Bullying in New Zealand
Incidence of Bullying and Victimisation among Adolescents in New Zealand
Moja Kljakovic, Caroline Hunt University of Sydney, Australia Paul E. Jose Victoria University of Wellington, New Zealand
It has been established that bullying and victimisation have negative rates of involvement for both boys and outcomes for those involved. However, this problem has received little girls were reported from Lithuania research attention in New Zealand samples, particularly with longitudinal (Craig et al., 2009). designs. The incidence of four types bullying was assessed in a large Prevalence data based on large adolescent New Zealand sample including; traditional bullying inside the samples of school students have school, bullying outside the school, bullying via text message and bullying reported consistent rates of bullying via the internet. The same categorisation of victimisation was also assessed. and victimisation, despite the use of The overall rates of bullying and victimisation appeared elevated relative to different response options. Nansel, international samples but traditional school-based bullying was more frequent Overpeck, Pilla, Ruan, Simons-Morton than text or internet bullying. No gender differences were found. Differences & Scheidt (2001) surveyed 11-16 year for ethnic group differences were found only for specific types of bullying, old students in the US (N=15,686) and with Māori students reporting more traditional school and text bullying, and found that in the past school term 8.8% more text-based victimisation than other ethnic groups. of students reporting bullying others at least ‘once a week’, 10.6% reported Keywords: bullying, victimization, New Zealand, adolescents bullying others ‘sometimes’ and 25% reported bullying others ‘once or twice’. In terms of victimisation, 8.4% of students reported being victimised at Bullying and victimisation are aged 11, 13 and 15 years in 40 countries least ‘once a week’, 8.5% reported being highly prevalent among young people, worldwide (N = 202,056). New bullied by others ‘sometimes’ and 24.2% and both bullies and victims exhibit Zealand did not take part in this survey. reported being bullied by others ‘once negative outcomes (Stassen Berger, Respondents were asked how often they or twice’. Fleming and Jacobsen (2009) 2007). Adolescents are greatly involved had bullied others or had been bullied by used the Global School-based Student in bullying and experience particularly others in the past two months. Response Health Survey (GSHS) to explore the adverse outcomes in comparison with options included ‘never’, ‘once or prevalence of victimization of 13-15 children (Kim & Leventhal, 2008; twice’, ‘2 or 3 times a month’, ‘about year olds from 19 low-middle income Simon-Davies, 2011). Furthermore once a week’, or ‘several times a week’. countries (N=104,614). They found that bullying phenomena are under- Those who reported being bullied at 34.2% of respondents reported being researched in New Zealand samples. least ‘2 or 3 times a month’ and did not victimised on at least one day in the This paper aims to describe the nature report bullying others at least ‘2 or 3 past month. Of that group, 55.6% had of bullying and victimisation in a large times a month’ were considered victims. been victimized 1 or 2 days and 19.7% sample of New Zealand adolescents Those who reported bullying others at had been victimised 3–5 days in the and compare the findings to results least ‘2 or 3 times a month’ and did not past month. Similar results were found from international samples. Four types report being victimized by others at least in Venezuela with 37.0% of males and of bullying will be assessed: traditional ‘2 or 3 times a month’ were considered 27.0% of female adolescents reported bullying inside the school, traditional bullied. If individuals reported being having been the victims of bullying bullying outside the school, cyber both bullied and victimised ‘2 or 3 times at least once within the past 30 days bullying via text message and cyber a month’ or more they were classified (Muula, Herring, Siziya & Rudatsikira, bullying via the internet. The same as bully/victims. Collectively, 10.7 % 2009). four types of victimisation will also be of the sample reported bullying others, assessed. 12.6 % were victims and 3.6 % were When broader definitions are bully/victims. The prevalence of being used, prevalence rates are higher. For An indication of the world-wide example, in a sample of 25 schools prevalence of bullying and victimisation involved in bullying (as a bully, victim or bully/victim) varied greatly between from around the UK that included 4700 can be drawn from a number of large children, 75% reported being victims community-based studies. For example, the countries surveyed with estimates ranging from 8.6% to 45.2% in boys, of bullying at some stage during the Craig et al. (2009) used the Health school year (Glover, Gough, Johnson, Behaviour in School-aged Children and 4.8% to 35.8% in girls (Craig et al., 2009). The lowest rates of involvement & Cartwright, 2000). Collectively, (HBSC) survey to measure self-reported these studies illustrate that the period bullying and victimisation in children in bullying for both boys and girls were reported from Sweden, and the highest over which bullying is measured affects
New Zealand Journal of Psychology Vol. 44 No. 2, September 2015 • 57 • M. Kljakovic, C. Hunt, P. E. Jose the number of students who report They also showed that victimisation rates of cyber victimisation. However, being bullied. However, it is also clear consistently declined over time after boys tended to cyber bully more than from these studies that bullying is a this peak, an effect that appears to be girls, girls were more often victims of distressingly common phenomenon consistent worldwide. Again using email bullying than boys, and boys were amongst adolescent samples. data from the Health Behaviour in more likely to bully via text message School-aged Children (HBSC) study, than girls. Different Types of Bullying and victimisation was found to decrease Victimisation across the 11 to15 year span across 28 Incidence by Ethnicity Another factor that affects the countries (Due et al., 2005). Bullying research often indicates reported rates of bullying is the different Not only does bullying decrease that there are differences between the types of bullying behaviours that are with age, it also appears to be decreasing rates of bullying and victimisation by measured. For example, Seals and over time. Molcho et al. (2009) looked different ethnic groups within the same Young (2003) looked at the prevalence at prevalence trends for rates of bullying country. For example, within North of physical bullying, threats of harm, in over 20 countries. They found that American communities, Hispanic name calling, mean teasing and in general, bullying has decreased over adolescents appear to bully others more exclusion as different measures of time from 1993 to 2006. frequently than African American or bullying. Respondents were asked to Caucasian individuals (Nansel et al., report whether these occurred ‘never’, Incidence by Gender 2001). African American adolescents ‘sometimes’ or ‘often’ in the past Rates of bullying and victimisation are significantly less victimised than school year. Name calling was the also appear to differ by gender. Generally, Hispanic or Caucasian adolescents most common form of bullying with traditional bullying appears to be (Nansel et al., 2001; Spriggs, Iannotti, 36.7% of respondents reporting that more common in male samples than Nansel & Haynie, 2007). Additionally, this happened to them ‘sometimes’ and female samples (Barboza, Schiamberg, Spriggs et al. (2007) found that for 13.5% reporting that it happened ‘often’. Oehmke, Korzeniewski, Post & Heraux, Caucasian and Hispanic students, school Another way that the incidence of 2009; Li, 2006). It is also often found satisfaction and school performance bullying can vary is the means through that although bullies are most often were negatively associated with which it occurs. For example, cyber boys, both males and females tend to bullying and victimisation; whereas, bullying (i.e., bullying via the internet, be victims (Rodkin & Berger, 2008). school factors were unrelated to phone or other electronic media) appears However, some argue that this difference bullying or victimisation for African to differ in certain ways from traditional may be due to the fact that males engage American students. Conversely, Seals forms of face-to-face bullying. Data in more obvious, physical aggression and Young (2003) have found no from the 2005/2006 Health Behaviour whereas females engage in relational differences between rates of bullying in School aged Children (HBSC) survey aggression, which is less observable and victimisation of African American showed that 20.8% of the adolescents (Craig, 1998; Olweus, 1991). and Caucasian students. However, there were significant differences between the surveyed reported that they had bullied Research pertaining to the gender samples of Seals and Young’s (2003) and others at least once in the last 2 months differences in rates of cyber bullying is Nansel et al. (2001) which may account physically, 53.6% using verbal bullying, still in its infancy; however, it appears to for the observed differences. Seals 51.4% using relational, and 13.6% yield a different pattern to that observed and Young’s (2003) sample was much using cyber methods (Wang, Iannotti & in traditional bullying and victimisation. smaller (N = 454) than that of Nansel Nansel, 2009). Some evidence indicates cyber bullying et al. (2001; N = 15,686), Nansel et al. is more prevalent amongst males (Li, (2001) achieved an 83% participation Bullying Incidence by Age 2006; Wang et al., 2009); whereas, some result as opposed to 40% (Seals & evidence suggests it is equally likely in Despite these difficulties with the Young, 2003). Seals and Young’s (2003) both genders (Beckman, Hagquist & measurement, age trends show a clear sample was primarily comprised of Hellström, 2013). Cyber victimisation pattern with bullying and victimisation African American individuals (79%) on the other hand, generally appears most common in late childhood, peaking and although Nansel et al. (2001) to be more prevalent amongst females at approximately 12 years of age with oversampled both African American and (Beckman et al., 2013; Kowalksi & the transition to high school, and then Hispanic individuals in their sample, it is Limber, 2007; Wang et al., 2009). declining thereafter. For example, unclear from their study exactly how the Pelligrini and Long (2002) examined the Gender differences in cyber sample was distributed. Despite these transition period from primary school to bullying and victimisation may become observations, it is unclear whether it is high school using a sample of 11 to14 more evident when different media minority status, socio-economic status year olds, and they confirmed that rates (e.g., text message, email, chat room, or some other factor relating to ethnicity of bullying increased with the transition etc.) are explored. Slonje and Smith that is causing these differences. between schools and then decreased (2008) explored the nature of different A number of studies in the U.S. thereafter. They reasoned that this peak types of cyber bullying in a sample of have found a higher prevalence occurred at this time due to a desire adolescents (mean age 15.3 years) in of victimisation in Asian students to establish social dominance in high Sweden. Overall, it appeared that there compared to ethnic majority students school among a new cohort of peers. were few gender differences between
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(Juvonen, Graham & Schuster, 2003; The New Zealand Context In a sample (N = 821) encompassing Mouttapa, Valenta, Gallaher, Rohrbach The international literature shows 15-16 year olds from 107 New Zealand & Unger, 2004; Zhou, Peverly, Xin, that bullying and victimisation are schools (approximately a quarter of the Huang & Wang, 2003). However, it universally experienced, although the schools in New Zealand at the time), is unclear whether Asian students in rates may differ according to factors Nairn and Smith (2002) found that 45% these cases are victims because of their such as country, gender, domain of of the sample reported having ever been ethnicity per se or because of ethnic bullying and ethnicity. It is important bullied at their current school. Of those minority status, or again because of to understand these factors more fully bullied, 31% reported being bullied some other factor. in New Zealand, and thereby help to sometimes and 12% reported being Further research alludes that in ascertain the risk and protective factors bullied often (Nairn & Smith, 2002). some cases it may be minority status specific to bullying in this country. Using a more selective cut off, Deny that plays a role in different rates of Some (e.g., Petrie, 2012) have et al. (2014) examined the prevalence of bullying and victimisation observed claimed that New Zealand has some bullying and victimisation, once a week between different ethnic groups. For of the highest rates of bullying in or more over the past year, in the 2007 example, in a sample of adolescents the developed world. However, as cohort of the Youth2000 survey series. from the Netherlands, Vervoort, Scholte outlined above, varying measurement This comprised 9107 adolescents from and Overbeek (2010) found that, after of bullying may account for differences 96 high-schools across New Zealand. Of controlling for the ethnic composition in reported rates of bullying. For the sample, 6.1% of students reported of school class, non-Western ethnic example, New Zealand studies tend to being victims of bullying once a week or minorities were victimised less and they measure any experience of having been more, and 5% reported bullying others did not differ from the ethnic majority bullied during the past year, whereas once a week or more. in their rates of peer reported bullying. many other studies require a more In regard to bullying via text Ethnic composition of the school classes frequent experience of bullying to meet message only, Raskauskas (2010) appeared to moderate the relationship criteria, which will inevitably result in reported that 43% of their sample had between ethnicity and bullying in that a lower percentage reported. Within experienced at least one incident of ethnic minorities appeared to bully New Zealand, Carroll-Lind and Kearney text-bullying, with 23% of the sample more in ethnically diverse classes. (2004) found that 63% of their sample experiencing this form of bullying more Australian and British research indicates (N = 1480) reported being bullied at frequently. The majority of victims that children are most likely to be the some stage in the past school year and of text-bullying also reported to be victims of bullying from those in their of those bullied, 8% were bullied ‘about victims of traditional bullying. Students own ethnic group as opposed to those once a week’. However, this study who were victims of both text message outside of it (Nguy & Hunt, 2004; Eslea included both children and adolescents. and traditional bullying reported more & Mukhtar, 2000). Using a sample of 2066 New depressive symptoms than those who Other factors, such as measurement Zealand adolescents, Adair, Dixon, experienced traditional bullying only tools and level of assimilation may also Moore and Sutherland (2000) used two and those not involved in bullying. play a role in the relationship between measures to ascertain the incidence Two large birth cohort studies exist bullying and victimisation within ethnic of bullying behaviours. They found that have explored factors relating to minority groups. For example, Sawyer, that 58% of the sample reported being bullying and victimisation in New Bradshaw and O’Brennan (2008) found bullied in the past year according to Zealand samples. Gibb, Horwood that higher rates of victimisation were the participants’ own definitions of the and Fergusson (2011) followed a birth reported by ethnic minorities when a phenomena; whereas, 75% reported cohort from birth to 30 years of age in behaviour-based measure was used as having been a victim of at least one Christchurch, New Zealand. Gibb et al. opposed to a definition-based measure. of the listed bullying behaviours. (2011) found that those who bullied or Yu, Huang, Schwalberg, Overpeck and Additionally, 44% reported being were victims at any time between the Kogan (2003) showed that children who perpetrators of bullying in the past year ages of 7 and 15 years had higher rates spoke languages other than English according to their own definition. of later self-reported mental health at home were at a greater risk of In a more recent online survey, difficulties and adjustment problems at being victims of bullying than their similar prevalence statistics were found 16-30 years of age. Caspi et al. (2002) solely English speaking peers. They (Marsh, McGee, Nada-Raja & Williams, looked at genetic factors relating to attributed this difference to levels of 2010). Of 1169 15-year-old students, aggression in male participants involved assimilation of immigrants based on 47% reported having been bullied in the Dunedin multidisciplinary study, the degree to which English was spoken sometimes or often. Eleven percent of a birth cohort that continues to follow at home. They also considered the role this sample also reported being victims individuals born in Dunedin, between of psychosocial, school, or parental of text bullying, and those involved 1972 and 1973. They found that boys risk factors and found that those who in text bullying (either as a bully or a in this sample who had low monoamine speak languages other than English are victim) were significantly more likely oxidase A (MAO-A) due to a specific at increased risk of feeling vulnerable, to be involved in other, non-text forms genetic allele in combination with low excluded and lacking confidence (Yu et of bullying (Marsh, et al., 2010). nurturance were at increased risk of al., 2003). being bullies or aggressive-victims.
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Sixty percent of this group had been cyber and traditional forms of bullying Participants convicted for violent offence by the age and victimisation. In year one (2006), 2,174 of 26 whereas only 4% of boys with low participants were recruited from 78 MAO-A and high parental nurturance Method schools throughout the North Island of suffered the same fate. Thus it appears The current study involved the use New Zealand. A roughly equal number that the children’s home environment of males and females were obtained for influenced whether this gene would of data from the Youth Connectedness Project (YCP). The YCP used a mixed- the sample (52% females, 48% males). be expressed as aggressive tendencies Participants attended schools from a or not. method, cross-lagged longitudinal design, involving the collection of number of geographical areas in the Coggana, Bennett, Hooper and quantitative and qualitative data from North Island, including Wellington, Dickinson (2003) also explore the three cohorts of youth starting at ages Kapiti Coast, Wairarapa, Horowhenua, outcomes of bullying and victimisation 10, 12, and 14, over three successive Taranaki, Hawke’s Bay, and Auckland. in a New Zealand sample. Their cross years. Ethical approval for the project By the third point of measurement, due sectional study looked at the effects was granted by the Victoria University to attrition, the number of participants of chronic bullying on over 3000 of Wellington Human Ethics Committee. had dropped to 1,774. Data analyses adolescents in New Zealand. They Readers can obtain further information were conducted on individuals who reported that victims had lower self- about the YCP from http://www.vuw. participated in the survey at all three time esteem, suffered more from depression, ac.nz/youthconnectedness/ index.aspx. points. A previous statistical analysis stress and hopelessness, and were more comparing those who participated at likely to think about and attempt self- Measures and Procedure all three time points with those who harm and suicide than non-victims. Students were administered self- had dropped out revealed that the latter Given that prevalence estimates report surveys on lap-top computers group reported significantly lower of bullying and victimisation vary at each of the three time points. The levels of future orientation and life between different New Zealand samples survey included 369 questions in total; satisfaction at T1 than those individuals and different ethnicities, and have however, students rarely had to answer who had completed all three time points been based on varying definitions and all of them due to branching and (Jose, Ryan & Pryor, 2012). Males and measurement periods, it is important skipping within the survey. Eleven items students from lower decile schools were to further investigate the extent of the asked about the frequency of bullying also less likely to complete all three time problem in New Zealand. While there and victimization in the previous month points (Jose et al., 2012). A school’s is a growing international literature and were preceded by the following decile rating gives an indication of the on the correlates of involvement in definition of bullying: “Bullying proportion of its students who reside bullying, New Zealand has a unique includes any behaviour that is done to in low socio-economic communities. multicultural society that differs from try and hurt another person’s feelings or According to the New Zealand Ministry other countries on a number of factors body.” Bullying and victimisation items of Education, “Decile 1 schools are (Ward & Masgoret, 2008). As such, were measured on a 5-point Likert scale. the 10% of schools with the highest bullying and victimisation may present Response options were: Never (1), 1 to proportion of students from low socio- differently. It is clear that bullying and 3 times (2), 4 to 6 times (3), 7 or more economic communities, whereas decile victimisation have negative outcomes times (4), and Almost daily/daily (5). 10 schools are the 10% of schools with for New Zealanders (Coggana et al., The bullying items are reproduced in the lowest proportion of these students” 2003; Gibb et al., 2011) and the first step Appendix 1. (Ministry of Education, 2014). in developing interventions is to clarify When asked about ethnicity, students the nature of the phenomena so that it were provided with the following Statistical Analyses can be effectively targeted. As such, definition “Every person is part of an The data were analysed using SPSS the present study aimed to determine ethnic group, sometimes two or more 18.0. An analysis of variance (ANOVA) the current state of bullying and ethnic groups. Some names of ethnic was conducted to determine the size and victimisation in terms of prevalence, and groups are: Samoan, Chinese, Māori, significance of group differences. For the effects of age, gender, ethnicity and Tongan, New Zealand European.” the group comparisons, bullying and type of bullying in a large representative Students were then asked to indicate victimisation mean item scores were sample of New Zealand adolescents. the ethnic group or groups (“tick all treated as continuous variables. To address the aforementioned that apply”) to which they belonged. A purposeful overrepresentation of Māori issues, rates of bullying and victimisation Results in this New Zealand sample were participants was effected in this sample. compared to international samples and The aim of this was to obtain a sufficient Students came from schools that differing measurement approaches number of Māori participants so that this represented the entire range of school were considered when interpreting group could be examined in detail in deciles (range 1 to 10). The average the results. Age, ethnicity and gender future analyses of the YCP data. school decile in the present study was patterns were considered and compared 5.2, which approximated the average to international samples where possible. for the entire country. In the first This study also uniquely explored both year, 52% of respondents identified
• 60 • New Zealand Journal of Psychology Vol. 44 No. 2, September 2015 Bullying in New Zealand as European New Zealanders, 30% as any experience of victimization or item scores averaged across the three Māori (compared to 15% by census, involvement in bullying. Figure 1 and time points. Figure 3 illustrates that Statistics New Zealand, 2010), and 20% Figure 2 illustrate that bullying and bullying via text message (M = 1.43, as Other; this latter group primarily victimisation appeared to be highest in 95% CI [1.39, 1.46] appears to be the included Pacific Islanders (12%) as well the 12-14 year cohort and then appeared most common form of bullying followed as people who identified as Chinese, to decrease with age. by in-school bullying (M = 1.40, 95% Indian, other European, American, Figure 1: Rates of bullying by age across the three cohorts African, and a host of other ethnicities.
Bullying and Victimisation Total bullying scores were based on the following questions: ‘in the last month how often have you bullied other students’ (bullying inside school), ‘in the last month how often have you bullied young people who do not go to your school/kura’ (bullying outside of school), ‘in the last month how often have you sent a mean text message to someone’ (text bullying) and ‘in the last month how often have you bullied others online’ (internet bullying). At time one (T1), just over a quarter of the sample reported that they had bullied others using some form of bullying (27%, 95% Figure 2: Average rates of victimisation by age across the three cohorts CI [25%, 29%] and that this behaviour appeared to decrease at T2 (20%) and at T3 (19%). This range of values is significantly larger than the predicted prevalence rate, 10.7%, based on Craig et al.’s (2009) findings, so Hypothesis 1 was not supported. Like bullying scores, total victimisation scores were based on four victimisation questions (see Appendix A). Approximately one third of the sample were self-reported victims at T1 (35%, 95% CI [33%, 37%] and as with bullying, victimisation appeared to decrease at T2 (25%) and T3 (22%). CI [1.38, 1.43], outside of school Table 1. Rates of bullying and victimisation in the sample bullying (M = 1.20, 95% CI [1.18, Total bullying Total victimisation 1.22] and bullying via the internet (M = 0.98, 95% CI [0.95, 1.00]. In terms T1 T2 T3 T1 T2 T3 of rates of victimization, in-school Never 73.4% 80.1% 80.6% 65.1% 74.9% 78.0% victimisation (M = 1.61, 95% CI [1.58, 1.65] appears to be the most common 1-3 times 18.6% 14.3% 15.0% 23.8% 18.0% 16.3% form followed by victimization via 4-6 times 3.3% 2.3% 1.9% 5.0% 3.4% 2.8% text message (M =1.44, 95% CI [1.40, 7 or more times 2.4% 1.6% 1.1% 3.0% 1.7% 1.3% 1.47], victimization outside of school Daily/almost daily 2.3% 1.8% 1.4% 3.1% 2.1% 1.7% (M = 1.26, 95% CI [1.24, 1.28] and Any bullying 26.6% 19.9% 19.4% 34.9% 25.1% 22.0% internet victimization (M = 0.99, 95% CI [0.96, 1.01].
Gender Age Types of Bullying or Victimisation Mean item scores were used to Rates of bullying across different determine whether there were differences Comparisons between the different age groups were represented by the in types of bullying by gender. Bullying percentage of participants who reported types of bullying were based on mean
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Figure 3: Frequency of bullying and victimisation by type Ethnicity An ANOVA analysis revealed that overall there were no significant differences between the three ethnic categories in relation to average rates of bullying (F(2, 1540) = 1.569, p = 0.21). The mean rate of bullying for the NZ European sample was 1.03 (SD = 0.62), Māori was 1.08 (SD = 0.65) and Other was 1.09 (SD = .65). The analysis also confirmed that overall there were no significant differences between the three ethnic categories in relation to average rates of victimisation (F(2, 1540) = 2.071, p = 0.13). The mean rate of victimisation for the NZ European sample was 1.07 (SD = 0.65), Māori and victimisation rates were averaged hand, no significant differences were was 1.14 (SD = 0.69) and Other was across the three time points. ‘Total’ found in the rates of text (F(1) = 0.816, 1.14 (SD = .70). scores indicate the average of the four p = 0.37) or internet (F(1) = 2.240, p Figure 4 illustrates the average different types. = 0.14) bullying between males and scores for the different types of bullying Tables 2 and 3 illustrate the mean females. amongst the three ethnic categories. scores for each form of bullying and In regard to victimisation, no ANOVA revealed that there were victimisation by male and female significant difference was identified significant differences between the three participants. A significant difference between males and females on total ethnic categories in relation to average between males and females on total rates rates of victimisation, F(1, 1544) rates of bullying inside the school (F(2) of bullying was found in an ANOVA = 2.630, p = 0.11). Nevertheless, = 22.26, p < 0.001), bullying outside of analysis, F(1, 1544) = 3.816, p = 0.05). males were victimised significantly school (F(2) = 24.10, p < 0.001) and Some gender differences were noted more than females inside the school bullying via text message (F(2) = 26.69, for particular types of bullying. In environment, (F(1) = 5.929, p = 0.02). p < 0.001). Across each of these three particular, the ANOVA revealed that But no significant gender differences types of bullying, those who identified males engaged in significantly more were found in the rates of victimisation as Māori engaged in the highest average bullying inside school than females, outside of school (F(1) = 0.766, p= rate of bullying, followed by those F(1, 1771) = 18.845, p < 0.001), and 0.38), text victimisation (F(1) = 0.765, who identified as “other” and lastly by males also engaged in significantly more p= 0.38), or internet victimisation (F(1) those who identified as New Zealand bullying outside school than females = 0.441, p= 0.51). European. These differences remained (F(1) = 4.835, p = 0.03). On the other when school decile was included as a covariate. There was no significant Table 2. Average rates of bullying by gender and type of bullying difference between the three ethnic categories in the average rates of internet Male Female Total bullying (F(2) = 0.142, p = 0.87). Mean SD Mean SD Mean SD Figure 5 indicates that overall School bullying 1.47 0.00 1.35 0.00 1.41 0.00 there was little variability in the rates Bullying outside of school 1.22 0.46 1.18 0.38 1.20 0.42 of victimisation between the three Text bullying 1.41 0.84 1.44 0.79 1.43 0.81 ethnic categories. An ANOVA analysis revealed a significant difference between Internet bullying 1.00 0.59 0.96 0.51 0.98 0.55 the average ratings of victimisation via Total bullying 1.09 0.63 1.02 0.64 1.05 0.63 text message (F(2) = 14.736, p<0.001). Those who identify as Māori were victimised most, followed by those who Table 3. Average rates of victimisation by gender and type of victimisation identified as “other”, and those who Male Female Total identified as New Zealand European Mean SD Mean SD Mean SD were victimised least. Again, these School victimisation 1.66 0.76 1.57 0.72 1.61 0.74 differences remained when school decile was included as a covariate. Victimisation outside of school 1.27 0.53 1.25 0.44 1.26 0.48 There were no significant differences Text victimisation 1.42 0.81 1.45 0.74 1.44 0.78 in the rates of victimisation between Internet victimisation 1.00 0.59 0.98 0.54 0.99 0.56 the three ethnic categories in terms of Total victimisation 1.13 0.65 1.08 0.68 1.10 0.67 victimisation inside the school (F(2) =
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Figure 4: Mean frequencies of different types of bullying by three ethnic (as a bully, a victim or a bully-victim) categories for each gender by country. As such it is difficult to compare New Zealand to other countries of similar size or demographic to assess whether in fact bullying rates are unexpectedly high. However, setting aside the measurement differences between the two surveys, New Zealand appears to have higher rates of bullying involvement relative to Northern and Western European countries (range 4.8 to 27.1%), but lower rates than Eastern European countries (range 8.9 to 45.2%). Reported victimisation in the current sample appears to be elevated relative to the international data. The Figure 5: Average frequencies of different types of victimisation by three ethnic rate of reported victimisation of our categories sample in year one (34.9%) is very similar to that reported by Fleming and Jacobsen (2009; 34.2%) using the Global School-based Student Health Survey (GSHS), however, both of these figures are high in comparison to other international research (Craig et al., 2009; 12.6%). Fleming and Jacobsen (2009) used a very similar indicator of victimisation to the current study (self-reported victimisation on at least one day in the past month) but employed samples from lower to middle income countries. Since New Zealand is a high-income country, it is possible that the different rates of victimisation could be influenced by 0.043, p =0.958), victimisation outside In our sample, the average rate of the difference in socioeconomic status. of school (F(2) = 2.902, p = 0.055), or reported engagement in bullying for Although rates of bullying and internet victimisation (F(2) = 0.449, p year one (26.5%), was more than double victimisation appear to be high in = 0.639). the average rate of bullying (10.7%) this sample in comparison with other reported by Craig et al. (2009) from countries worldwide, it is unclear why the Health Behaviour in School-aged this might be the case. The reasons Discussion Children (HBSC) study. Although the behind these differences require A growing international literature rate in our New Zealand sample was further delineation so that intervention demonstrates that the experience of higher than that reported by Craig et al. programmes can be appropriately bullying is a common problem, with (2009), these rates might be comparable adapted for the New Zealand context. incidences varying in regards to a when the differing inclusion criteria For example, comparing the intervention number of factors, including age, between the two studies are considered. programmes or policies pertaining to gender, ethnicity and bullying type. Craig et al. (2009) only classified bullying in the countries surveyed may The present study adds to this body individuals as bullies if they were also account for some of the difference in of literature through its focus on the not victims and if they bullied others prevalence rates. correlates of bullying and victimisation at least twice per month, whereas; Although many studies differentiate amongst New Zealand adolescents. This inclusion criteria for the present study between cyberbullying and traditional study’s findings are largely comparable included individuals who bullied at bullying, few explore the subtypes to international data; however, some least once per month, regardless of of cyberbullying such as bullying key differences emerged, including the their victim status. Unfortunately, Craig over the internet or bullying via text prevalence of traditional victimisation, et al. do not identify the mean rates of messaging. The use of this distinction the prevalence and nature of different bullying specifically by each country in the present data highlighted some forms of cyber aggression, and the rates surveyed. Instead, they give the rates important differences from previous of bullying in regard to this ethnically of involvement in any form of bullying New Zealand research in several unique sample in New Zealand.
New Zealand Journal of Psychology Vol. 44 No. 2, September 2015 • 63 • M. Kljakovic, C. Hunt, P. E. Jose regards. In the current sample, reported victimisation, which differs from the U.S. (Nansel et al., 2001; Seals engagement in bullying with text previous literature in which females &Young, 2003; Spriggs et al., 2007), messaging was the most popular means are more likely to be cyber victims for example, Caucasian Americans with of bullying, followed by bullying inside than males (Beckman et al., 2013; Hispanic Americans. It is possible that school, bullying outside of school, and Kowalksi & Limber, 2007; Wang et al., marginalised ethnic minorities such as lastly, internet bullying. Although both 2009). When different forms of cyber Hispanic youth in the U.S. and Māori Wang et al. (2009) and Li (2006) found victimisation are explored, the pattern youth in New Zealand share sufficient that traditional bullying was more is slightly different. Where the current commonalities to allow a comparison, common than cyberbullying, they did study found no gender differences in but at this juncture insufficient data has not differentiate between different forms text messaging or email victimization, been collected worldwide to permit such of cyber aggression. Slonje and Smith (2008) found that analyses. In other countries, traditional females were more often victims of New Zealand is unique in that victimisation has been reported to be email bullying (but had similar levels of it is a multicultural society with a more common than cyber victimisation text message victimisation) than males. high percentage of recent immigrants (Li, 2006). However, in the present It should be pointed out, however, that (i.e., one in five New Zealanders study, in-school victimisation was Slonje and Smith’s (2008) measure of were born overseas; Department of the most common form followed email bullying differed from the present Labour, 2009). It has a bicultural by text victimisation, victimisation broader measure of internet bullying, history, formed with the signing of the outside of school, and lastly internet and hence, this discrepancy may explain treaty of Waitangi between the British victimisation. Few previous studies the difference. immigrants and Māori natives in 1840 have differentiated between the different Māori individuals were purposefully (Lyons, Madden, Chamberlain, & types of cyber victimisation, which oversampled in this sample such that Carr, 2011). European immigrants may explain the unique findings in our there were large enough numbers so that have been the majority cultural group sample. We suggest that it is important bullying and victimisation rates amongst in New Zealand since the mid-1850s, to distinguish among different forms of this group could be effectively assessed. however, most New Zealanders strongly cyber aggression because they seem to When the rates of the four different endorse multiculturalism and the divide occur at different rates, and they may types of bullying and victimisation between cultural groups within New also have differential outcomes. were averaged, no differences were Zealand is less than in other Western In regard to gender and age trends found between Māori individuals, New countries (Ward & Masgoret, 2008). in bullying and victimisation, the Zealand European participants, and If there is a small divide between current sample appears to follow similar those categorised as ‘Other’ ethnicity. cultural groups within New Zealand, the patterns to those reported in other New However, differences between ethnic observed inter-ethnic group differences Zealand samples and other countries. groups were noted when the subtypes must exist for some other reason such In line with other research (Due et al., of bullying and victimisation were as discrepancy in privilege between 2005; Pelligrini & Long, 2002), bullying considered. In regard to bullying others, different ethnic groups or some other and victimisation decreased with age Māori individuals reported engaging in factor or combination of factors. The after the transition to high school. more bullying inside school, outside effects remain when accounting for Also in line with previous research, school, and text bullying than New school decile, therefore, socio-economic traditional bullying was more common Zealand Europeans or ‘other’ ethnicities. status may not be the explaining factor; in males than females (Barboza et al., No differences were found in the however, this measure may not be 2009; Li, 2006). In-school victimisation rates of internet bullying. In regard sensitive enough to fully account for was also more common in males than to victimisation, Māori individuals the complexity of socio-economic females, but there were no differences reported more text victimisation than disparity. As with much of the previous between the genders for victimisation ‘Others’ or New Zealand Europeans. literature pertaining to ethnicity and outside of school. No other differences across the ethnic bullying (Nansel et al., 2001; Seals & groups in rates of victimisation either on Young, 2003; Spriggs et al., 2007), the Gender differences in regard to the internet, inside of school or outside results do not conclusively account for cyberbullying and victimisation are of school were identified. the observed differences between ethnic not clear-cut in the literature. Some groups. Further research is needed to evidence indicates cyberbullying is It is difficult to compare these determine whether these differences more prevalent amongst males (Li, ethnic group findings with international are due to minority status, contextual 2006; Wang et al., 2009), whereas, studies, as it is unclear whether higher variables such as school composition, some suggests it is equally likely in the or lower rates may be observed in a or some other factor. two genders (Beckman et al., 2013). certain group due to their majority or The present study supports the ‘no minority status, or some specific factor difference’ finding in the literature as no related to their ethnicity such as degree Limitations difference was found between males and of acculturation, socio economic status, Collectively, these results females for internet or text bullying. No religious affiliation, etc. In terms of contribute to the existing body of difference was found between males and ethnic group research, much of this literature pertaining both to New females in the rates of text or internet work compares ethnic groups within Zealand and international research.
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However, some limitations within this internationally and provides a much perspective. Journal of Youth and research should be noted. As mentioned needed overview of the state of bullying Adolescence 38, 101–121. DOI: 10.1007/ above, methodological differences in and victimisation within a New Zealand s10964-008-9271-1. the time frame of measurement used sample. The sample used also had a Beckman, L., Hagquist, C., & Hellström, L. for bullying behaviour and in the number of methodological strengths (2013). Discrepant gender patterns for phrasing of questions pertaining to including the number of different cyberbullying and traditional bullying: bullying behaviour may have impacted schools sampled within New Zealand An analysis of Swedish adolescent data. Computers in Human Behavior, 29, 1896– self-reported rates of bullying and with a range of school deciles, the large 1903. DOI:10.1016/j.chb.2013.03.010. victimisation, and thus may account sample size, and the longitudinal design. Carroll-Lind, J., & Kearney, A. (2004). for some of the observed differences in The results indicate that rates of Bullying: What do students say? prevalence rates. The present research both bullying and victimisation may Kairaranga, 5, 19-24. experiences the same limitation as it be elevated compared to international Caspi, A., McClay, J., Moffitt, T. E., Mill, does not align with the majority of samples and therefore higher than J., Martin, J., Craig, I. W., Taylor, A., research in terms of the measurement expected. Differing rates of bullying & Poulton, R. (2002). Role of genotype period used. Different approaches and victimisation were found across in the cycle of violence in maltreated to the measurement of bullying and the different types of these phenomena, children. Science, 297, 851–854. DOI: victimisation including self report, with both bullying and victimisation DOI: 10.1126/science.1072290. peer nomination, teacher nomination via text messaging being more common Coggana, C., Bennett, S., Hooper, R., or behavioural observation, also limit than anticipated. Gender and age trends & Dickinson, P. (2003). Association the comparability of results. Little in bullying and victimisation were between bullying and mental health status in New Zealand adolescents. cosensus exists about which approach comparable to international research; International Journal of Mental is best; however, it is largely agreed however, differences were noted in that rates of bullying and victimisation Health Promotion, 5, 16-22. DOI: regard to cyberbullying and victimisation 10.1080/14623730.2003.9721892. vary according to measurment methods with no differences being found between (Cole, Cornell & Sheras, 2006; Griffin Cole, J. C. M., Cornell, D. G., & Sheras, P. the two genders. Ethnicity showed no (2006). Identification of school Bullies & Gross, 2004; Swyer et al., 2008). overall difference for average rates of by survey methods. Professional School Bullying research would benefit from bullying and victimisation, but when Counseling, 9, 305-313. consensus among researchers in their the differing types were explored; Māori Craig, W. M. (1998). The relationship among approach to assessment. individuals engaged in more bullying bullying, victimization, depression, One commonly reported issue with inside school, outside school, and text anxiety and aggression in elementary self report is that individuals may under- bullying and were subjected to more school children. Personality and report the prevalence of bullying or text victimisation than New Zealand Individual Differences, 24, 123-130. victimisation in which they are involved Europeans or ‘other’ ethnicities. DOI: 10.1016/S0191-8869(97)00145-1. (Solberg & Olweus, 2003). Although If the rates are accurate, they Craig, W. M., Harel-Fisch, Y., Fogel- Grinvald, H., Dostaler, S., Hetland, anonymity was preserved in this study indicate that bullying is a significant J., Simons-Morton, B. et al. (2009). A and this was emphasised to students, it issue for New Zealand adolescents and is unclear whether the levels reported cross-national profile of bullying and bullying in New Zealand may present victimization among adolescents in do in fact represent the true levels of somewhat differently than in other 40 countries. International Journal of student involvement in bullying and countries. Consequently, more research Public Health, 54, S1–S9. DOI: 10.1007/ victimisation. Using multiple measures is needed to specifically understand s00038-009-5413-9. of bullying and vicitmisation, such as New Zealand adolescents. As such, Denny, S., Peterson, E. R., Stuart, J., Utter, peer report and self report, may have intervention programmes within New J., Bullen, P., Fleming, T., Ameratunga, lead to more reliable results but this Zealand may need to be adapted to S., Clark, T., & Milfont, T. (2014): was not achievable within the scope of cater specifically to the needs of Māori Bystander intervention, bullying, and this study. students such that this problematic victimization: A multilevel analysis of Although large and in many behaviour can be ameliorated. New Zealand high schools. Journal of School Violence, 0, 1-28. DOI: ways representative of New Zealand 10.1080/15388220.2014.910470. adolescents, the sample was drawn References Department of Labour. (2009). Migration only from schools throughout the North Trends and Outlook 2007/08. Department island of New Zealand. As such it may Adair, V. A., Dixon, R. S., Moore, D. W., & Sutherland, C. M. (2000). Ask your of Labour, New Zealand. 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Appendix 1
Bullying/victimisation questions
In the last month, how often have you seen other student(s) being bullied in your school/kura?
In the last month, how often have you bullied other students?
In the last month, how often have you been bullied by other students?
Is your school/kura trying to do anything to stop bullying?
How well do you think you school’s/kura’s actions to stop bullying have helped?
In the last month, how often have you bullied young people who do not go to your school/kura?
In the last month, how often have you been bullied by young people who do not go to your school/kura?
In the last month, about how often have you sent a mean text message to someone?
In the last month, about how often have you received a mean text message from someone?
In the last month how often have you bullied others online?
In the last month how often have you been bullied by others online?
Note: the final two questions (regarding internet bullying/victimisation) were not included in the year one survey.
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