways pornography is: a poor sex educator; promotes unrealistic portrayals of sexual behaviour; disrespects women; increases behaviour that risks STIs; leads to increased body image insecurities; increases sexual aggression; and creates potential for lawbreaking behaviours through sexting underaged materials.
What this curriculum lacks is reference to the impact of pornography production on performers, the long-term effects on relationships, neurological effects on behaviours and development, long-term sexual development issues, and long-term mental health.
Building Respectful Relationships
This 8-session resource, designed for a Victorian school high-school context, interacts with various negative effects of pornography, particular as they pertain to gender, respectful behaviour, violence against women, power inequalities, and sexual harassment [32]. The author declares that its content “drew heavily on gender equity and human rights discourses. Much of the programme was designed to: raise awareness of the extent of VAW that occurs through ‘objectification’ and ‘dehumanisation’ of women in pornography and popular and mainstream media” [146]. Although there is substantial scholarship undergirding the content, it only addresses some of the effects of pornography, using dated scholarship. As with In The Picture, it does not provide a holistic description of the problem, nor provide justification for its methodologies.
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Appendix B: Baseline Survey Questionnaire
Item # Scale Question Option** 1 Control Variables I am (Age) 13–17
2 I am Male or Female or Other M, F, O
3 My parents are (Parent relationship)* Married, Divorced, Live together (de facto), Widowed, Other
4 My parents do paid work* One, Both, None
5 Religion is important to my family* Never, Rarely, Sometimes, Mostly, Always
6 Religion is important to me* Never, Rarely, Sometimes, Mostly, Always
7 My age when I first saw Pornography was about* Never; Under 5; 6–16 ; 17 or above
8 How often in the past month did you engage with Not at all; Once or a few pornography* times; About once a week; A couple times a week; Every day or almost every day
9 If you have viewed pornography, what device did My phone; My tablet/iPad; you mostly view pornography on* My laptop; My desktop; My tv; Other
10 I normally watch pornography intentionally * Always intentionally (4) - Never intentionally (0) 11 Exposure In the last 6 months, I encountered pictures or Never; Less than once a Prevalence[6] movies with clearly exposed genitals month; One to three times a month; Once a week; Several times a week; Every day; Several times a day
12 In the last 6 months, I encountered pictures or Never; Less than once a movies in which people are having sex month; One to three times a month; Once a week; Several times a week; Every day; Several times a day 13 Attitudes to Pornography teaches about sexual techniques Entirely disagree (6) - Pornography[32] Entirely agree (0)
14 Pornography degrades men Entirely disagree (0) - Entirely agree (6)
15 Pornography is stimulating and exciting Entirely disagree (6) - Entirely agree (0)
16 Pornography breaks down family structure Entirely disagree (0) - Entirely agree (6)
17 Pornography gives women false expectations Entirely disagree (0) - about the opposite sex Entirely agree (6)
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18 Pornography degrades women Entirely disagree (0) - Entirely agree (6)
19 Pornography gives men false expectations about Entirely disagree (0) - the opposite sex Entirely agree (6)
20 Pornography leads to sexual addiction Entirely disagree (0) - Entirely agree (6)
21 Pornography is educational Entirely disagree (6) - Entirely agree (0)
22 Pornography increases violence towards women Entirely disagree (0) - Entirely agree (6)
23 Pornography releases sexual tension Entirely disagree (6) - Entirely agree (0)
24 Pornography is harmful to romantic relationships Entirely disagree (0) - Entirely agree (6)
25 Pornography is a harmless activity Entirely disagree (6) - Entirely agree (0) 26 CPUI-9 I believe I am addicted to Internet pornography All the time (6) - Never (0) Compulsivity[9]
27 I feel unable to stop my use of online pornography All the time (6) - Never (0)
28 Even when I do not want to view pornography All the time (6) - Never (0) online, I feel drawn to it 29 CPUI-9 Efforts[9] I feel ashamed after viewing pornography online All the time (6) - Never (0)
30 I feel depressed after viewing pornography online All the time (6) - Never (0)
31 I feel sick after viewing pornography online All the time (6) - Never (0) 32 CPUI-9 Distress[9] At times, I try to arrange my schedule so that I will All the time (6) - Never (0) be able to be alone in order to view pornography
33 I have refused to go out with friends or attend All the time (6) - Never (0) certain social functions to have the opportunity to view pornography
34 I have put off important priorities to view All the time (6) - Never (0) pornography 35 Parental Active My parents tell me they don't like how so many Often (3) - Never (0) Mediation[17] people view pornography
36 My parents tell me pornography has a negative Often (3) - Never (0) effect on society
37 My parents tell me I shouldn't look at pornography Often (3) - Never (0)
38 My parents tell me that pornography sends a bad Often (3) - Never (0) message about relationships 39 Restrictive My parents restrict my access to pornography Yes (1); Sometimes (1); Mediation[17] Never (0)
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40 My parents have rules about viewing pornography No (0); Yes, they set limits on how much I can view (1); Yes, I am not allowed to view pornography at all (1)
41 My parents have rules about when and where I can Yes (2) - None (0) use my devices (laptop, phone, iPad)*
42 My parents have access to my social media All accounts (2) - None (0) accounts (e.g. email, Instagram, Facebook, Snapchat)* 43 Peer Most people my age look at pornography Often (3) - Never (0) Descriptive[17]
44 Most of my closer friends look at pornography Often (3) - Never (0) 45 Peer Injunctive[65] It's ok for people to look at pornography Often (3) - Never (0)
46 It's ok for my friend's to look at pornography Often (3) - Never (0) 47 Strengths and I get very angry and often lose my temper Not true (0) - Certainly True Difficulties (0) Conduct Subscale[41, 48]
48 I usually do as I am told Not true (2) - Certainly True (0)
49 I fight a lot. I can make other people do what I Not true (0) - Certainly True want (0)
50 I am often accused of lying or cheating Not true (0) - Certainly True (0)
51 I take things that are not mine from home, school Not true (0) - Certainly True or elsewhere (0) 52 Strengths and I am usually on my own. I generally play alone or Not true (0) - Certainly True Difficulties Peer keep to myself (0) Subscale[41, 48]
53 I have one good friend or more Not true (2) - Certainly True (0)
54 Other people my age generally like me Not true (2) - Certainly True (0)
55 Other children or young people pick on me or bully Not true (0) - Certainly True me (0)
56 I get on better with adults than with people my Not true (0) - Certainly True own age (0) 57 Strengths and I try to be nice to other people. I care about their Not true (2) - Certainly True Difficulties feelings (0) Prosocial Subscale[41, 48]
58 I usually share with others (food, games, pens, etc.) Not true (2) - Certainly True (0)
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59 I am helpful if someone is hurt, upset or feeling ill Not true (2) - Certainly True (0)
60 I am kind to younger children Not true (2) - Certainly True (0)
61 I often volunteer to help others (parents, teachers, Not true (2) - Certainly True children) (0) 62 Self-Description I worry more than I need to True (5) - False (0) Questionnaire II Emotional Stability Subscale[40]
63 I am a nervous person True (5) - False (0)
64 I often feel confused and mixed up True (5) - False (0)
65 I get upset easily True (5) - False (0)
66 I worry about a lot of things True (5) - False (0) 67 Self-Description Overall, I have a lot to be proud of True (5) - False (0) Questionnaire II Self-Esteem Subscale[40]
68 Most things I do, I do well True (5) - False (0)
69 Overall, most things I do turn out well True (5) - False (0)
70 I do things as well as most people True (5) - False (0)
71 If I really try, I can do almost anything I want to do True (5) - False (0)
72 Overall, I am a failure True (0) - False (5) 73 Self-Description I get along well with my parents True (5) - False (0) Questionnaire II Parent Subscale[40]
74 My parents treat me fairly True (5) - False (0)
75 My parents understand me True (5) - False (0)
76 I do not like my parents very much True (0) - False (5) 77 Women as Sex Unconsciously, girls always want to be persuaded Strongly agree (4) - Strongly Objects[1] to have sex disagree (0)
78 Sexually active girls are more attractive partners Strongly agree (4) - Strongly disagree (0)
79 An attractive woman should expect sexual Strongly agree (4) - Strongly advances disagree (0)
80 It bothers me when a man is interested in a woman Strongly agree (0) - Strongly only if she is pretty disagree (4)
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81 There is nothing wrong with men being primarily Strongly agree (4) - Strongly interested in a woman's body disagree (0) 82 Attitudes to It is important to gather experience with multiple Strongly agree (4) - Strongly Uncommitted sexual partners disagree (0) Sexual Exploration[6]
83 It is important to try out as many sexual things as Strongly agree (4) - Strongly possible before you start with a steady relationship disagree (0)
84 When you are young, you have to enjoy your Strongly agree (4) - Strongly sexual freedom. You can start with a steady disagree (0) relationship later
85 It is important to have had many sexual partners Strongly agree (4) - Strongly before you start with a steady relationship disagree (0) 86 Sexualised Social Have you ever sent a sexually explicit written text Yes, No, Don't know Media message Behaviour[26]
87 Have you ever received a sexually explicit written Yes, No, Don't know text message
88 Have you ever sent a sexually explicit nude or Yes, No, Don't know nearly nude photo or video of yourself
89 Have you ever sent a sexually explicit nude or Yes, No, Don't know nearly nude photo or video of someone else
90 Have you ever received a sexually explicit nude or Yes, No, Don't know nearly nude photo or video of someone else
91 Have you ever used a social media site for sexual Yes, No, Don't know reasons
92 Is sending and receiving naked pictures a normal Yes, No, Don't know thing your friends do with each other*
93 Is sending naked pictures acceptable amongst Yes, No, Don't know close friends or people who are in a relationship* Note: * Original Question; ** Likert scale range can vary, with the minimum and maximum values indicated in parenthesis.
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Appendix C: Letter to the Principal
Dear N
I am writing to invite the Year 10 students from your school to participate in pilot program sexual health, the internet, social media, sexualised culture and pornography. This pilot is part of a PhD study I am conducting through the University of Sydney’s Faculty of Medicine, Discipline of Child and Adolescent Health on effective education interventions designed to reduce the negative effects of pornography on adolescents. I am doing this research under the supervision of Professor Kim Oates and Professor Rachel Skinner. If you wish to participate, please communicate that to me by email.
The 6-lesson pilot is designed to be run within the PDHPE curriculum and aligns with the National Curriculum’s HPE strand. At the commencement and conclusion of the program, students are to complete a survey, which will measure how effective the program is for improving wellbeing markers, enhancing positive peer and parental influence, and reducing various negative effects from exposure to sexualised media and social media behaviours. The survey was previously conducted in 2018, and a report of that study is attached.
The pilot should be taught in regular PDHPE classes by their normal teacher, and we recommend that the Head of PDHPE takes responsibility for administering the process. I have attached via email the Teachers Pack, which consists of:
• The Lesson Overview – which describes the scope, sequence, ethos and various elements in the pilot • The Lesson Background – which provides the theoretical and empirical content underlying each lesson • The Lesson Teaching Content – which includes the teaching content for each lesson • The Parental Diary – which is the homework component of the pilot
As you consider this invitation to participate, your PDHPE and pastoral staff should familiarise themselves with the content, to assess its appropriateness for your students. Teachers should willingly participate in teaching this program and should not be required if they are uncomfortable with doing so. The content has already been reviewed by PDHPE staff from three schools, in addition to some parent and student focus groups. Please see the attached references.
The only data gathered by us in this study is through the survey. The survey is anonymous and confidential. Students cannot be identified by any question, and we have processes in place to ensure that no other identifying data, like I.P. or Mac addresses, will be kept. The school’s identity will also be kept strictly confidential, and neither the published results nor any stored data will have the school’s name associated with the survey results. The survey consists of 115 questions and should take about 25mins.
We will require consent by the student’s parents and have prepared information statements for the parents. Consent will be opt-out, meaning the parents need to notify the school if they do not wish to participate. This opt-out process was also adopted for the 2018 survey study, and schools reported it worked well.
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Student’s will also be given instructions via a separate information statement, which we have also prepared, explaining that they can also withdraw at any time, up until they complete the survey. In the event that an individual student does not participate, it would be important for appropriate alternative activities to be provided by the school, and for us to be informed of this.
One of the requirements for participating in this study is for schools to provide the students access to counselling and pastoral support. Since the content addresses sexual themes, there is a risk that some students will be distressed by the concepts raised in it. Students should be clearly aware of the school’s support services as they participate.
We would like to conduct the survey and the 6-lesson program in either Term 3 or 4, 2019.
If you would like your school to be part of this study, then please respond to me as soon as possible, so that we can make preparations and facilitate a smooth process.
Marshall Ballantine-Jones 0423 352 312, [email protected]
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Appendix D: Parental Participation Information Statement
Pilot Education Program on Sexual Health and Internet Pornography
Parental information statement
(1) What is this study about?
Your child is invited to take part in a pilot education program about sexual health, the internet, social media, sexualised culture and pornography. Your school has agreed to participate in this program, which has been designed for Year 10 and above. The program contains six 50min teaching units, including a baseline survey taken at the commencement and a few weeks after the conclusion of the course. The survey will be delivered online, managed by independent researchers, and is completely anonymous, such that your students cannot be identified by the school or wider researchers, and the identity of school will also remain anonymous in any publications related to this study.
Your child has been invited to participate in this study because they are both of the generation that is highly digital media and sexualised culture, whilst of a maturity to understand how those influences may affect themselves and their peers. A recent separate study for validating the baseline survey which is part of this pilot comprehensively confirmed how sexualised media is affecting Year 10 students in schools like your child’s – this report can be found here: https://www.edcomm.org.au/publications/school-pornography-survey-2018/. Knowing what is involved will help you decide if you want to let your child take part in the research. Please read this sheet carefully and ask questions about anything that you don’t understand or want to know more about.
Participation in this research study is voluntary.
By giving your consent you are telling us that you: ✓ Understand what you have read. ✓ Agree for your child to take part in the research study as outlined below. ✓ Agree to the use of your child’s personal information as described.
The study is opt-out, meaning you do not have to return a signed consent form, however if you do not wish your child to participate, please notify the Head of PDHPE
(2) Who is running the study?
The study is being carried out by Marshall Ballantine-Jones as the basis for the degree of Doctor of Philosophy, at The University of Sydney. This will take place under the supervision of Emeritus Professor Kim Oates.
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(3) What will the study involve?
There are three main aspects to this study.
Firstly, students will complete a survey during the first lesson of this pilot program and also a few weeks after the final lesson, via an online website, using either their own school-approved device, or school provided device. The survey consists of about 115 questions, and will explore attitudes and behaviours related to the internet, social media, sexualised culture and pornography. The purpose of the survey is to test the effectiveness of the pilot education program, in particular the core influences on the students’ life, including school education, family, and friends. As previously mentioned, the report of a past study on this survey can be found here: https://www.edcomm.org.au/publications/school-pornography-survey-2018/).
Secondly, students will participate in a 6-lesson program, designed to align with the Health and Physical Education (HPE) strand of the National Curriculum. Each lesson will consist of a mixture of creative content learning, popular cultural interaction, peer- discussion groups, and personal reflection. The lessons are designed to align with the National Curriculum’s HPE Strand for Stage 4. The lessons will be taught by their normal PDHPE teacher. The teaching content has been evaluated and approved by your school, however if you have any specific queries about the topics and contents covered, you are welcome to consult with your student’s teacher for more information.
Thirdly, students have a novel home activity called the Parental Diary. The purpose of this activity is to have students engage with parents on a range of topics that pertain to each teaching unit. The purpose of these questions is to invite students into their parent’s world when they were an adolescent, whilst allowing parents to reflect upon the societal changes that their child faces. Examples of these questions include: When you see how sexuality is promoted in the media, movies and tv shows, and popular culture, do you think much has changed since your time; Do you think a more sexualised culture makes people feel insecure or more confident; and Do you think young people today are more sexualised than your time?
So over the course of the program, your child will ask you a series of questions which will help them understand your perspective about being a teenager in a complicated and sexualised world. Each week will take about 5-10mins. You are not obligated to answer any questions, however you may use the opportunity to communicate more generally about the content they are learning in this course.
In the event that your child does not participate, appropriate alternative supervision will be provided by PDHPE staff.
(4) How much time will the study take?
The study will take 6 normal class lessons – which depending on how your school schedules the lesson timetable, could be 4-8 weeks. It is recommended that it be conducted within a normal PDHPE class period.
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(5) Who can take part in the study?
The study is being implemented in a selection of independent schools in NSW, including your school. It is being completed by Year 10 students only.
(6) Does my child have to be in the study? Can they withdraw from the study once they’ve started?
Being in this study is completely voluntary and your child does not have to take part. Your decision whether to let them participate will not affect your/their relationship with the school, their peers, the researchers or anyone else at the University of Sydney, now or in the future.
If you decide to let your child take part in the study and then change your mind later (or they no longer wish to take part), they are free to withdraw from the study at any time. If you wish to withdraw your child from the study, please indicate this by contacting the head of PDHPE or the school counsellor any time before the commencement of the survey.
Your child’s questionnaire responses can be withdrawn any time before they have submitted the questionnaire. Once they have submitted it, their responses cannot be withdrawn because they are anonymous and therefore we will not be able to tell which one is theirs.
If your child withdraws from the pilot program, we will not collect any further information from them. However, any information that we have already collected prior to their withdrawal, including any baseline survey data, will be kept in our study records and may be included in publications because we have no way of knowing what individual students submitted (in order to isolate and remove their contribution).
(7) Are there any risks or costs associated with being in the study?
Great lengths have been taken to ensure that the teaching content is age-appropriate, is consistent with the National Curriculum’s HPE strand, and consistent with similar Australian teaching programs, including In The Picture; Porn - what you should know; Sexting: social and legal consequences; Catching On Later, and Building Respectful Relationships. Furthermore, care has been taken in the delivery of the content such that students with a low awareness of, or exposure to sexualised media and associated behaviours will not be subjected to pervasive questions or content that are sensitive or explicit. We believe that your child will not be made uncomfortable by this process.
Aside from giving up their normal school time allotted for PDHPE, we do not expect that there will be any risks or costs associated with taking part in this study for your students.
However, if distress and discomfort are caused by the process or content of the survey, the school counsellor is on hand to address any concerns a student may have. Also, if your child wants to access other support, they can visit Beyond Blue’s youth service at https://www.youthbeyondblue.com/ including their 24 hour hotline 1300 22 4636; or alternatively Headspace’s youth services at https://headspace.org.au/young-people/.
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(8) Are there any benefits associated with being in the study?
This pilot education program has two potential benefits. Firstly, your child will experience a comprehensive and powerful education experience which will impart the most up-to-date and empirically-based content, whilst challenging the attitudes and behaviours of them and their peers. Secondly, it will be carefully assessed for effectiveness. There are only a handful of school-based education programs that address pornography and sexualised media, but none of these programs address the broad suite of negative effects, nor have they been empirically tested for effectiveness.
In the long run, your student’s participation in the study may enable other students to benefit from the pilot program. The information gathered will provide a critical picture of attitudes and behaviours of the students involved, as well as knowledge of whether this unique combination of teaching elements can contribute to meaningful change in students’ lives.
(9) What will happen to information that is collected during the study?
By providing your consent, you are agreeing to us collecting personal information about your child for the purposes of this research study. Their personal information will only be used for the purposes outlined in this Participant Information Statement, unless you consent otherwise.
Any information your child provides, which is limited to the anonymous survey, will be stored securely and kept strictly confidential, except as required by law. In addition to the survey being anonymous, researchers will not keep records of any device identifiers like I.P numbers of MAC addresses. Study findings may be published, but neither the school nor your child will be individually identifiable in these publications.
We will keep the information we collect for this study, and we may use it in future projects. By providing your consent you are allowing us to use the survey data for future projects. We don’t know at this stage what these other projects will involve. We will seek ethical approval before using the information in these future projects.
(10) Can I or my child tell other people about the study?
Yes, you are welcome to tell other people about the study.
(11) What if we would like further information about the study?
When you have read this information, Marshall Ballantine-Jones will be available to discuss it with you further and answer any questions you may have. If you or your child would like to know more at any stage during the study, please feel free to contact Marshall via email [email protected].
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(12) Will we be told the results of the study?
You and your child have a right to receive feedback about the overall results of this study. You can tell us that you wish to receive feedback by email. This feedback will be in the form of either an executive summary of a respective thesis chapter, or of a published peer-review journal. You will receive this feedback after the study is finished. It may be some months before this occurs, but the report will be posted on the Anglican Education Commission’s website http://www.edcomm.org.au/. The school will notify you when this happens.
(13) What if we have a complaint or any concerns about the study?
Research involving humans in Australia is reviewed by an independent group of people called a Human Research Ethics Committee (HREC). The ethical aspects of this study have been approved by the HREC of the University of Sydney [INSERT protocol number once approval is obtained]. As part of this process, we have agreed to carry out the study according to the National Statement on Ethical Conduct in Human Research (2007). This statement has been developed to protect people who agree to take part in research studies.
If you (or your child) are concerned about the way this study is being conducted or wish to make a complaint to someone independent from the study, please contact the university using the details outlined below. Please quote the study title and protocol number.
The Manager, Ethics Administration, University of Sydney: • Telephone: +61 2 8627 8176 • Email: [email protected] • Fax: +61 2 8627 8177 (Facsimile)
This information sheet is for you to keep.
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Appendix E: Student Participation Information Statement
Study Information Sheet
Participating in a Trial Education Program on Sexual Health and Internet Pornography
You are invited to participate in new PDHPE education program being conducted by Dr Kim Oates and Marshall Ballantine-Jones.
The trial program seeks to understand and challenge your attitudes and beliefs about the internet, social media, sexualised culture and pornography.
You are being asked to be in this study because you and your peers are digital natives, and are highly exposed to the internet and sexualised culture. The study wants to learn how the internet affects you, how you navigate through it, and how you can make responsible decisions for your future.
You can decide if you want to take part in the study or not, but your parents will also be asked if they want you to be involved.
This sheet describes what the study involves if you decide to take part in the study. Please read it carefully so that you can make up your mind about whether you want to take part.
If you decide you want to be in the study and then you change your mind later, that’s ok. All you need to do is tell your PDHPE teacher that you don’t want to be in the study anymore.
If you have any questions, you can ask us or your family or someone else who looks after you. Also, if you want to, you can email Marshall on [email protected].
What will happen if I say that I want to be in the study?
If you decide that you want to be in this study, you will be asked to do these things:
• There are six lessons that will be run in your scheduled PDHPE class. In these classes your teacher will share teaching content about topics related to sexual health, the internet, social media, sexualised culture and pornography. You will watch some interesting opinions from experts and celebrities, and will be invited to have discussions about the teaching content with your class peers. Each week you will be given a short homework assignment that involves interviewing your parents about some of the content, and how they think the world has changed since their time as a teenager.
• You will also be asked to fill out a survey before and after the six lessons, which your teacher has arranged for you to do. Your parents have already been asked to contact the school if they do not want you to be involved. Follow any instructions about accessing the survey, which may involve using your own school-approved computer.
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• The survey will be done via a webpage. When you are asked questions, you can choose which ones you want to answer. If you don’t want to answer something, that’s ok. You can stop doing the survey at any time if you don’t want to do it anymore. But once you finish the survey, and submit the answers, you will no longer be able to withdraw because we will not know which answers yours were.
• Be aware that if your parents have indicated they do not want you to do the survey and lessons, but you still want to, unfortunately you cannot participate. Your PDHPE teacher will instruct you on what to do during the survey time.
Will anyone else know what I say in the survey?
The survey is completely anonymous. You won’t be asked for your name or school. No one will not be able to tell what your answers are. If you talk about someone hurting you or about you hurting yourself or someone else, then it might be necessary to tell your school so they can try keep the school community safe, however even then, no one can tell which student said this.
All of the anonymous information that you give from the survey will be stored in a safe place and will be looked after very carefully. A report about the whole study will be written at the end and be made available to all who were involved, however it will not reveal any of your details or your school’s identity. No one will know that you were in this study.
How long will the study take?
Each of the lessons will last 50mins. The survey will last about 30minutes and has about 115 questions.
Are there any benefits from being in the study?
We believe that your participation in the six lessons may be of great benefit to students who experience them, as the content is engaging, creative and challenging. The information gathered from the surveys will show just how effective the lessons are, and will also provide a critical picture of attitudes and behaviours of the students involved. This may have ongoing benefits for other students your age who later do the lessons.
Are there any risks or costs from being in the study?
This study will take up some of your class time, along with some occasional homework time, but there is no cost to do it. Great lengths have been taken to ensure that the teaching content is age- appropriate, and you should not be made uncomfortable by the content. You may be asked some personal questions about the internet, social media, your friends, sexuality and pornography. If you get worried or upset about anything from the study, your school counsellor is ready and available for you to see. Also, if you want to access other support, you can visit Beyond Blue’s youth service at https://www.youthbeyondblue.com/ including their 24 hour hotline 1300 22 4636; or alternatively Headspace’s youth services at https://headspace.org.au/young-people/.
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Will you tell me what you learnt in the study at the end?
We will make the results of the study available to you, your school and your parents. It may be some months before this occurs, but the report will be posted on the Anglican Education Commission’s website http://www.edcomm.org.au/. Your school and your parents wil be notified when this happens.
What if I am not happy with the study or the people doing the study?
If you are concerned about the way this study is being conducted or you wish to make a complaint to someone independent from the study, please contact the university using the details outlined below. Please quote the study title and protocol number.
If you are concerned about the way this study is being conducted, or you wish to make a complaint to someone independent from the study, please contact the university via the following details:
The Manager of Ethics Administration: • By phone on +61 2 8627 8176 or ▪ By email to [email protected]
This sheet is for you to keep.
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Appendix F: Teacher Participation Information Statement
Pilot Education Program on Sexual Health and Internet Pornography
Information statement: person responsible
(14) What is this study about?
Year 10 students under your care are invited to take part in a pilot education program about sexual health, the internet, social media, sexualised culture and pornography. Your school has agreed to participate in this program, which has been designed for Year 10 and above. The program contains six 50min teaching units, including a baseline survey taken at the commencement and a few weeks after the conclusion of the course. The survey will be delivered online, managed by independent researchers, and is completely anonymous, such that your students cannot be identified by the school or wider researchers, and the identity of school will also remain anonymous in any publications related to this study. You will teach the program using the Teaching Unit Pack accompanying this letter. The Teaching Unit Pack content includes topical background information, aims and outcomes, lesson outlines, student worksheets, peer-group discussion activities, and homework activities.
Your students have been invited to participate in this study because they are both of a critical age for high exposure to digital media and sexualised culture, whilst of a maturity to understand how those influences may affect themselves and their peers. A recent separate study for validating the baseline survey which is included in this pilot comprehensively confirmed how sexualised media is affecting Year 10 students in schools like yours – this report can be found here: https://www.edcomm.org.au/publications/school-pornography-survey-2018/. This Participant Information Statement tells you about the upcoming pilot study. Knowing what is involved will help you decide if you want to let your students take part in the research, or how to manage a student who wishes to withdrawal from it. Please read this sheet carefully and ask questions about anything that you don’t understand or want to know more about.
Participation in this research study is voluntary.
By giving your consent you are telling us that you:
✓ Understand what you have read. ✓ Agree for the person under your guardianship/care to take part in the study as outlined below. ✓ Agree to the use of their personal information as described.
The study is opt-out, meaning the student’s parents or guardians do not have to return a signed consent form, however if the student does not wish to participate at any time, please discretely allow them to withdrawal, and manage their absence in consultation with the Head of PDHPE
You will be given a copy of this Information Statement to keep.
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(15) Who is running the study?
The study is being carried out by Marshall Ballantine-Jones as the basis for the degree of Doctor of Philosophy, at The University of Sydney. This will take place under the supervision of Emeritus Professor Kim Oates.
(16) What will the study involve?
There are four main aspects to this study.
Firstly, students will complete a survey during the first lesson of this pilot program and also a few weeks after the final lesson, via an online website, using either their own school-approved device, or school provided device. The survey consists of about 115 questions, and will explore attitudes and behaviours related to the internet, social media, sexualised culture and pornography. The purpose of the survey is to test the effectiveness of the pilot education program, in particular the core influences on your student’s life, including school education, family, and friends. As previously mentioned, the report of a past study on this survey can be found this report can be found here: https://www.edcomm.org.au/publications/school-pornography-survey-2018/.
Secondly, students will participate in a 6-lesson program, designed to align with the Health and Physical Education (HPE) strand of the National Curriculum. Each lesson will consist of a mixture of creative content learning, popular cultural interaction, peer- discussion groups, and personal reflection. The lessons are designed to align with the National Curriculum’s HPE Strand for Stage 4.
As the teacher of this content, you are to familiarise yourself with all the content in the Teachers Pack, which consists of:
• The Lesson Overview – which describes the scope, sequence, ethos and various elements in the pilot • The Lesson Background – which provides the theoretical and empirical content underlying each lesson • The Lesson Teaching Content – which includes the teaching content for each lesson • The Parental Diary – which is the homework component of the pilot
If you have questions about the content, or require clarity about the teaching process, you are welcome to contact me to discuss at length.
Thirdly, students have a novel home activity schedule, called the Parental Diary. The purpose of this activity is to have students engage with parents on a range of topics that pertain to each teaching unit. Essential to this pilot is an effort to increase communication and engagement between the student and their parents, because research suggests that parental engagement is the single most influential factor for minimising the negative effects of sexualised media exposure on the student. The Parental Diary is also attached.
In the event that a student does not participate, appropriate alternative supervision must be provided by the school, including alternative teaching content for them to do.
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Fourthly, in addition to teaching the course, you are requested to fill out the attached questionnaire called ‘Teachers Questionnaire for Pilot Program.docx’. This will help us better evaluate the effectiveness of the study, as well as inform us how the program can be strengthened for future use. Your consent is required before collecting your response and using this data. Your identity, both name and school, will remain confidential and not disclosed in any future publication related to this study. Your consent is presumed if you return the attached questionnaire via email or post.
(17) How much time will the study take?
The study will take 6 normal class lessons – which depending on how your school schedules the lesson timetable, could be 4-8 weeks. It is recommended that it be conducted within a normal PDHPE class period.
(18) Who can take part in the study?
The study is being implemented in a selection of independent schools in NSW, including your school. It is being completed by Year 10 students only. The identity of each participating school is kept anonymous in any and all publications about this study.
(19) Does the person have to be in the study? Can they withdraw from the study once they’ve started?
Being in this study is completely voluntary and a student does not have to take part. Their non-participation will not affect their relationship with the school, their peers, the researchers or anyone else at the University of Sydney, now or in the future.
If a student’s parents do not request a withdrawal from the study, but the student indicates they no longer wish to take part, they are free to withdraw from the study at any time.
If the student withdraws from the pilot program, we will not collect any further information from them. However, any information that we have already collected prior to their withdrawal, including the baseline survey data, will be kept in our study records and may be included in publications because we have no way of knowing what individual students submitted (in order to isolate and remove their contribution).
(20) Are there any risks or costs associated with being in the study?
Great lengths have been taken to ensure that the teaching content is age-appropriate, is consistent with the National Curriculum’s HPE strand, and consistent with similar Australian teaching programs, including In The Picture; Porn - what you should know; Sexting: social and legal consequences; Catching On Later, and Building Respectful Relationships. Furthermore, care has been taken in the delivery of the content such that students with a low awareness of, or exposure to sexualised media and associated behaviours will not be subjected to pervasive questions or content that are sensitive or explicit. We believe that your students will not be made uncomfortable by this pilot program.
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Aside from giving up their normal school time allotted for PDHPE, we do not expect that there will be any risks or costs associated with taking part in this study for your students.
However, if distress and discomfort are caused by the process or content of the survey, it is essential that the school counsellor or equivalent is on hand to address any concerns a student may have. Also, if your student wants to access other support, they can visit Beyond Blue’s youth service at https://www.youthbeyondblue.com/ including their 24 hour hotline 1300 22 4636; or alternatively Headspace’s youth services at https://headspace.org.au/young-people/.
(21) Are there any benefits associated with being in the study?
This pilot education program has two potential benefits. Firstly, your students will experience a comprehensive and powerful education experience which will impart the most up-to-date and scientifically-based content, whilst challenging the attitudes and behaviours of them and their peers. Secondly, it will be carefully assessed for effectiveness. There are only a handful of school-based education programs that address pornography and sexualised media, but none of these programs address the broad suite of negative effects, nor have they been empirically tested for effectiveness.
In the long run, your student’s participation in the study may enable other students to benefit from the pilot program. The information gathered will provide a critical picture of attitudes and behaviours of the students involved, as well as knowledge of whether this unique combination of teaching elements can contribute to meaningful change in students’ lives.
(22) What will happen to information collected during the study?
By providing their consent, the parents of your students have agreed to us collecting personal information about your students for the purposes of this research study. Their personal information will only be used for the purposes outlined in this Participant Information Statement, unless you consent otherwise.
Your students’ information will be stored securely and their information will be kept strictly confidential, except as required by law. In addition to the survey being anonymous, researchers will not keep records of any device identifiers like I.P numbers of MAC addresses. Study findings may be published, but neither the school nor your students will not be individually identifiable in these publications.
We will keep the information we collect for this study, and we may use it in future projects. By providing their consent, parents are allowing us to use your students’ information in future projects. We don’t know at this stage what these other projects will involve. We will seek ethical approval before using the information in these future projects.
(23) Can we tell other people about the study?
Yes, you are welcome to tell other people about the study.
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(24) What if we would like further information about the study?
When you have read this information, Marshall Ballantine-Jones will be available to discuss it with you further and answer any questions you may have. If you or your child would like to know more at any stage during the study, please feel free to contact Marshall via email [email protected].
(25) Will we be told the results of the study?
Your school and the students who participate have a right to receive feedback about the overall results of this study. You can tell us that you wish to receive feedback by email. This feedback will be in the form of either an executive summary of a respective thesis chapter, or of a published peer-review journal. You will receive this feedback after the study is finished. It may be some months before this occurs, but the report will be posted on the Anglican Education Commission’s website http://www.edcomm.org.au/. The school will notify you when this happens.
(26) What if we have a complaint or any concerns about the study?
Research involving humans in Australia is reviewed by an independent group of people called a Human Research Ethics Committee (HREC). The ethical aspects of this study have been approved by the HREC of the University of Sydney [INSERT protocol number once approval is obtained]. As part of this process, we have agreed to carry out the study according to the National Statement on Ethical Conduct in Human Research (2007). This statement has been developed to protect people who agree to take part in research studies.
If you or your students are concerned about the way this study is being conducted or you wish to make a complaint to someone independent from the study, please contact the university using the details outlined below. Please quote the study title and protocol number.
The Manager, Ethics Administration, University of Sydney: • Telephone: +61 2 8627 8176 • Email: [email protected] • Fax: +61 2 8627 8177 (Facsimile)
This information sheet is for you to keep.
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Appendix G: Lesson Overview
Lesson Overview
This 6-lesson pilot teaching unit is for Year 10 students, doing the equivalent of Stage 4 under the HPE strand of the National Curriculum. The HPE aims are to: develop the knowledge, understanding and skills to enable students to… access, evaluate and synthesise information to take positive action to protect, enhance and advocate for their own and others’ health, wellbeing, safety and physical activity participation across their lifespan [1].
This pilot draws on the latest research to address how pornography relates to young people. The topics incorporate several perspectives as they relate to the student, including personal, relational, and societal. Each lesson is designed to stimulate critical thinking, creative exploration, and personal responsibility for choices and actions.
Additionally, each lesson incorporates three education strategies: engaging didactic teaching content, peer-group critical discussions, and parental engagement activities. The peer and parental strategies are novel features, prompted by empirical data that describes how significant both peer and parental engagement is on shaping a student’s knowledge, attitudes and behaviours. A baseline survey will measure the effect of peer and parental engagement on the student, with a follow up survey to analyse how the pilot modifies those effects.
Due to the sensitive nature of the content of this course, all teachers should be alert to how students are responding and coping to it. Students should be regularly reminded that if they feel distressed, that the school counselling services are available. Likewise, your school counselling and pastoral staff should be alerted to when the course is happening, so that they can be prepared to consult with any students that may need support.
Lesson Features
Aims and Outcomes:
Each lesson has the Aims, Outcomes, and relevant National Curriculum areas described at the beginning.
Way In
Each lesson commences with a “Way In” feature, which generally involves the following:
a. A short Vox Pop clip created by the students (Weeks 3-6) b. A Youtube/Vimeo clip raising discussion content for the weeks lesson c. Some general questions of reflection to generate thinking in preparation for the teaching content
Did You Know
Each lesson imparts the core teaching content through a “Did You Know” exercise. This involves the students using a worksheet with either ‘fill in the blanks’, ‘multiple choice’, or a ‘true or false’ quiz. The students are prompted to evaluate the content against their previous knowledge, to reinforce the factual data.
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Peer Group Time
Except for Lesson 1, which has reduced time due to the survey, each lesson requires that the class is divided into smaller discussion groups (of 4-8 students). They are to read through the discussion questions for each lesson and discuss. Two matters for consideration are:
1. It may be beneficial to arrange for a senior student, pastoral staff, or the appointment of a peer-leader to assist the process of discussing the peer questions. Quieter students may not contribute easily, so it will help if group leaders encourage all students to participate. 2. It is highly recommended that these groups are single-sex, and not mix gendered because the discussions may involve sensitive topics, including sexuality. The empirical data shows that boys are significantly more at risk of being highly exposed to pornography, thus having higher rates of compulsivity, positive attitudes towards: uncommitted sexual behaviour; seeing women as sex objects, and pornography in general. Conversely, females are 3.6 times more likely never to have viewed pornography, and generally have higher scores in social empathy, but lower scores in self-esteem, emotional stability, peer and parent relationships. These discussion groups are aimed to produce open, serious reflection and discussion. Mix groups may make females feel uncomfortable and intimidated, which could restrict their engagement.
Parental Diary
Each week, the student has a home assignment where they are to interview their parents. The interview involves asking a few topical questions related to the parent’s recollection of their own adolescents, with some comparisons to modern times. The goal of the parental diary is to generate communication between the student and parent in order to stimulate empathy for each other’s worldview and experience. Research suggests that students who have engaged parents (particularly regarding social media, the internet, sexuality and relationships), have better wellbeing outcomes and internet-related behaviours than those who do not have this engagement.
Students need to get their Parents to Sign-Off each week. Parents will have already been notified in advance of the pilot to expect conversation with their child.
Bring It Home
If there is time left over at the end of the lesson, the students can be gathered back from the peer group discussions for some general reflection. For example, questions like: Was there anything surprising in today’s lesson? Do you think some of the things discussed today will be easily accepted by students your age? Can you see ways society makes it easier or harder to accept this information?
Additional Content
Some lessons have additional activities, which are contained within their outline. One particular activity which could strengthen the student’s engagement is the Vox Pop activity found at the end of Lesson 2.
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Lesson Overview
Week 1 Porn, An Week 2 Porn and the Week 3 Porn and the Week 4 Porn and Week 5 Social Media Week 6 Social Media Introduction User Society Relationships and Identity and Sexualised Behaviour Online Topics covered
What is porn? Negative effects Who makes porn, and Effects on Social media and Sexting, the Law, and why Relationships. identity Porn in pop culture Effects on attitudes cyber bullying The reality for porn Porn as a bad educator Social media and real Why do people watch Effects on Behaviours Risk management and performers, friendship porn? Porn lacks Intimacy time management Dopamine and exploitation of Social media and real Is it a good Educator? repetitive behaviours vulnerable people Porn creates people insecurities Peer attitudes about Creates insecurities How porn effects mass sexualised media media Porn creates mistrust Increases Risk taking behaviours How porn sexualises Erectile Dysfunction women (and men) Effects memory and Bad long-term academic outcomes investment
Reduces desire and enjoyment for non- sexual activities
Reduces capacity for self-control/impulse control, delayed gratification and
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Appendix H: Background Content for Lessons
Background Content for Lessons
Lesson 1 Background
A broad body of international research describes a wide range of negative outcomes from an adolescent’s exposure to pornography. At least 65 empirical articles reviewing the impact of pornography on adolescents have been published (for example, see Owens [1], Peter and Valkenburg [2], Flood [3], Springate [4], and Bloom [5]). A smaller number of studies has not shown negative effects.
1. Negative effects associated with pornography exposure
Some of the negative effects associated with pornography exposure include: adapting attitudes of sexual objectification towards women [6], increased sexual aggression [6-10], increased positivity towards uncommitted sexual exploration [11], negative gender attitudes [6, 12, 13], increased compulsivity [14] and addictive behaviours [15], reduced self-esteem [16, 17], emotional stability, social empathy [9, 18], social conduct [1], poor family [1, 10] and peer relationships [19], and increased sexualised behaviours on social media, including ‘sexting’ [12, 20]. There are limitations to these studies, including most being cross-sectional that do not describe cause and effect. Study samples vary in size, age, and social background. The lack of longitudinal and controlled interventional research means that adverse effects of exposure to pornography have not been conclusively demonstrated in otherwise healthy adolescent populations. Studies have not used standardised measures, making it difficult to compare findings. Furthermore, as Valkenburg points out [2], the theoretical basis’s for understanding adolescent engagement with pornography are poorly developed, limiting the depth of analysis behind attitudes and behaviours.
2. Positive effects of associated with pornography
A small number of studies suggest that pornography exposure has positive effects, or at least effects that are not negative. Pornography viewing has been positively associated with: stronger relationships, increasing a couples’ desire to be with each other [21], better sexual understanding and practice, providing a recreational sexual outlet or a buffer against sexual assaults, and having therapeutic benefits for common sexological dysfunctions [22]. Some claim there is an educative benefit from viewing pornography to learn about sex, including new techniques, even if may not result in better sexual experiences [23]. Another study suggested that pornography improves positive attitudes towards women, whilst having no correlation with sexual aggression, rape culture, or a contribution to relationship breakdown [24]. Rasmussen found no association between pornography and committing violent harm [25]. Diamond also concluded that pornography had no negative social effect on sex related crimes and child sexual abuse, contrarily those countries with relaxed pornography laws had a decline in these incidences [26]. One analysis of the widely consulted 2002 Swiss Multicenter Adolescent Survey on Health concluded that ‘pornography exposure is not associated with risky sexual behaviour’ [27]. Lastly, Prause et al concluded that there was no association with pornography and riskier behaviour, and that to describe pornography use as ‘addictive’ was not empirically valid [21].
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Overall the evidence for the positive effects of pornography is sparse, and outweighed by the volume of research associating pornography with negative effects.
In a recent survey on adolescent sexuality, wellbeing, and exposure to pornography (conducted in May-June 2018 on 750 Year 10 students from 7 Sydney-based independent schools), data were obtained that described the prevalence of pornography exposure on young people. A report of this study, performed by Marshall Ballantine-Jones through the Medical School at the University of Sydney, can be found here: https://www.edcomm.org.au/publications/school-pornography-survey- 2018/. Table 1 describes the frequency of pornography viewing amongst the students. Females are 3.8 times more likely never to have watched pornography, whilst males are 7.6 times more likely to watch pornography at extreme frequencies (weekly or more). Overall, 70% of male students and 21% of females view pornography monthly or more. These results are consistent with other contemporary adolescent surveys within Australia and internationally, for example Lim [28] and Valkenburg [11], making the degree of exposure amongst this cohort typical and generalisable.
Table 1
Pornography Viewing Frequency Prevalence Table Male Female Total
Never 82 (14.5%) 101 (55.5%) 183 (24.5%)
Less than monthly 86 (15.2%) 43 (23.6%) 129 (17.3%)
Monthly 110 (19.5%) 24 (13.2%) 134 (18.0%)
More than once/month but less than once/week 122 (21.6%) 7 (3.8%) 129 (17.3%)
Weekly 117 (20.7%) 7 (3.8%) 124 (16.6%)
More than once/week but less than every day 37 (6.6%) 0 (0.0%) 37 (5.0%)
Daily 10 (1.8%) 0 (0.0%) 10 (1.3%)
Total 564 (100%) 182 (100%) 746 (100%)
Note: Question adapted from Valkenburg’s Pornography Exposure Scale [11].
Additional data from the study show that the average age of first time exposure, for students who indicated they had previously encountered pornography, was 12.1 years (with 12.1 for males and 12.3 for females). Table 2 describes the preferred method of viewing pornography, with most students accessing via a phone, followed by an alternative digital device.
Table 2 Preferred Viewing Device Preferred Device Table Male Female Total
Phone 282 (58.0%) 33 (38.4%) 315 (55.1%)
Tablet/iPad 60 (12.3%) 10 (11.6%) 70 (12.2%)
Laptop 92 (18.9%) 21 (24.4%) 113 (19.8%)
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Desktop 6 (1.2%) 1 (1.2%) 7 (1.2%)
TV 12 (2.5%) 6 (7.0%) 18 (3.1%)
Other 34 (7.0%) 15 (17.4%) 49 (8.6%)
Total 486 100% 86 100% 572 100% Note: only one choice was given
Males were more likely to initiate sexualised social media behaviours (m30%, f22%), which include the sending of sexualised messages and images via social media accounts and phones. Females, however, were more likely to received sexualised social media content (m43%, f46%).
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Lesson 2 Background
Negative effects of pornography on the User
Objectification, sexual aggression, and negative gender attitudes.
Pornography exposure is associated with objectification attitudes and increased sexual aggression [1-5]. Studies suggest that the type of pornography viewed (violent or non-violent) has little effect on the degree of violent tolerance found in users (verbal aggression is more affected than physical aggression, but not significantly different) [3]. Regular consumers of pornography are inclined to hold negative gender attitudes [4, 6, 7] and commit sexual harassment [8].
Furthermore, studies suggest that increased sexual aggression occurs in both males and females after prolonged exposure to pornography [3]. Sexual aggression can be a precursor to rape and domestic violence. A landmark study of 304 scenes from a random sample of the top 275 selling adult movies in 2005 showed an extraordinary picture of the level of violence in contemporary pornography. It showed that 88% of scenes contained physical violence (including choking, spanking, gagging, slapping, and hair-pulling); 49% contained verbal violence; 94% of the recipients of violence were women; and 95% of the violence was received neutrally or with pleasure [9]. Women who watch porn increase their acceptance of victimisation over time, as their exposure to sexually aggressive (towards women) pornography normalises such behaviour [8].
Mental Health and Behaviour changes
There is a range of adverse mental health consequences from pornography usage. Depression, reduced self-esteem [10, 11], sexual insecurity [13], and anxiety accompany prolonged use. Doornwaard showed a relationship between psychological wellbeing (lower levels of self-esteem) and excessive sexual interest as predictors of compulsive porn use [10].
Pornography has been shown to be a poor sex educator [14]. Increased exposure to pornography increases sexual uncertainty and confuses sexual belief [12, 13]. It increases unrealistic attitudes about sex, including altering the users sense of sexual realism [13, 15].
Academic outcomes, especially for adolescents, are poorer in pornography users [16]. Some studies have shown that memory retention is also compromised in long-term pornography users [17, 18]. Prolonged exposure to pornography leads to significant behavioural changes. This includes increases in acting out [19], casual sex [12, 15, 20], earlier first-time sexual activity [2], sexually permissive attitudes[13], and sexual sensation seeking[21, 22]. Additionally, general increases in risky behaviour [2, 21] (including sexting), alcohol consumption have been found [23]. There is also evidence of increased sexual preoccupation, [13, 24, 25], and reduced capacity to delay gratification [13, 26-29]. Lastly, a significant percentage of long-term pornography users have found it more difficult to find sexual satisfaction with a real partner. This includes males being diagnosed with erectile dysfunction disorder [2, 3].
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Some Supplementary Research on Possible Neurological Effects of Hypersexual Exposures
There is an emerging body of scientific research from the last decade suggesting that pornography has major effects on the individual user. This is not well validated science, with minimal research being longitudinal or under controlled conditions. However it is useful to know how some researchers are exploring the intersection of neurology, biology and sexuality sees major behaviour changes. This is supplementary research which you may find helpful when your students critique the videos about dopamine and pornography.
At its core, pornography stimulates our sexual systems, which are primarily an activity of the brain. The physical act of sex, which on the surface is the stimulation of the genitals to produce an orgasm, is in fact a brain activity from first to last.
Sex and the Brain
The sexual processes of desire, arousal, anticipation, excitement, fulfilment, and recovery involve numerous powerful hormones which flood the brain. Some basic hormonal functions include:
• Dopamine, the hormone responsible for excitement and anticipation, is produced in large volumes in anticipation of the reward of an orgasm and sexual fulfilment. The limbic system of the brain, which includes the reward and pleasure areas, has numerous dopamine receptors, which react to certain cues – including sexual ones. During the process of sexual arousal, large volumes of dopamine are generated in the limbic system. As dopamine is produced, brain signals from the pre-frontal cortex are bypassed. The pre-frontal cortex is the area of the brain responsible for judgement and self-control. • Endorphins and enkephalins, which are natural opioids, are stimulated and released during orgasm, relaxing muscles, alleviating pain, and regulating stress. In other words, following the intense pleasurable feeling of an orgasm, there is an ongoing feeling of relaxation and satisfaction. • Oxytocin is released following orgasm, which has a bonding function, drawing the person closer to the object of their desires. • Norepinephrine is a neurotransmitter produced during sexual arousal. It is both a natural adrenaline, increasing elated energy, and mediates communication in the sympathetic nervous system. It enhances memories, such that experiences during heightened levels are forged into the memory. • Serotonin, the hormone associated with mood regulation, reduces during arousal. This reduction lowers our inhibition and self-control, and relaxes us.
How sex changes the brain over time
Not only does oxytocin bond us to our sexual partner, but over time, dopamine causes changes to our brains, so that our desires and triggers for arousal become more established. More specifically:
• Neural pathways are reinforced through repeated cycles of dopamine and norepinephrine production such that the things we desire become more concrete. • At the same time, other interests and activities become less desirable, as our limbic system adapts to those preferred triggers for dopamine reception. • Dopamine causes a bypassing of the signals from the frontal cortex – the part of the brain responsible for judgement and self-control. Overtime, the brain adapts by less engagement of the frontal cortex – and in the case of adolescents with underdeveloped brains, retarding it’s maturing.
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Scientifically, our brains are wired to enhance our desires and attachments to the person we’re sexually engaged with.
Pornography hijacks the natural sexual process
With pornography, the consumer bonds with many images and concepts, amplified by sight and sound. The other senses (touch, taste, and feelings) become less associated with sexual desire, and are disassociated from sexual arousal. This is why porn users can be highly aroused by images, but find it difficult to be aroused by a real person.
When exposed to high volumes of dopamine over a period of time, dopamine receptors are reduced, requiring more dopamine to experience similar levels of excitement and anticipation than previously. Consequently, porn users progress into more unsavoury, extreme fetishes, because the previous things that used to arouse them no longer generate the same excitement. Below we present a summary of the research on the negative neurological effects of pornography.
Neurological effects.
A wave of recent scholarship has emerged on the relationship between compulsive pornography use and it’s neurological impact, with one source citing 37 neurological studies and 13 literature reviews [36]. The evidence of these studies show that regular pornography use causes real change to the brain, and supports the view that compulsive pornography-use fits the behavioural addiction models of similar DSM-5 disorders like Internet Gaming Disorders [30].
For example, one study from Cambridge by Valerie Voon found that compulsive pornography users had heightened reactions to sexual cues in the dorsal anterior cingulate, ventral striatum and amygdala – generally associated with sexual desire, that is to say, ‘craving’ increased. Yet they also found that these same subjects had no increase in the desire, or ‘liking’, pornography. Thus researchers concluded that this brain behaviour was consistent with drug addictions [31].
Another study of compulsive pornography users showed significant reduction in the functional (activity between the amygdala and the dorsolateral prefrontal cortex (DLPFC) compared to non- pornography users. The DLPFC is widely accepted as the instrument of cognitive control, and the functional activity between it and the amygdala is associated with a range of behaviours including emotion regulation, impulsivity, modulating negative emotions, as well as anxiety, depression and stress.
This loss of the frontal control system, known by neuroscientists as the braking system, is well documented amongst patients with substance addictions like cocaine and methamphetamines, accompanied by observable reductions in brain volume [32]. Studies of compulsive pornography users have also shown similar losses in grey brain matter, in particular the right striatum, as well as reduced functioning of the left putamen – both of which mediate cognition of various functions including executive controls. [33]
The authors at www.yourbrainonporn.com summarise these combined studies suggesting that pornography affects the brain in three ways:
• sensitisation – where motivational and reward circuits become hypersensitive to memory cues; • desensitisation – where the brain becomes less-sensitive to pleasure;
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• and hypofrontality – where the increased dysfunction between the prefrontal cortex and limbic system results in reduced impulse control, and increased cravings.
Regarding addiction, there has been (general) reticence in classifying problematic pornography use as addictive. In part that has been due to a classical definition of addiction as pertaining to substances like alcohol, opiates and cocaine [34], as well as the relatively new research frontier of pornography and neurology. However, in 2011 the American Society of Addiction Medicine (ASAM) redefined addiction to include other broader behavioural influences on the brains reward, motivation and reward circuitry. In 2013 the American Psychiatric Association (APA) added Internet gaming disorder as an addiction in its Diagnostic and Statistical Manual (DSM-5), however there was no reference to internet pornography addiction. Love (et al) makes the compelling argument that compulsive internet pornography use fits into the addiction framework, sharing similar processes as substance addictions [34].
More broadly, further research has shown the brain’s neuroplastic capacity to change itself, including adapting and recovering from various injuries and disorders. Doidge, a leader in this science, claims that partial to complete cues can be constructed under certain circumstances [35]. This is relevant for pornography users in that just as the brain can negatively adapt to regular neurological stimulation, intentional therapy can reverse the effects of pornography – either in creating alternative neural pathways for other activities, as well as reducing the degree of reactivity to sexual cues. That is, cognitive behavioural and other therapies may find success in reversing the neurological effects of long-term pornography use on compulsive users. At present there is little to no research to show if this is specifically the case, but in light of general support for the brains ongoing plasticity, studying the capacity of the brain to reverse/reduce dependency on pornography warrants serious consideration.
Thus, the overall evidence is that excessive long-term pornography use does impact the brain, particularly the limbic system and DLPFC, in ways consistent with substance addictions, and any genuine intervention seeking to reduce the effects of pornography on a user needs to allow for proven addictive behaviour therapies.
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Lesson 3 Background
Some of the criticisms of pornography production and its impact on society include:
It’s driven solely by profit.
The argument has been made that the primary beneficiaries of pornography are the producers, distributors, advertisers, technology producers and service providers. Although a large amount of pornography is free online, profit is made through advertising. It’s difficult to ascertain the annual worldwide income from pornography, since there is little transparency from producers and distributors. However, estimations lie between $12 billion and $96 billion per annum [1].
Pornography production is generally not regulated.
Describing pornography as an ‘industry’ is deceptive, as even in the most heavily regulated region, California, workers are deprived of:
• health insurance • sick-leave • annual-leave • job redeployment services • job security • minimum wages • contraceptive protection.
Gross copyright breaches by mainstream providers are also common practice [1]. It is not a conventional industry abiding by common standards; and performers are not employed on equal terms with standard workers of countries like Australia and the USA.
Performers are generally exploited and disadvantaged.
There is an absence of reliable quantitative studies on the impact pornography has on the ‘performers’, however some qualitative research suggests that pornography performers display higher rates of:
• Depression and anxiety • child sexual abuse, • living in poverty, • STIs, and • substance abuse [2] [3] [4].
Performers regularly report doing things against their will.
Qualitative studies also claim that performers are often coerced, manipulated, deceived and threatened [5]. It would seem that only the most esteemed performers in safer regions like California are awarded the protection of negotiations and terms prior to shooting, but the majority are not paid well [1].
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Pornography and prostitution go hand in hand.
Porn production and performers have well-documented links with prostitution [3, 6]. This is unsurprising as by definition, prostitution is the engagement of sexual activity for money. Porn is therefore connected with various abuses and vulnerabilities associated with prostitution generally, including:
• financial exploitation [2] • human trafficking [7] [8] • child-sexual abuse [2]
Many women and children who are trafficked and prostituted are used for the production of pornography against their will and without consent [9].
Pornography leaves a permanent record.
The reality of internet pornography is that it is impossible to eliminate. Porn performers are placed on perpetual display. Even when a performer chooses to leave the ‘industry’, they have no control over the ongoing distribution of their activities – they are permanently controlled and defined by the stigma of the past [1]. It could be argued that this is a form of slavery of people who may have already been vulnerable when they first participated.
Popular culture is in constant step with pornography.
Researchers have suggested that there is a steady increase of sexual material in consumer content over time [10]. That is, all forms of mainstream media have adopted sexualised materials previously found only in pornography. For example:
• Current popular television series feature the use of frequent, intense sex scenes • R-rated movies on Foxtel now contain full penetration scenes and frontal ejaculation. • Contemporary music videos when compared to those of the 1980s show the huge development of overt sexual themes and images. • Commercials like the Ultra Tune Auto Service Centres series (despite being the most complained about Australian commercials in 2017 due to their highly sexualised content) were not restricted by Australia’s Ads Standards Board [11].
Porn culture changes social behaviour.
Other research claims an association between exposure to sexualised mass media (movies, advertising, television and magazines) accelerates sexual activity and early first-time intercourse in young people [12].
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Porn culture sexualises young girls.
As pornography infiltrates and influences mainstream media, there is evidence of the increasing sexualisation of young girls in society [13]:
• The marketing strategy of ‘age compression’ (where products are marketed to younger ages) has been linked with reducing girls’ ‘space for action’ – that is, redefining their femininity and beauty through overt sexualised media exposure [14]. • Further evidence points to the growing pressure on females to look and behave more sexually [13].
Pornography may increase objectification culture.
• A number of studies suggest that over time, porn users adopt objectifying attitudes towards women [16, 17], including aggression towards women [18]. This predominately, but not exclusively, applies to males who are the main consumers of pornography. • This leads to a larger social risk of pornography influencing a power imbalance skewed against women.
Pornography is associated with riskier, more aggressive behaviour, and more frequent casual sex.
Users of porn, especially younger users, seem increasingly comfortable with pornography in society and casual sex [20]. A meta-analysis of 22 studies also posited that consuming porn was associated with ‘an increased likelihood of committing actual acts of sexual aggression [18].
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Lesson 4 Background
Research suggests that porn produces unrealistic sexual expectations between couples about sex. It may put undue pressure on the non-user (usually the female) to conform to unrealistic and unpleasant sex that is devoid of intimacy. Some of the main risks that have been associated with relationships affected by porn include:
It places undue pressure on partners.
One study reported that almost eight out of ten young women (77%) claim that pornography has pressured them ‘to look a certain way’, while 75% say that it has led to pressure ‘to act a certain way.’[1]
It may contribute to erectile dysfunction disorder.
One study found over 50% of porn users experienced diminished libido or erectile function in real relationships [2, 3]. Although there is absence of reliable clinical studies that concretely identify pornography as a cause of various sexual dysfunctions, this systematic review concludes there is ample evidence pointing to a sharp rise in the reporting of such dysfunctions, warranting further research [37]. The risk that should be communicated to current and potential pornography users is that although they think that exploring pornography will help them sexually, this may not be the case. Voon’s study concluded that due to porn’s neuroplastic power, there may be a corruption to one’s arousal mechanisms, reducing the chance of enjoying physical sex with a single partner, even if there may be no trouble being sexually aroused by porn [38].
It aggravates dishonesty, mistrust and insecurity in relationships.
Research suggests that couples who are both non-users of pornography have higher sexual and relational satisfaction, whilst when one or both partner use porn, they have much lower sexual satisfaction[4]. Furthermore, when a woman discovers her husband’s porn use, she experiences trauma akin to if her husband were cheating on her, resulting in lower self-esteem and a deeply altered perception of her husband’s character and trustworthiness [5]. Honesty leads to relationship satisfaction amongst women, so secrecy places a wedge between seeking out joy in a relationship and actual relationship satisfaction[4].
It contributes to adultery and can reach far beyond your marriage.
Studies suggest that porn users are inclined to perceive extra-marital romantic relationships as superior, and therefore seek them out [6]. One 2014 survey of 350 members of the American Academy of Matrimonial Lawyers suggested that 56% of divorces were related to ‘obsessive interest in pornographic sites’ [7]. Ultimately, when a relationship breaks down, there are always broader costs impacting finances, ministry, friendships and family.
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Lesson 5 and 6 Background
Emerging worldwide research describes the prevalence of Sexualised Social Media Behaviours. Often described as ‘Sexting’, this behaviour has multiple concerns, not the least being the illegal distribution of child pornography behaviour [39]. Some statistics from Europe suggest that up to 69% of females (average age of 14) have sent a form of sext, whilst up to 77% have received one. For males, up to 46% have sent a sext, and up to 58% have received [12].
In an Australian context, the recently published National Survey of National Survey of Australian Secondary Students and Sexual Health (2013 by La Trobe University) [40] describes this prevalence for a large sample of students aged 14-18. Our own recent study of Year 10 students, found here [41], compared its results with the La Trobe study, providing a more realistic assessment of how typical these behaviours are in an Australian context. Table 1 shows that males are more likely to send sexualised content via social media, whilst girls are more likely to receive them. The total figures for sending and receiving content is less than the La Trobe figures, however the La Trobe study combined Years 10-12, with no way of isolating Year 10 students. However, the two samples compare well in other measures, and it is reasonable to conclude that the students in our study are typical. Furthermore, with around 30% of students having sent a sexual message, and 44% having received one, there is ongoing alarm for parents and educators, since the risk for violating the law, let alone the many other behavioural and attitudinal risks associated with sexualised social media behaviour remain.
When considering more general social media behaviours, there have been a handful of studies examining the relationship between student wellbeing, narcissism, and sexualised behaviours. The findings, although preliminary, are concerning. For example, frequency of selfie-posting has been associated with increased sexualised behaviours, engagement with pornography, high self-esteem, compulsive behaviours, and lower social-empathy. Most concerning is the potential association between social media usage and narcissistic personality disorder, which has been flagged in the research but requires more investigation to understand more deeply as it relates to adolescent identify formation [42-44].
Lastly, there are a range of legal concerns related to online behaviours. The eSafety Commissioner website contains helpful UpToDate content relating to illegal behaviours, making complaints, and helpful tools for safe online behaviours. From their website [45]:
The following types of content may be classified as prohibited:
• footage of real or simulated violence, criminal activity or accidents from video clips, games or films • sexually explicit content • images of child sexual abuse • content that advocates the doing of a terrorist act • content instructing or promoting crime or violence.
Another helpful resource is this summary of how Crimes Act (1995) relates to various online sexualised behaviours, which are discussed in this lesson [46].
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Table 1 Sexualised Social Media Behaviour La Trobe Question Male Female Total n=2100+ n=564 n=182 n=746
52% Never 60% 68% 62%
Have you ever sent a sexually explicit written text Don't know 9% 10% 9% 5% message? 43% Yes 30% 22% 28%
Never 49% 47% 48% 42% 4% Don't know 8% 7% 8% Have you ever received a sexually explicit written Yes 43% 46% 44% 54% text message? 72% Never 78% 84% 79% 3% Don't know 5% 2% 4% Have you ever sent a sexually explicit nude or Yes 17% 15% 16% 26% nearly nude photo or video of yourself? 89% Never 88% 92% 89%
Don't know 4% 3% 4% 2% Have you ever sent a sexually explicit nude or 9% Yes 7% 5% 7% nearly nude photo or video of someone else? Never 59% 55% 58% 56% 2% Don't know 7% 4% 6% Have you ever received a sexually explicit nude Yes 35% 41% 36% 42% or nearly nude photo or video of someone else? 74% Never 68% 87% 73%
Don't know 9% 5% 8% 4% Have you ever used a social media site for sexual 22% Yes 23% 8% 19% reasons? Never 73% 86% 76% - - Don't know 18% 10% 16% Is sending and receiving naked pictures a normal Yes 9% 4% 8% - thing your friends do with each other? - Never 49% 54% 51%
Don't know 25% 26% 25% - Is sending naked pictures acceptable amongst Yes 26% 20% 25% - close friends or people who are in a relationship? Note: Questions 1-6 adapted from National Survey of Australian Secondary Students and Sexual Health 2013 [40].
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Lesson Background References
1. Owens, E.W., et al., The Impact of Internet Pornography on Adolescents: A Review of the Research. Sexual Addiction & Compulsivity, 2012. 19(1-2): p. 99-122. 2. Peter, J. and P.M. Valkenburg, Adolescents and pornography: a review of 20 years of research. The Journal of Sex Research, 2016. 53(4-5): p. 509-531. 3. Flood, M., The harms of pornography exposure among children and young people. Child Abuse Review, 2009. 18(6): p. 384-400. 4. Springate, J. and H.A.M.D. Omar, The impact of the Internet on the sexual health of adolescents: A brief review. International Journal of Child and Adolescent Health, 2013. 6(4): p. 469-471. 5. Bloom, Z.D. and W.B. Hagedorn, Male Adolescents and Contemporary Pornography. The Family Journal, 2015. 23(1): p. 82-89. 6. Peter, J. and P.M. Valkenburg, Adolescents’ Exposure to a Sexualized Media Environment and Their Notions of Women as Sex Objects. Sex Roles, 2007. 56(5): p. 381-395. 7. Zillmann, D. and J.B. Weaver, Pornography and men's sexual callousness toward women, in Pornography: Research advances and policy considerations. 1989, Lawrence Erlbaum Associates, Inc: Hillsdale, NJ, US. p. 95-125. 8. Villani, S., Impact of media on children and adolescents : a 10-year review of the research U6 - ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF- 8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Ak ev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Impact+of+media+on+children+and+adol escents+%3A+a+10- year+review+of+the+research&rft.au=Villani%2C+Susan&rft.externalDBID=n%2Fa&rft.extern alDocID=b29339546¶mdict=en-US U7 - Course Reading. 2001. 9. Wright, P.J., R.S. Tokunaga, and A. Kraus, A Meta-Analysis of Pornography Consumption and Actual Acts of Sexual Aggression in General Population Studies. Journal of Communication, 2016. 66(1): p. 183-205. 10. Ybarra, M.L., et al., X-rated material and perpetration of sexually aggressive behavior among children and adolescents: is there a link? Aggressive Behavior, 2011. 37(1): p. 1-18. 11. Peter, J. and P.M. Valkenburg, Adolescents' exposure to sexually explicit internet material, sexual uncertainty, and attitudes toward uncommitted sexual exploration: Is there a link? Communication Research, 2008. 35(5): p. 579-601. 12. Stanley, N., et al., Pornography, Sexual Coercion and Abuse and Sexting in Young People’s Intimate Relationships. Journal of Interpersonal Violence, 2016: p. 0886260516633204. 13. Hald, G.M., N.N. Malamuth, and T. Lange, Pornography and sexist attitudes among heterosexuals. Journal of Communication, 2013. 63(4): p. 638-660. 14. Grubbs, J.B., et al., Internet pornography use: Perceived addiction, psychological distress, and the validation of a brief measure. Journal of Sex & Marital Therapy, 2015. 41(1): p. 83-106. 15. Fernandez, D.P., E.Y.J. Tee, and E.F. Fernandez, Do Cyber Pornography Use Inventory-9 Scores Reflect Actual Compulsivity in Internet Pornography Use? Exploring the Role of Abstinence Effort. Sexual Addiction & Compulsivity, 2017. 24(3): p. 156-179. 16. Doornwaard, S.M., et al., Lower Psychological Well-Being and Excessive Sexual Interest Predict Symptoms of Compulsive Use of Sexually Explicit Internet Material Among Adolescent Boys. Journal of Youth and Adolescence, 2016. 45(1): p. 73-84. 17. Bélanger, R.E., et al., A U-Shaped Association Between Intensity of Internet Use and Adolescent Health. Pediatrics, 2011. 127(2): p. e330-e335. 18. McKee, A., Methodological Issues in Defining Aggression for Content Analyses of Sexually Explicit Material. Archives of Sexual Behavior, 2015. 44(1): p. 81-87. 19. Marriott, E., Men and Porn. The Guardian, 2003.
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20. Morelli, M., et al., Sexting Behaviors and Cyber Pornography Addiction Among Adolescents: the Moderating Role of Alcohol Consumption. Sexuality Research and Social Policy, 2017. 14(2): p. 113-121. 21. Staley, C. and N. Prause, Erotica Viewing Effects on Intimate Relationships and Self/Partner Evaluations. Archives of Sexual Behavior, 2013. 42(4): p. 615-624. 22. Hald, G.M., C. Seaman, and D. Linz, Sexuality and pornography. 2014. 23. Rothman, E.F., et al., “Without Porn … I Wouldn't Know Half the Things I Know Now”: A Qualitative Study of Pornography Use Among a Sample of Urban, Low-Income, Black and Hispanic Youth. The Journal of Sex Research, 2015. 52(7): p. 736-746. 24. Diamond, M., Porn: Good for us? Scientific examination of the subject has found that as the use of porn increases, the rate of sex crimes goes down. The Scientist, 2010. 24(3): p. 29-30. 25. Rasmussen, K., A Historical and Empirical Review of Pornography and Romantic Relationships: Implications for Family Researchers. Journal of Family Theory & Review, 2016. 8(2): p. 173-191. 26. Diamond, M., E. Jozifkova, and P. Weiss, Pornography and Sex Crimes in the Czech Republic. Archives of Sexual Behavior, 2011. 40(5): p. 1037-1043. 27. Luder, M.-T., et al., Associations Between Online Pornography and Sexual Behavior Among Adolescents: Myth or Reality? Archives of Sexual Behavior, 2011. 40(5): p. 1027-1035. 28. Lim, M.S.C., et al., Young Australians' use of pornography and associations with sexual risk behaviours. Australian and New Zealand Journal of Public Health, 2017: p. n/a-n/a. 29. https://yourbrainonporn.com/brain-scan-studies-porn-users 30. Association, D.-A.P., Diagnostic and statistical manual of mental disorders. Arlington: American Psychiatric Publishing, 2013. 31. Voon, V., et al., Neural Correlates of Sexual Cue Reactivity in Individuals with and without Compulsive Sexual Behaviours. PLoS ONE, 2014. 9(7): p. e102419. 32. Hilton, D.L. and C. Watts, Pornography addiction: A neuroscience perspective. Surgical neurology international, 2011. 2(1): p. 19. 33. Kühn, S. and J. Gallinat, Brain structure and functional connectivity associated with pornography consumption: The brain on porn. JAMA Psychiatry, 2014. 71(7): p. 827-834. 34. Love, T., et al., Neuroscience of Internet Pornography Addiction: A Review and Update. Behavioral Sciences, 2015. 5(3): p. 388. 35. https://www.barna.org/blog/culture-media/barna-group/porn-press- conference#.VrS9OrSJndl., J.M.M., The Porn Phenomenon: A Comprehensive New Survey on Americans, the Church, and Pornography. 2016, Barna Group: Ventura, California. 36. https://yourbrainonporn.com/brain-scan-studies-porn-users 37. Park, B.Y., et al., Is Internet Pornography Causing Sexual Dysfunctions? A Review with Clinical Reports. Behavioral sciences (Basel, Switzerland), 2016. 6(3): p. 17. 38. Voon, V., et al., Neural correlates of sexual cue reactivity in individuals with and without compulsive sexual behaviours. PloS one, 2014. 9(7): p. e102419. 39. Commissioner, O.o.t.e., Sexting: social and legal consequences 2016: Australian Government. 40. Mitchell, A., et al., National survey of Australian secondary students and sexual health 2013. Melbourne: Australian Research Centre in Sex Health and Society & La Trobe University, 2014. 41. https://www.edcomm.org.au/publications/school-pornography-survey-2018/ 42. Andreassen, C.S., S. Pallesen, and M.D. Griffiths, The relationship between addictive use of social media, narcissism, and self-esteem: Findings from a large national survey. Addictive Behaviors, 2017. 64: p. 287-293. 43. Pantic, I., et al., Association between physiological oscillations in self-esteem, narcissism and internet addiction: A cross-sectional study. Psychiatry Research, 2017. 258: p. 239-243.
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44. McCain, J.L. and W.K. Campbell, Narcissism and Social Media Use: A Meta-Analytic Review. 2016. 45. https://www.esafety.gov.au/esafety-information/esafety-issues/offensive-or-illegal-content 46. http://www.findlaw.com.au/articles/4720/sexting-and-australian-law.aspx
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Appendix I: Lesson Outlines
Lesson 1 Porn, an introduction
Aims and Outcomes
Aims: This lesson will introduce the general topic of pornography and its prevalence in society, the media, internet, social media, and peer groups. The survey, video content, teaching content and general discussion will assist gauging the current awareness and attitudes of the students towards sexualised media and its usage. Some basic definitions about the topic as it pertains to adolescent exposure is provided. There are no peer discussion groups in lesson one due to the survey. Week 1 parent diary questions are designed to ease the students into a general dialogue with their parents, focussing on the parents perception of how society has changed between the their own adolescents and their child’s.
Outcomes: Students will learn what pornography is and how it is generally used amongst contemporary adolescents. They will be challenged to think about whether pornography has positive and negative influences on society. They will be presented with some popular perceptions about pornography by celebrities, and they will be provided an opportunity to enter the past world of their parent’s adolescents.
Background Content
See Lesson 1 in document Background Content for Lessons
Australian Curriculum
HPE Strand: strategies for relating to and interacting with others, establishing and managing changing relationships (offline and online), managing the physical, social and emotional changes that occur during puberty General Capabilities: Critical and Creative Thinking, Personal and Social Capability, Ethical Understanding Capability
Survey
Get students to conduct the online survey as pre-arranged with your head of department. Some students will finish earlier than others, so be prepared to keep them quiet until the last person has finished. This should be finished in under 25 mins.
Way in – feature/activity
Watch this Vlog by actor Terry Crews, https://www.youtube.com/watch?v=I4krRkO4sHc (running time 5mins), as a topic raiser (a shorter alternative is this Russell Brand clip https://www.youtube.com/watch?v=WsjJZgz9mx0).
Ask these general questions to the class:
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1. Do you think pornography has an impact on society? 2. Do you think pornography is a good thing for society?
Did you know – Teaching content
Instruction: get students to open Worksheet Lesson 1. Work through it question by question. Where there are blanks, give students time to think about a possible answer before dictating the correct answer for them to fill in.
1. How would you define ‘pornography’? Discuss a. ‘pornography’ comes from two ancient Greek words: ‘porneo’ meaning sexual immorality ‘graphei’ meaning writings 2. Can the following be defined as pornography? a. Sexually explicit internet sites b. Video games with sexual images c. Erotic literature d. Underwear catalogues e. Music video clips f. Renaissance art? g. Old postcards with swimsuit models? h. Handbags and high heel shoes? i. Poetry?
(Answer: if it is a form of media that is intended to sexually arouse, it is pornography. It is very subjective because what arouses one person may not arouse another)
3. Why do people look at pornography? Discuss a. (common answers include personal arousal, boredom, fun, curiosity, education, sexual expression – most common is personal arousal) 4. How many people look at pornography regularly (for students 15 years old)? a. 70% of males look at pornography monthly or more b. 21% of females look at pornography monthly or more c. 15% of males have never watched pornography d. 50% of females have never watched pornography 5. Do you think viewing pornography is helpful, harmful, or a bit of both? Discuss 6. Do you think Pornography has an influence on the following (write Y/N)? a. Mainstream movies b. Tv shows c. Advertising d. Movie clips e. Fashion f. Hollywood celebrities g. Sporting celebrities h. Art 7. Write a sentence to capture the opinions of your friends on the following: a. Pornography has the following effects on the user . b. Pornography has the following effects on relationships . c. Pornography has the following effects society . 8. Do you think pornography producers are providing a social service or business? Discuss
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a. It is estimated that the pornography business between 12 and 96 $billion per year 9. Males are more likely to use social media to send a sexualised content (a sext), but females are more likely to receive a sext. Why do you think this is?
Peer Group Discussions
There is no Peer Group Discussion in Lesson 1, although you may want to begin the process of allocating students into their groups in preparation for the remaining weeks.
Parent Diary
For homework, have students complete Lesson 1 of the Parent Diary.
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Lesson 2 Porn and the User
Aims and Outcomes
Aims: This lesson describes ways that compulsive pornography affects attitudes and behaviours on the individual. Implications include: sexual preoccupancy, increased objectification of women, increased sexual risk taking and earlier sexual engagement, reduced delayed gratification, reduced capacity to be stimulated by non-pornography activities, increased sexual aggression, reduced academic outcomes, and reduced memory retention.
Outcomes: students will be able to identify some of the common risks associated with pornography use. They will be challenged to consider if it is a good or bad investment for their own future relationships.
Background Content
See Lesson 3 in document Background Content for Lessons
Australian Curriculum
HPE Strand: managing the physical, social and emotional changes that occur during puberty, puberty and how the body changes over time, managing the physical, social and emotional changes that occur during puberty, reproduction and sexual health General Capabilities: Critical and Creative Thinking, Personal and Social Capability, Ethical Understanding Capability
Way in – feature/activity
• Show the student Vox Pop for Lesson 2. • Option 1: Watch the following video on ‘The Science of Pornography Addiction (SFW)’ https://www.youtube.com/watch?v=1Ya67aLaaCc • Option 2: Watch the following on the brain chemistry and porn by Eternity News https://www.youtube.com/watch?v=f-SE0oBoR6w Ask: what description did the psychologist give for the effect porn has on the brain? Do you think there could be other consequences for being highly exposed to sexual content? • Optional activity: Set up a class debate on the topic - Does pornography provide good education about sex?
Did you know – Teaching content
Run the following test from the Did You Know section. Answers are either True or False. After the full quiz is completed, reread through each question, giving the correct answer. Get students to tally their scores. Be ready to respond to queries from students, as some answers may be counter intuitive to them. Explain to them that each answer is drawn from various studies (listed in the accompanying research in the Lesson Background section).
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• Regular pornography use reduces memory function (true) • Female pornography users are more likely to have negative attitudes about women (true) • Most modern pornography involves violence against women (true) • Pornography users are less aggressive in their relationships (false) • Pornography use increases your sexual confidence (False – it increases sexual uncertainty) • The older you begin watching porn, the higher chance for compulsive behaviours (being addicted) as you grow older (false) • Being a porn user improves self-control in other areas of life (false) • Having higher levels of excitement from pornography also increases excitement for other fun things in life (false – it reduces general levels of excitement) • The more pornography you use, the more cautious you are about risk taking (false) • People who don’t use porn are more likely to be depressed (false) • People who don’t use porn have lower self-esteem (generally false, although those with narcissism may have increased self-esteem) • People often view pornography to learn about sex (true) • Pornography is known to be a good sex educating tool (false, evidence says it is a poor educator) • Pornography is a good way to improve academic outcomes (false) • People who view pornography will be more realistic about social relationships, and less likely to commit sexual harassment (false – porn users tend to have lower social empathy, and are more likely to accept sexual aggression and commit sexual harassment) • Sexual aggression has no influence on rape and domestic violence? (false) • Excessive pornography users are more likely to find physical sex with a partner satisfying than for non-pornography users. (false)
After this quiz, ask the students ‘Do you think this research is mostly true, mostly false, or a bit of both?
Peer Group Discussions
1. Studies show that the more someone watches porn, the less they enjoy sexual activity with a real person. Do you think pornography can be a good sex educator or have other positive effects on teenagers who watch it? 2. Do you think pornography will help or damage the quality of an intimate relationship? 3. If porn users are more likely to have lower self-esteem, less sexual certainty, and be more depressed – is it helpful for a young person to turn to porn as an outlet when stressed? If not, what would you recommend for those people? 4. Porn users are less likely to be self-controlled in other areas of their lives. What are some common ways your peers struggle with self-control? 5. Do you think society places pressures on girls or guys to be sexy? If so, in what ways? 6. Thinking how dopamine is significant for making mental pathways desires: do you think aggressive, sexist pornography can lead to violence against women? 7. Is non-violent porn an acceptable alternative? 8. Is using pornography a good or poor investment in a teenager’s future? What can you do to ensure your future relationships have the best chance of success?
Bring It Home
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If there is time left over, gather students back from the peer group discussions and ask:
1. Was there anything surprising in today’s lesson? 2. Do you think some of the things discussed today will be easily accepted by students your age? 3. Can you see ways society makes it easier or harder to accept this information? 4. What should we do with this information today?
Optional Vox pop exercise Week 2
Instructions:
Allocate to each of the student peer groups one of the sets of questions below. Ask them to put together a short 2min Vox pop (maximum 3mins) of senior students and teachers, which they should edit using software like Windows Movie Maker (free with Windows) or Apple iMovie (free with Macs). The questions being answered should be printed on the screen. Students should limit their questions to students Year 10 and above. There should be no more than 2 videos per week.
Porn’s effects on people (To show at the beginning of Lesson 3) a. Do you think a sexualised society is a good thing or a bad thing? b. Are there things which teenagers do too much of, which they have no self-control over? c. Do you think pornography is educational?
Porn and Society (To show at the beginning of Lesson 4) a. Are actors more successful if they are sexy? Does this change if you are a women or man? b. Are musicians more successful if they are sexy? Does this change if you are a women or man? c. Do you think using pornography is fine as long as it doesn’t hurt anyone else?
Porn and Relationships (To show at the beginning of Lesson 5) d. What is more important for relationships: being attractive or being romantic? e. What does it mean to be attractive in a relationship? f. Do you think society puts pressure on girls to be sexy?
Social Media (To show at the beginning of Lesson 6) g. How important is it to have a good profile on social media? h. Do you think people exaggerate about themselves on social media? i. Do you think sending or receiving sexual texts is harmless if it is between friends?
Parent Diary
For homework, have students complete Week 2 of the Parent Diary.
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Lesson 3 Porn and Society
Aims and Outcomes
Aims: This lesson describes the reality of pornography ‘industry’, including its profit driven purpose, and highly exploitative nature. Students will see the chasm between the fantasy projected onscreen and that of the lives of the people involved in the production. They will see how pornography’s impact on broader media, including movies, tv, music, and advertising, is significant. And they will see how, at a societal level, pornography-culture places pressure on young people, especially girls, to appear and behave sexually, reducing their value whilst impacting their self-identity.
Outcomes: Students will critically evaluate the ways sexualised media permeates society. They will consider the connection between the private consumer of pornography and the vulnerable people exploited in its production. They will be challenged to question how sexualised media impacts peer attitudes and behaviours, and will think through positive ways they can navigate an increasingly sexualised society.
Background Content
See Lesson 4 in document Background Content for Lessons
Australian Curriculum
HPE Strand: people who are important to them, strategies for relating to and interacting with others, assertive behaviour and standing up for themselves, establishing and managing changing relationships (offline and online), managing the physical, social and emotional changes that occur during puberty, reproduction and sexual health
General Capabilities: Critical and Creative Thinking, Personal and Social Capability, Ethical Understanding Capability, Information and Communication Technology Capability
Way in – feature/activity
• Show the student Vox Pop for Lesson 3. • Watch the following videos, asking the students and critically evaluate some of their messages.
CBN News report on Porn’s effects on society https://www.youtube.com/watch?v=jLn9a2DiBeM
Ask students to note ‘what are some of the concerns raised in this news report about porn’s effect on society?’ and ‘do you think these claims are realistic or overstated’?
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Did you know – Teaching content
Recent studies into how relationships may be affected by pornography have made the following claims:
• It is estimated that the pornography business makes between 6 and 96 billion dollars per year • Pornography performers are not treated like equals in western world workplaces. There is no: health insurance, sick-leave, annual-leave, job redeployment services, job security, minimum wages • Pornography performers are generally exploited and disadvantaged. They display higher rates of: o Depression and anxiety o child sexual abuse o living in poverty o STIs o substance abuse • Performers regularly report doing things against their will. • Porn production and performers have well-documented links with prostitution, which is associated with financial exploitation, human trafficking, and child-sexual abuse. Many women and children who are trafficked and prostituted are used to produce pornography against their will and without consent. • Pornography leaves a permanent record. Even when a performer chooses to leave the ‘industry’, their activities can be found online permanently. This is a form of slavery. • Popular culture is heavily influenced with pornography, where all forms of mainstream media (tv shows, movies, music, literature etc) have adopted sexualised materials previously found only in pornography. • Porn culture changes social behaviour, where exposure to sexualised mass media (movies, advertising, television and magazines) accelerates sexual activity and early first-time intercourse in young people. • Porn culture sexualises young girls. As pornography infiltrates and influences mainstream media, there is clear evidence of the increasing pressure on females to look and behave more sexually. • Pornography increases objectification culture towards women, since the main consumers of pornography are males. Pornography causes a gender power imbalance.
• Pornography contributes to riskier, more aggressive behaviour, and more frequent casual sex. • A population with high rates of porn use sees higher rates of anxiety, depression, insecurity and sexual uncertainty. • It perpetuates widespread risky behaviour, acting out, and relationship breakdown, with lower rates of intimacy and honesty. • It is impossible for the private user to be unconnected to, and not share responsibility for, these outcomes. • Most prostitutes have been involved in porn production without their consent
Ask the students ‘Do you think any of the above claims are true, overstated, or just plain wrong’?
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Note: the Pornography Social Pyramid diagram was designed by the author, M Ballantine-Jones, Copyright 2018. It is an attempt to capture the connection between individual consumption of pornography and various social dimensions. The concepts it includes have not been formally evaluated. but are designed to assist discussion and thinking amongst students.
Peer Group Discussions
1. Consider the Pornography Social Pyramid diagram, and answer: a. What is the main driving force behind the layers of influence from pornography? b. Are any particular people responsible for this driving force? c. How far and for how long might the influence of pornography reach? d. Who are the ‘winners’ and who are the ‘losers’ from pornography? 2. Have you ever felt compelled to act a certain way because it helped you fit in? Describe. Do you think society expects us to fit in with certain sexual behaviours? How? 3. Do you think there is more pressure on women than men to be attractive in: a. Sport b. Hollywood c. TV commercials d. Fashion 4. Do you think messages from the media and across society encourage teenagers to behave sexually at an earlier age? 5. Do you think a lack of sexual appeal or activity can make some teenagers feel like failures? 6. How might a person’s identity be affected when they are pressured to be sexual? 7. What does a person lose when they primarily define themselves by being sexual? 8. Do you think society has a responsibility to protect vulnerable people from sexual exploitation? Do you think Internet Service Providers (ISPs) have a responsibility for the content they allow users to download?
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9. Do you think individual porn users share responsibility for any harm that porn brings to other people? 10. Considering the impact that a sexualised culture might have on young people, what actions could be taken to improve society? Think at a personal level (what might help you), community level (what might help your friends), and global level.
Bring It Home
If there is time left over, gather students back from the peer group discussions and ask:
1. Was there anything surprising in today’s lesson? 2. Do you think some of the things discussed today will be easily accepted by students your age? 3. Can you see ways society makes it easier or harder to accept this information? 4. What should we do with this information today?
Parent Diary
For homework, have students complete Week 3 of the Parent Diary.
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Lesson 4 Porn and Relationships
Aims and Outcomes
Aims: in this lesson students explore the effects of pornography on relationships. They will examine the research on short-term effects, including unrealistic expectations, lack of intimacy, potential physiological harms, gender imbalance, and erectile dysfunction disorder. They will consider some long-term effects, including reduced sexual pleasure, mistrust, higher risk of relationship breakdown, and some potential costs associated with the breakdown of families.
Outcomes: students will be able identify some of negative effects pornography places on relationships. Students will be challenged to consider making wise decisions that benefit their future intimate relationships. Students will be challenged to commit to more respectful behaviours in their current relationships, whether social or romantic.
Background Content
See Lesson 5 in document Background Content for Lessons
Australian Curriculum
HPE Strand: people who are important to them, strategies for relating to and interacting with others, assertive behaviour and standing up for themselves, establishing and managing changing relationships (offline and online), strategies for dealing with relationships when there is an imbalance of power (including seeking help or leaving the relationship), puberty and how the body changes over time, managing the physical, social and emotional changes that occur during puberty, reproduction and sexual health General Capabilities: Critical and Creative Thinking, Personal and Social Capability, Ethical Understanding Capability, Information and Communication Technology Capability
Way in – feature/activity
• Note to teacher: the sexual relationships described in this lesson are inclusive of same sex relationships and same sex sexualities, and the examples in Option 1 and Option 2 below could just as easily apply to same sex partners. • Show the student Vox Pop for Lesson 4. • Option 1. Watch this video https://www.youtube.com/watch?v=cQR4FF6qLBk on how porn ruined a marriage
Ask this question: What are some of the reasons for porn ruining the marriage between Maria and her husband? Answers may include:
1. It meant they had no intimacy. 2. They preferred watching a screen than spending time with each other 3. It made Maria unhealthy because the addiction took away her authenticity • Option 2. Watch the story by an ex-porn star Gemma (BBC Documentary 3mins).
https://www.youtube.com/watch?v=7zvGZJUXvfs
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Ask this question to whole class: ‘why did the retired star not want to continue working?’
Answers may include:
1. Poor pay – paid 300 quid for 12 hours of work (more for ‘anal’ scenes) 2. Didn’t want to end up like the “other” girls who went ‘mad in the head’ 3. Many took drugs to escape and be in ‘another place’ 4. Porn does not reflect real sex, and is not how she would normally do it 5. Parents were unhappy about her doing that work 6. Disturbed about how many young kids watched her movies
Did you know – Teaching content
Refer to Lesson 5 Worksheet, and ask students to fill in the blanks:
Recent studies into how relationships may be affected by pornography have made the following claims:
1. Eight out of ten young women claim that pornography has pressured them ‘to look a certain way’ and ‘to act a certain way. 2. Pornography users are more likely to prefer uncommitted and casual relationships 3. Couples who are both non-users of pornography have higher sexual and relational satisfaction. 4. When one or both partner use porn, they have much lower sexual satisfaction. 5. Studies have found that over 50% of men who are porn addicts experience erectile dysfunction in real relationships. 6. One 2014 survey suggested 56% of divorces were related to ‘obsessive interest in pornographic sites’ 7. A women’s discovery of her partner’s porn use often causes trauma, resulting in lower self- esteem and reduced trust. 8. Porn users are inclined to perceive extra-marital romantic relationships as superior, and therefore seek them out.
Peer Group Discussions
1. What impact do you think being addicted to porn may have on intimacy and romance? 2. What impact do you think being addicted to porn may have on trust? 3. Isn’t having a fantasy a harmless outlet, with no impact on others? 4. What impact do you think a person’s porn addiction may have on their partners self- esteem? 5. Do you think a real sexual relationship is set up to fail if pornography has influenced a person’s expectations? 6. Do you see a contradiction between men watching porn to improve their sex life, and the increase in erectile dysfunction disorder? Why? 7. Why do you think porn-free relationships report higher levels of sexual satisfaction? 8. Considering the impact porn has on the teenage brain, do you think it is fair for a person to be cautious of entering a relationship with a porn-user? 9. Is it worth investing in future relationships by avoiding porn now? What would that mean for you?
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Bring It Home
If there is time left over, gather students back from the peer group discussions and ask:
1. Was there anything surprising in today’s lesson? 2. Do you think some of the things discussed today will be easily accepted by students your age? 3. Can you see ways society makes it easier or harder to accept this information? 4. What should we do with this information today?
Parent Diary
For homework, have students complete Week 4 of the Parent Diary.
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Lessons 5 – 6 Social Media, Sexual behaviour online, and Identity
Aims and Outcomes
Aims: in this lesson students will examine the risks associated with social media, including self- projection behaviours, critiquing how others are portrayed, narcissistic and addictive behaviours, and wellbeing threats. Additionally, risky social and sexualised behaviours including sexting, bullying, and engaging in illegal activities will be discussed.
Outcomes: students will critique there on own social media behaviours, distinguish between superficial and genuine content, and consider healthier, more balanced ways relate with peers and use their time. They will be alert to the risks of sexualised social media behaviours, bullying, trolling, and challenged to protect themselves from exposure to harm and harming others.
Background Content
See Lesson 6 in document Background Content for Lessons
Australian Curriculum
HPE Strand: people who are important to them, strategies for relating to and interacting with others, assertive behaviour and standing up for themselves, establishing and managing changing relationships (offline and online), bullying, harassment, discrimination and violence (including discrimination based on race, gender and sexuality), strategies for dealing with relationships when there is an imbalance of power (including seeking help or leaving the relationship) General Capabilities: Critical and Creative Thinking, Personal and Social Capability, Ethical Understanding Capability, Information and Communication Technology Capability
Way in – feature/activity
• Play the student Vox Pop for Lesson 5. • Watch the Youtube Video https://www.youtube.com/watch?v=LPwR1i-sWpo
Ask: What are some of the strategies social media giants use to hook you in?
Possible answers include:
o Goal to consume as much of your time and conscious attention as possible o Exploiting psychological fragilities o Social Validation Feedback Loop • Optional: ask these general questions to the class: o Do you struggle NOT to look at your phone whenever it is nearby? o How long can you go without thinking about your social media accounts? o How important is it to get a ‘like’ for a good selfie? Is it stressful if a selfie or post doesn’t get ‘liked’? o Do you control your social media use, or does it control you? o Do you trust that social media companies to do the right thing by you?
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Did you know Part 1 – Teaching content
Activity - Who do you think the 2018 top 10 celebrities were on Instagram?
Run through a PowerPoint of the top 10 (according to MarieClaire.Com).
1. Selena Gomez: 133 million followers 2. Cristiano Ronaldo: 121 million followers 3. Ariana Grande: 117 million followers 4. Beyoncé: 111 million followers 5. Kim Kardashian: 108 million followers 6. Taylor Swift: 106 million followers 7. Kylie Jenner: 104 million followers 8. Dwayne "The Rock" Johnson: 100 million followers 9. Justin Bieber: 97.1 million followers 10. Neymar Jr.: 89.7 million followers
Final slide has the full list, which can be left up for the following questions:
• How important is being ‘sexy’ for the popularity of the men in this list? • How important is being ‘sexy’ for the popularity of the women in this list? • Is there a difference, and if so – why? • Do these celebrities have much influence over how a teenager should aspire to be? How? • After posing naked for the cover of GQ Mexico, Kourtney Kardashian said it is “important to expose positive images of our body.” Do you agree? • Do you think normal teenagers communicate a true version of themselves on social media? Do you think teenagers aim to be likeable on social media? • If people prefer to post the best-versions of themselves, what exactly are the followers liking? How many of your friends actually know the real you? • Do you think as a society we are too obsessed with outward appearance? What are some ways individuals could reduce this obsession?
Peer Group Discussions (about 15 mins)
• Rethinking about those top 10 Instagramers for 2018, do you have any celebrities you follow on social media? Each group member can add one to the list. • Why do you think these people are so popular? As a group, come up with the top 5 most descriptive words that summarise their popularity? • If you were an Instagram celebrity, what reasons would you like people to follow you for? Add them to your list. • In the week each of you asked your parents to come up with some words to describe why they love you. As a group, share some of those words, and make a list of 5-6 of the most common words your parents used. • Compare your Instagram list to this list of things your parents used to describe why they love you. Are they the same or different? What does this tell you?
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• If friends liked you only for the same reasons people like celebrities, would you regard them as true friends? • Do you think following other people’s social media lives is helpful to you? • Could young people use their time better than spending time on social media?
Return the groups back to the Class
Class question: Can you think of some more dangerous and harmful risks to using social media and digital communication?
Cyber bullying, illegal transmissions of sexual content, regrettable communication, including naked selfies and images of people without consent
** This is the End of Lesson 5**
Bring It Home
If there is time left over, gather students back from the peer group discussions and ask:
1. Was there anything surprising in today’s lesson? 2. Do you think some of the things discussed today will be easily accepted by students your age? 3. Can you see ways society makes it easier or harder to accept this information? 4. What should we do with this information today?
Parent Diary
For homework, have students complete Week 5 of the Parent Diary.
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Lesson 6 Did You Know Part 2 – Teaching content (About 10 mins)
Topic: Social Media management and The Law.
• Play the student Vox Pop for Lesson 6. • Watch Video Alarmed by the eSafety Office https://www.youtube.com/watch?v=uQxJqbdXw9s
Do you think it is common for people to send things via social media they later regret, including sexting?
What are some of the risks in sending a sext of yourself?
What are some of the risks in sending a sext of someone else?
Did you know that under the Criminal Code Act 1995:
1. It is an offence to use the internet, social media or a telephone to menace, harass or cause offence. 2. Sending or receiving material of someone under 18 or who appears to be under 18 involved in sexual pose or act, or is with someone else who appears to be involved in a sexual pose or act, is an offence. This material can be categorised as an indecent act or child pornography [1]. 3. Any person who then intentionally receives the material , asks for the material, or distributes the material (including resending), has committed the offence of using a carriage service for child pornography material. The maximum penalty is 15 years’ jail.
Case Study
Sexting Case Study: Martin’s story:
Martin is 15, in Year 9. His parents received a knock on the door one evening. It was the police. They asked if they could speak with them and Martin. A parent from the school had complained that Martin had been sending naked pictures of their daughter to friends. At first he denied it, but when the police said they would confiscate his phone for evidence and arrest him, he confessed that a mate had sent him the nude picture of his girlfriend. Martin wanted to share it around for a laugh, but also to boast about his friend’s ‘achievement’ – since Martin himself had never even had a girlfriend.
What crimes have occurred in this story? What should he have done, and what should the police do about this now?
There are potentially a few offences against the Criminal Code Act 1995:
1. Martin has received a nude image of someone under 18, which he did not delete or report, making it intentional. 2. Martin sent the image on to others, meaning he has distributed child pornography. 3. Martin’s friend first received and then sent on the sexual images of the girl, making the friend guilty too. 4. The girl most likely took and sent the original image, meaning she too has been an offender of the Criminal Code Act.
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Bring it Home – Final Wrap Up
Owning Your Future Final Activity – write an Epitaph.
Ask students to project to their old age, where others write an epitaph about them on the event of their death. They should frame the epitaph around these ideas:
• I want to be remembered by the people I love for these reasons: • The skills and achievements I would like to have accomplished in my lifetime include
Then, as a final challenge, they should write a few reflective sentences that answer:
• The activities I need to invest in to ensure this legacy include • The current things in my life that do not contribute to those activities, but which occupy my time, thinking, emotions, and sense of worth include
Follow-up – Dealing with cyberbullying and online concerns
If you are experiencing problems with cyberbullying about you or distribution of pictures/videos of you without your consent, you can take the following steps:
1. Tell the school counsellor or your house master 2. Tell your parents 3. Contact the eSafety Commission through their website at https://www.esafety.gov.au/complaints-and-reporting/cyberbullying-complaints/i-want-to- report-cyberbullying
Note that under Australian Law, the eSafety Commissioner is empowered to force social media providers to take down content of the above nature.
For Further Support in the event of distress
• Kids Helpline 1800 55 1800 | https://kidshelpline.com.au/teens/get-help/webchat- counselling/ • Lifeline 13 11 14 | https://www.lifeline.org.au/get-help/online-services/crisis-chat • Headspace 1800 650 890 | https://eheadspace.org.au/
1. https://www.gotocourt.com.au/legal-news/unthinkable-teens-sexting-can/
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Appendix J: Parental Diary
Week 1 – Overview
1. When you were a teenager, how important was it for your peers to look attractive? 2. When you were a teenager, what sort of access was there to pornography? 3. Was it common for your friends and fellow peers to access, discuss, and share pornography? 4. When you see how sexuality is promoted in the media, movies and tv shows, and popular culture, do you think much has changed since your time? 5. Are you aware of any current statistics around teenagers using social media? 6. Are you aware of any current statistics around teenagers viewing pornography? 7. What advice would you give yourself if you were a teenager living in my world?
Week 2 – How porn effects the user
1. When you were a teenager, what were the types of activities your friends wanted to do most? 2. Can you remember if there were particular activities or interests that you got obsessed about? 3. With the following three questions, be prepared to look through your class notes for answers: a. Are you aware of how the brain works when it comes to regularly repeating exciting activities? b. Are you familiar with parts of the brain called the prefrontal cortex and the limbic system? c. Do you know how dopamine effects the behaviour of these parts of the brain? 4. When you look around, what addictive behaviours do you see people regularly doing? 5. Does it surprise you to hear that the brains of people with addictive behaviours mirror the brains of drug addicts? (Like gambling, over eating, computer gaming, social media, and pornography use) 6. How would you describe what happens over time to the thinking and behaviours of people who view pornography regularly? 7. When it comes to addictive behaviours - what advice would you give yourself if you were a teenager living in my world?
Week 3 – How porn effects society
1. When you were a teenager, did your friends feel their individual actions affected society? 2. Were there any social causes that captivated you when you were my age? What and why? 3. Do you think young people today are more sexualised than your time? 4. Are girls more sexualised today in comparison to your time? 5. Do you think when it comes to viewing pornography, it is just a private matter, or is it a social concern? 6. Do you think if pornography production exploits vulnerable people, the private-user shares responsibility for that exploitation?
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7. Do you think there is a link between the high consumption of aggressive-based pornography and domestic abuse? 8. Do you think there is a relationship between pornography on the changes in sexualised movies, shows, advertising and music? 9. Overall, do you think pornography is helpful or unhelpful for society? Why? 10. Considering how conscience young people of things like recycling and climate change, would you expect young people today to be more vocal against the negative effects pornography has on society?
Week 4 – How porn effects relationships
1. When you were a teenager, was dating common? What was more important to young people: having a long-term romantic relationship, uncommitted casual relationships, or something else? 2. What advice did you get about how to have a successful relationship? 3. Were people back then supportive of uncommitted sexual activity? 4. Do you think a more sexualised culture makes people feel insecure or more confident? 5. Listen to these statements about how pornography affects a sexual relationship, and say if you ‘agree’, ‘disagree’, or are ‘not sure’: a. Regularly using pornography reduces a person’s ability to enjoy real sex b. Pornography puts pressure on women to look and act certain ways c. Intimate relationships that don’t use pornography have better sex lives d. Pornography increases the chance of unfaithfulness e. Pornography reduces trust in a relationship 6. What advice would you give me to maximise my success and happiness in a future relationship?
Week 5 – How social media affects our identities
1. Do you have a social media account? How often will you use it (them)? 2. Can you see some strengths and weaknesses to using social media amongst your friends? 3. Do you think teenagers my age are more obsessed with their self-image than when you were my age? 4. Do you think social media friends are real friends? 5. Who were the top celebrities you admired when you were 15? 6. Do you think celebrities are more idolised today than back then? Do you think following celebrities is helpful? 7. Do you know what the laws are around transmission of underage sexual content? 8. Do you know what proportions of boys and girls currently send or receive sexualised content to each other via social media? (Some information can be found here: https://www.edcomm.org.au/publications/school-pornography-survey-2018/) 9. Take a couple of minutes to consider this last question: can you give me three reasons why you love me.
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Appendix K: New Baseline Instruments
Narcissistic Personality Index NPI-13 [15]
In each of the following pairs of attributes, choose the one that you MOST AGREE with. Mark your answer by writing EITHER A or B in the space provided. Only mark ONE ANSWER for each attitude pair.
1. A I find it easy to manipulate people. B I don’t like it when I find myself manipulating people. 2. A When people compliment me, I get embarrassed. B I know that I am a good person because everybody keeps telling me so. 3. A I like having authority over other people. B I don’t mind following orders. 4. A I insist upon getting the respect that is due me. B I usually get the respect I deserve. 5. A I don’t particularly like to show off my body. B I like to show off my body. 6. A I have a strong will to have power. B Power for its own sake doesn’t interest me. 7. A I expect a great deal from other people. B I like to do things for other people. 8. A My body is nothing special. B I like to look at my body. 9. A Being in authority doesn’t mean much to me. B People always seem to recognise my authority. 10. A I will never be satisfied until I get all that I deserve. B I will take my satisfactions as they come. 11. A I try not to be a show-off. B I will usually show off if I get the chance. 12. A I am a born leader. B Leadership is a quality that takes a long time to develop. 13. A I like to look at myself in the mirror. B I am not particularly interested in looking at myself in the mirror.
Social Media Survey Items (taken from Moon [8] and Ong [11])
14. I got my first social media account at age: (Don’t have one, 5–17) 15. My most used social media account is (Don’t have one, Instagram, Snap Chat, Facebook, Twitter, Other) 16. How often per week would you update your profile picture (Less than 1, 1–9, 10 or more) 17. How often per week would you post a selfie (Less than 1, 1–9, 10 or more)
How would you rate your appearance in your last selfie post:
18. Attractive (7-point Likert scale) 19. Fashionable (7-point Likert scale) 20. Cool (7-point Likert scale) 21. How much time do you spend a day on your account? (in minutes)
Followers:
22. Number of followers 23. Number of people you follow
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Appendix L: Comparison between and DSM-5 Gambling Disorder Criteria and Compulsivity Scale
DSM-5 Internet Gaming Disorder [5] Compulsivity Scales (CPUI-9) [6]
1. Needs to gamble with increasing Q3. Even when I do not want to view amounts of money in order to achieve pornography online, I feel drawn to it. the desired excitement.
2. Is restless or irritable when attempting Q3. Even when I do not want to view to cut down or stop gambling. pornography online, I feel drawn to it. 3. Has made repeated unsuccessful efforts Q1. I believe I am addicted to Internet to control, cut back, or stop gambling. pornography.
Q2. I feel unable to stop my use of online pornography.
*Post-intervention correlation between Compulsivity and Efforts to Reduce Viewing (β = 0.2, t = 2.84, p = 0.01).
4. Is often preoccupied with gambling (e.g., Q5. I have refused to go out with friends or having persistent thoughts of reliving attend certain social functions to have the past gambling experiences, opportunity to view pornography. handicapping or planning the next venture, thinking of ways to get money with which to gamble). 5. Often gambles when feeling distressed *Post-intervention correlation between (e.g., helpless, guilty, anxious, Compulsivity and Distress (β = 0.58, t = 11.67, depressed). p = 0.00).
6. After losing money gambling, often returns another day to get even (“chasing” one’s losses). 7. Lies to conceal the extent of involvement Q4. At times, I try to arrange my schedule so with gambling. that I will be able to be alone in order to view. 8. Has jeopardised or lost a significant Q6. I have put off important priorities to view relationship, job, or educational or pornography. career opportunity because of gambling. 9. Relies on others to provide money to relieve desperate financial situations caused by gambling.
Note: *Additional study results demonstrating similarities with DSM-5 Gambling disorder criteria
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