AGGRESSIVE BEHAVIOR Volume 41, pages 97–108 (2015)

Childhood Bullying and Social Dilemmas Amelia Kohm* Chapin Hall at the University of Chicago, Chicago, Illinois

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Children who witness bullying often do not defend victims. Bystanders might be reticent to intervene because they are stuck in “social dilemmas.” Social dilemmas are situations in which individuals make decisions based on self-interest due to their lack of confidence that others will join with them in decisions that benefit the collective. In this study, the social dilemmas concept, which comes from game theory and social psychology, was applied to bullying for the first time. A total of 292 middle school students at a private residential school in the United States completed surveys about their bullying-related experiences within their residences of 10 to 12 students of the same gender. Multilevel modeling was employed to assess if and how attitudes, group norms, and social dilemmas predict behavior in bullying situations. The findings suggested that both individual and group factors were associated with behavior in bullying situations and that attitudes, group norms, and social dilemmas each made a unique contribution to predicting behavior in bullying situations. Aggr. Behav. 41:97–108, 2015. © 2015 Wiley Periodicals, Inc.

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Keywords: bullying; social dilemmas; bystanders; group norms

INTRODUCTION

Children who witness bullying defend victims in only 12% to 25% of bullying episodes regardless of their sympathy for the victims or dislike of the bullies (Craig & Pepler, 2000; O’Connell, 1999). For the bystanders who decide not to intervene, such bold action may seem futile at best and dangerous at worst. But might more bystanders be more willing to intervene if they felt confident that others would stand with them? As Aristotle observed long ago: “No tyrant need fear till men begin to feel confident in each other.” Evidence from ethnographic studies of children’s social hierarchies sheds light on the role of bystanders, who are usually present in bullying situations (Atlas & Pepler, 1998; Craig & Pepler, 2000; Hawkins, Pepler, & Craig, 2001; O’Connell, Pepler, & Craig, 1999; Sutton & Smith, 1999; Xie, Swift, Cairns, & Cairns, 2002). For example, Adler and Adler (1995); who conducted seven years of participant-observation and interview research with third- through sixth-grade students, observed that most children side with a popular clique member in any dispute to avoid becoming victimized themselves. Similarly, a research team that interviewed middle school and high school students found that harassing and humiliating weaker, less popular students was a common method to try to increase their own status at school. Moreover, victims’ friends rarely defended them and sometimes joined in the bullying to boost their status (Bishop et al., 2004). © 2015 Wiley Periodicals, Inc.

Such findings, from research on social hierarchies, provide evidence in line with the hypothesis that social dilemmas would help to explain why children often do not defend victims of bullying. Social dilemmas are situations in which isndividuals make decisions based on self-interest due to their lack of confidence that others will join with them in decisions that benefit the collective (Dawes, McTavish, & Shaklee, 1977; Van Lange, Liebrand, Messick, & Wilke, 1992). In a common social dilemma called a public goods dilemma, an individual is reluctant to contribute to a public good, such as a public park or clean air, if he or she believes that an insufficient number of others will also contribute and thus his or her own efforts would be wasted (Kollock, 1998). The social dilemmas concept, which comes from game theory and social psychology, has been applied to school-age bullying only in the present study, but could be a fruitful direction for future research. Perhaps children refrain from defending victims because they feel that such a selfless contribution (for the good of the


Correspondence to: Amelia Kohm, Chapin Hall at the University of Chicago, 1313 East 60th Street, Chicago, IL 60637. E-mail: [email protected] Received 29 January 2013; Revised 7 November 2014; Accepted 10 November 2014 DOI: 10.1002/AB.21579 Published online 6 January 2015 in Wiley Online Library (wileyonlinelibrary.com).

98 Amelia Kohm

victim and the good of the group since it might prevent future bullying) would be futile unless a sufficient number of other group members joined their efforts. As the evidence from ethnographic studies suggests, unilateral action might leave the defender vulnerable to victimization (Adler & Adler, 1996; Merten, 1997). In addition, children might have low expectations about others supporting a defender because they might recognize that other children are similarly motivated to act in their own self-interest. In a cross-sectional study of 1,220 Finnish elementary school children, Salmivalli and Voeten (2004) examined the connections among individual attitudes, group norms, and students’ roles in bullying situations. Roles included bullying others, assisting the bully, reinforcing the bully, defending the victim, or staying outside the bullying situation, and each role was associated with a type of behavior. Because the researchers found behavior in bullying situations to be predicted by not only individual attributes (attitudes) but also group characteristics (norms), their study provided an appropriate model for the current one. In addition, Salmivalli and Voeten found that when they added attitudes and norms to their models, there were fairly small reductions in the variance for behavior in bullying situations, at both the individual and group levels, suggesting that other factors are important to predicting behavior in bullying situations. The current study replicated and extended the previous study by focusing on whether social dilemmas help further explain the variance in behavior in bullying situations. There were two hypotheses: Both individual factors (such as attitudes) and group factors (such as norms) would be associated with behavior in bullying situations; and attitudes, group norms, and social dilemmas would each make a unique contribution to predicting student behavior in bullying situations. METHOD

Sample and Participant Selection Participants were 292 middle school students aged 11 to 14 years (29% in sixth grade, 35% in seventh grade, and 36% in eighth grade; 48.3% were girls) at a private residential school in the United States that serves children from low-income families from throughout the United States. Students at the school are normally functioning and are not selected according to specific needs. The racial composition of the school at the time of the study was approximately 60% Caucasian, 20% African American, 10% Hispanic, and 10% other. Students at the school live in residences with other students of the same gender. A married couple oversees each residence. At the time of the study, the school had Aggr. Behav.

37 middle school residences each composed of 10 to 12 students in Grades 6, 7, and 8. There was a similar distribution of students from each grade in each residence. Assessments and Measures Behavior in bullying situations. The Participant Role Questionnaire (PRQ), developed by Salmivalli and Voeten (2004), was used in the present study to assess student behavior in bullying situations within student residences, the dependent variable. The PRQ first specifies bullying as when “one child is repeatedly exposed to harassment and attacks from one or several other children. Harassment and attacks may be, for example, shoving or hitting the other one, calling him/ her names or making jokes about him/her, leaving him/ her outside the group, taking his or her things, or any other behavior meant to hurt another.” The students reviewed 15 items describing different ways to behave in such situations and assessed how often each of their housemates behaved in the ways described since the school year began (response options are “never,” “sometimes,” or “often”). The items form five scales reflecting different participant roles associated with bullying: bully, assistant, reinforcer, defender, and outsider. Assistants do not initiate but join in the bullying; reinforcers encourage the bullying; defenders help victims; and outsiders are not involved in bullying in any way (Goldbaum, Craig, & Shelley, 2003; Olthof & Goossens, 2003; Salmivalli, 1999, 2001; Salmivalli, Lappalainen, & Lagerspetz, 1998; Sutton & Smith, 1999). The PRQ has demonstrated adequate reliability and validity in past studies. Cronbach’s alpha coefficients based on data in the present study were .93 for the bully scale, .95 for the assistant scale, .93 for the reinforcer scale, .90 for the defender scale, and .55 for the outsider scale. Although scores on the bully, assistant, and reinforcer scales tend to be highly correlated, according to the authors, they seem to represent three distinct factors, rather than one underlying construct (Salmivalli & Voeten, 2004). However, other studies using the PRQ or an adapted 21-item version by Sutton and Smith (for younger children) found that the bully, reinforcer, and assistant roles may be measuring the same underlying construct (Goldbaum, Craig, & Shelley, 2003; Sutton & Smith, 1999; Tani, Greenman, Schneider, & Fregosao, 2003). Thus, “Composite Pro-bullying Behavior” was also computed from all items related to bullying, assisting, and reinforcing behavior. Attitudes toward bullying. Attitudes toward bullying were operationalized as students’ moral beliefs regarding the appropriateness or inappropriateness of bullying and related behavior (Salmivalli & Voeten,

Childhood Bullying and Social Dilemmas 99

2004). Students’ attitudes toward bullying were measured by asking them to evaluate the extent to which they agreed or disagreed with 10 statements about bullying. The scale range was .00 to 4.00. Scores were based on self-reports. Scale means were imputed for missing data for 23 participants. Higher scores corresponded to more antibullying attitudes. In the Finnish study, the internal consistencies of attitudes as measured by Cronbach’s alpha coefficient was .75. In the present study, the Cronbach’s alpha coefficient was .73. Group norms. The development of the questionnaire designed to assess bullying-related classroom norms in the Finnish study was guided by the standard definition of norms as expected standards of behavior in a certain group (Franzoi, 1996). The norms questionnaire included questions about behavior that would be expected or not appropriate in the classroom (Salmivalli & Voeten, 2004). For each of five situations, students assessed the likelihood of seven consequences (such as “Other kids in my residence would avoid him/her” or “He/she would be considered cool”). A neutral norms score was also computed based on the sum of the last item for each condition (“nothing in particular would take place”). The scale range was 30.00 to 120.00 for the antibullying scale and 5.00 to 20.00 for the neutral scale. Higher scores reflected perception of stronger antibullying norms or neutral norms. Scores were based on selfreport and aggregated by student residence. The reliability of the antibullying norm, as measured by the coefficient alpha, was .90. The alpha for the neutral norm was .69. In the Finnish study, students were asked to evaluate the consequences of each act by choosing from eight optional answers. The present study modified the norms measure by asking students to evaluate the probability of several positive and negative consequences using a Likert scale. Social dilemmas. A social dilemmas instrument was developed drawing on the goal-expectation theory by Pruitt and Kimmel (1977). The theory states that cooperative behavior arises in a “strategic environment” (one in which people aim to make rational decisions toward certain ends) when group members share a goal of mutual cooperation and an expectation of cooperation (Pruitt, 1998; Pruitt & Kimmel, 1977). In the present study, it was assumed (although not measured) that participants’ decisions regarding bullying were, at least in part, rational and geared toward certain ends. Noncooperation or “social dilemmas” arise when individuals make decisions based on self-interest due to their lack of confidence that others will join with them in decisions that benefit the collective. The social dilemma variable was operationalized as the degree to which group members agreed that three conditions were present in their residences: Unilateral action to defend

victims would be dangerous or ineffective; group efforts could be more effective; and cooperation from others in an effort to defend a victim was unlikely. Therefore, any individual’s best short-term strategy was to act selfishly (i.e., not defend a victim) even though the best long-term strategy to reduce bullying in the group was to act collectively (to defend the victim). The instrument assessed social dilemmas within the context of three different types of bullying: physical, verbal, and relational. Eight questions were asked about each type of bullying. Students were asked to indicate their level of agreement (strongly agree, agree, disagree, or strongly disagree) with each item. Examples of items related to social dilemma conditions for the verbal bullying scale were, “I could get other kids to stop teasing someone with other students helping me” and “I could get other kids to stop teasing someone by myself.” Because participants were coded as 1 if they met the three social dilemma conditions and 0 if they did not, means were equivalent to percentage of participants who met conditions based on the total number participants who responded to all relevant questions. If a participant skipped any of the items related to a condition, that condition was coded as missing data and it was not established whether the participant met the criteria for being in a social dilemma. There was missing data for 7% to 23% of the participants, depending on the type of bullying under consideration. Means were not imputed for missing data because conditions were not established based on scales composed of similar items. Therefore, there were no logical means to impute. The reliability of the six items related to social dilemma conditions was then assessed for each type of bullying. The alpha for verbal bullying (teasing) was .64, for physical bullying (beating up or pushing around) was .71, and for relational bullying (gossiping) was .67. The reliability of all 18 items, assessed together, was .87. Minor edits were made to the original items used in the Finnish study to make them more understandable to students at the participating school. Edits were based on feedback during pilot testing of the instrument with 15 students at the school, in Grades 4 to 8. Assessment of missing data. Missing data points were replaced with imputed scale means or sample means for categorical variables. Mean substitution produces internally consistent sets of results. However, it also artificially decreases the variation of scores, and this decrease is proportional to the amount of missing data. To assess the possible effect of missing data, dummy variables were created as controls where means were imputed for missing data. Only a small number of the coefficients for the dummy variables for the missing data were significant, suggesting that those participants with missing data did not significantly differ Aggr. Behav.

100

Amelia Kohm

from those without missing data. In addition, final models for three outcomes (composite probullying, withdrawing, and defending) were run with cases with missing data deleted. This procedure eliminated approximately one third of the cases (n ¼ 190). However, even with this much-reduced sample, the coefficients were generally similar in size and direction to those produced with the whole sample (which included imputed means and dummy variable controls) suggesting that the missing data did not have a substantial effect on the results. Procedure Parents and guardians of all students in the designated grades (N ¼ 389) were contacted to inform them of the study, explain their children’s rights as participants, and ask if they would like their child to participate. The transience of this low-income population often made it difficult to reach parents and guardians. Consent was received from 308 (or 79%) of the parents and guardians and refusal from 19 (or 5%). A total of 292 students living in 37 student residence (or 95% of the students who had parental consent) agreed to complete the questionnaire. The data were collected via online questionnaires in the computer laboratory at the middle school building. Those students with parental consent who also assented to participate in the study completed the questionnaire and were led through the four instruments in the following order: attitudes measure, PRQ, social dilemmas measure, and norms measure. Analyses To assess if and how attitudes, group norms, and social dilemmas predict behavior in bullying situations, multilevel modeling was employed using Hierarchical Linear Modeling software (Raudenbush & Bryk, 2002). Multilevel modeling is a type of regression analysis designed to handle hierarchical or clustered data. In the current study, students were considered Level 1 units and were clustered in residences that were considered Level 2 units. Observations of students within groups were likely to be more similar than observations of individual students sampled from different residences. When such conditions exist, there is an intraclass correlation (ICC), and the assumption of independence of observations for regular regression is violated (Hox, 1998; Kreft & De Leeuw, 1998; Raudenbush & Bryk, 2002). In the current study, the groups of interest were the residences, rather than classrooms, because ICCs are typically higher in family households than in classrooms, and residences within an educational setting might be more similar to households (Gulliford, Ukoumunne, & Chinn, 1999; Murray et al., 1994; Siddiqui, Hedeker, Flay, & Hu, 1996). Aggr. Behav.

A series of 11 multilevel regression models of increasing complexity were run for each of the dependent variables: probullying (a composite of the three probullying behavior), withdrawing from bullying situations, and defending victims of bullying.1 Each series of regressions began with a null model, which included an intercept and two variance components: behavior differences between students within residences and behavior differences between residence behavior means. The null model served as a reference for subsequent models, each of which included variables from previous models and an additional variable of interest. Variables that controlled for missing data and/or significant interactions between key variables with gender or grade were added, along with variables of interest as appropriate. Interactions between grade and gender with nonsignificant coefficients were not included in models. Grade and attitudes were entered into the model as Level 1 predictors of behavior in bullying situations. Such predictors could explain both withinand between-group variances because each residence had a different group of students. Gender and norms were entered into the model as Level 2 predictors. Because there was only one gender per residence, this variable could not explain within-group variance. Similarly, because the group norms variables were aggregated to the group level, they could only explain variance between groups. The social dilemma variable was entered as a Level 1 predictor (i.e., whether the individual reported all three social dilemma conditions) and, in aggregate form, as a Level 2 predictor (i.e., the percent age of residence members who reported all three social dilemma conditions). The attitudes and norms predictors were continuous variables whereas the grade, gender, and social dilemma variables were dummy variables. Unlike the study by Salmivalli and Voeten (2004), the current study did not omit the general intercept and thereby create separate coefficient estimates for each grade. To simplify analyses, Grade 6 was used as the reference category for grade. As in the study by Salmivalli and Voeten (2004) a Rankit transformation was employed to reduce the influence of outliers and normalize the distribution of behavioral variables (Noruésis, 1993). However, the distribution of the raw scores did not strongly depart from normality as it did in the earlier study. In addition, for each model that added a Level 1 variable, the model was run twice: once with the slope fixed (or set to 0) at Level 2 and once with a random slope, one that is 1 This article does not report results on models for the individual probullying roles-bully, reinforcer, and assistant-due to evidence that they may be measuring the same underlying construct.

Childhood Bullying and Social Dilemmas 101

allowed to vary across groups. The deviance statistics for the two models were then compared with each other, taking into account the number of parameters in each model, using a chi-square test. In none of the tests was a difference statistically significant. Thus all slopes for Level 1 variables were fixed at Level 2, meaning that the relation between individual-level variables and behavior outcomes did not vary by residence. RESULTS

Descriptive Table I presents the means and standard deviations of boys and girls in the three grade levels for each of the variables2. The means and standard deviations for the antibullying and neutral norms were residence averages and were not categorized by grade because each residence included students in all three grades. Reinforcing bullies, defending victims, or withdrawing from bullying situations were more common behavior than bullying and assisting a bully. Assisting the bully seemed to decrease with age for girls in the sample. Also, there was an increasing trend, from sixth to eighth grade, in both defending victims and withdrawing in bullying situations for both boys and girls. Bullying, assisting, reinforcing, and withdrawing were more prevalent among boys than girls, while defending was more prevalent among girls. With respect to attitudes, girls’ antibullying attitudes appeared to decrease with age. Boys and girls did not appear to differ in the strength of their antibullying attitudes. In addition, boys’ and girls’ residences were similar in the strength of antibullying and neutral norms. The number of students who reported all three conditions for social dilemmas with regard to verbal bullying seemed to decrease with age for boys and increase with age for girls. The number of girls reporting social dilemma conditions related to relational bullying also appeared to increase with age. In addition, the number of girls reporting social dilemma conditions related to physical bullying seemed to decrease with age. The majority of students had witnessed bullying in their residences, with verbal (96.2%) and relational (91.8%) being the most common types of bullying. In addition, 50% to 60% of the students, depending on the type of bullying, believed that unilateral efforts to help victims would be dangerous and/or ineffective in their residences. Similarly, 44% to 54% believed that group efforts would be more effective and/or safe. Fewer

2

Description in this section is based on inspection of the descriptive data in Table 1 and no inferential statistics were carried out.

students (approximately 30% for each type of bullying) had low expectations that their housemates would help them defend a victim. Assessment of Regression Coefficients Table II provides the regression coefficients for the variables of interest and related standard errors for the final model for each of the dependent variables. Because coefficients were not standardized, comparisons across predictors should be considered relative to their standard errors. Review of the coefficients begins with withingroup (Level 1) predictors and then focuses on betweengroup (Level 2) predictors. Grade was entered as a dummy variable with Grade 6 as the reference category. The differences between seventh graders’ and sixth graders’ behavior in bullying situations were not statistically significant. Similarly, eighth graders did not differ from sixth graders in terms of their behavior, except with regard to defending victims. Students in the eighth grade, on average, ranked significantly higher on defending behavior than those in the sixth grade. Consistent with Hypothesis 2, the coefficients suggested that as antibullying attitudes increased, probullying ranks decreased and defending ranks increased. Antibullying attitudes, however, did not have a significant effect on withdrawing behavior. Contrary to expectations, within-group variation on reporting social dilemma conditions generally did not predict behavior in bullying situations. All coefficients were nonsignificant, with the exception of those for social dilemmas related to relational bullying. The coefficient for this variable was significant in the model for the probullying composite outcome. There was an inverse relation between reporting social dilemma conditions and probullying behavior. Thus, contrary to expectations, those who reported all three conditions tended to rank lower on probullying behavior. However, the effect size, given that the values for social dilemmas could only be 1 or 0, was modest. The coefficient on gender was significant for all behavior except defending. In general, boys’ residences ranked higher than girls’ residences on probullying behavior and on withdrawing behavior. The relation of antibullying norms to probullying behavior was significant and in the expected direction: As antibullying norms increased, probullying behavior ranks decreased. The coefficient for withdrawing behavior was not significant, and the antibullying norms coefficient for defending behavior approached significance and was positive, as expected. Student residences that ranked higher on neutral norms tended to have students who ranked higher on probullying behavior and Aggr. Behav.

102

Amelia Kohm

TABLE I. Score Means (and Standard Deviations) of Boys and Girls From Different Grade Levels Independent Variable Behaviors Bullying Assisting the bully Reinforcing the bully Defending the victim Withdrawing

Gender Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls

Grade 6

Grade 7

Grade 8

.59 .54 .66 .64 .86 .87 .79 .83 .92 .88

.70 .56 .74 .62 .92 .81 .84 .86 .93 .87

.65 .48 .71 .58 .88 .80 .96 .94 .96 .91

(.35) (.40) (.36) (.42) (.35) (.41) (.29) (.26) (.20) (.19)

(.38) (.36) (.37) (.39) (.35) (.36) (.31) (.29) (.18) (.18)

(.36) (.34) (.35) (.32) (.35) (.37) (.33) (.31) (.18) (.13)

Attitudes Boys Girls Group Norms Antibullying norms Neutral norms Social Dilemmas Verbal Bullying: Meets Conditions A, B, C Physical Bullying: Meets Conditions A, B, C Relational Bullying: Meets Conditions A, B, C

Boys’ Girls’ Boys’ Girls’

Homes Homes Homes Homes

Boys Girls Boys Girls Boys Girls

lower on defending, although the coefficient for the composite probullying outcome only approached significance. In addition, the coefficient for neutral norms related to withdrawing behavior was not significant. The number of students in a residence reporting all three social dilemma conditions related to either physical or relational bullying tended to have a positive relation with probullying behavior and withdrawing, as expected. None of the coefficients for mean social dilemmas related to verbal bullying were significant (however, note the interactions discussed below). In addition, several significant interactions indicated that the relation between mean social dilemmas and behavior sometimes varied by gender or grade. As shown in Figure 1, mean social dilemmas related to physical bullying did not predict withdrawing behavior for boys, but did predict this behavior for girls: on average, girls scored far below the mean on withdrawing behavior in residences with low mean scores (mean  1 SD) and scored slightly above the mean on withdrawing behavior in residences with high mean scores (mean þ 1 SD). In addition, mean social dilemmas related to verbal bullying did not predict girls’ defending behavior, but they appeared to be related to boys’ defending behavior. Boys in residences with low mean social dilemmas related to verbal bullying (mean  1 SD) tended to score Aggr. Behav.

3.17 (.55) 3.02 (.64) 69.35 69.45 12.88 12.77 .19 .15 .10 .22 .07 .08

2.75 (.53) 2.95 (.51)

2.78 (.60) 2.80 (.54)

(11.45) (14.24) (3.08) (2.84) (.39) (.36) (.30) (.42) (.26) (.28)

.18 .17 .14 .16 .21 .11

(.39) (.38) (.35) (.37) (.41) (.32)

.10 .23 .10 .10 .04 .14

(.31) (.42) (.31) (.30) (.20) (.35)

above the mean on defending behavior whereas boys in residences with high social dilemmas (mean þ 1 SD) tended to score below the mean on defending behavior. A significant interaction between grade and mean social dilemma related to relational bullying was detected in the final defender model. Sixth graders’ defending behavior, on average, was not strongly associated with the number of housemates reporting social dilemma conditions related to relational bullying. However, eighth-grade students in residences with low mean social dilemmas related to relational bullying (mean  1 SD) tended to rank substantially higher on defending behavior than those in high mean social dilemma residences (mean þ 1 SD). However, it should be noted that even students in residences with high mean social dilemmas tended to score above the mean on defending behavior. Assessment of Variance Components In addition to coefficient statistics, Hierarchical Linear Modeling also results in data on the variance components of each model. Variance is analogous to the error term in traditional regression equations. The multilevel model disaggregated the total variation into a component at the individual level (i.e., withinresidence variation) and at the group level (i.e., between-residence variation).

Childhood Bullying and Social Dilemmas 103 TABLE II. Total Explained Variance (R2) for Each Model Behavior and ICC Composite Probully Behavior ICC: 19.86%

Withdrawing ICC: 11.55%

Defending the Victim ICC: 11.53%

Model Null 1 2 3 4 5 6 7 8 9 10 11 Null 1 2 3 4 5 6 7 8 9 10 11 Null 1 2 3 4 5 6 7 8 9 10 11

Variables Added (Level Added) Grade Gender Antibullying Attitudes Antibullying Norms Neutral Norms Social Dilemma - Verbal Bullying Social Dilemma - Physical Bullying Social Dilemma - Relational Bullying Social Dilemma - Verbal Bullying Social Dilemma - Physical Bullying Social Dilemma - Relational Bullying Grade Gender Antibullying Attitudes Antibullying Norms Neutral Norms Social Dilemma - Verbal Bullying Social Dilemma - Physical Bullying Social Dilemma - Relational Bullying Social Dilemma - Verbal Bullying Social Dilemma - Physical Bullying Social Dilemma - Relational Bullying Grade Gender Antibullying Attitudes Antibullying Norms Neutral Norms Social Dilemma - Verbal Bullying Social Dilemma - Physical Bullying Social Dilemma - Relational Bullying Social Dilemma - Verbal Bullying Social Dilemma - Physical Bullying Social Dilemma - Relational Bullying

Level 1 Variance

Level 2 Variance

.815 .817 .817 .732 .73 .73 .725 .731 .723 .723 .723 .725 .888 .876 .874 .875 .875 .875 .877 .87 .873 .873 .872 .873 .89 .851 .851 .826 .825 .824 .829 .833 .836 .84 .838 .821

.202 .203 .185 .157 .145 .127 .137 .135 .144 .138 .101 .077 .116 .127 .114 .117 .129 .123 .121 .124 .126 .138 .107 .078 .116 .126 .133 .114 .095 .092 .084 .076 .079 .019 .023 .003

R2W (%)

R2B (%)

0.25 0.25 10.18 10.43 10.43 11.04 10.31 11.29 11.29 11.29 11.04

0.50 8.42 22.28 28.22 37.13 32.18 33.17 28.71 31.68 50.00 61.88

1.35 1.58 1.46 1.46 1.46 1.24 2.03 1.69 1.69 1.80 1.69

9.48 1.72 0.86 11.21 6.03 4.31 6.90 8.62 18.97 7.76 32.76

4.38 4.38 7.19 7.30 7.42 6.85 6.40 6.07 5.62 5.84 7.75

8.62 14.66 1.72 18.10 20.69 27.59 34.48 31.90 83.62 80.17 97.41

Note. R2W, within-group variance; R2B, between-group variance.

As indicated in Table II, ICCs for outcome behavior in the present study ranged from 11.5% for defending and withdrawing behavior to 19% to 20% for probullying behavior. This finding supported Hypothesis 1 that both individual and group factors would be associated with behavior in bullying situations. In addition, although there were clear associations between context and behavior for all of the behavior measured, the probullying behavior was more closely associated with context than were withdrawing and defending. Because none of the models included random slopes, it was possible to compute explained (or modeled) variance, analogous to R2 statistics in traditional regression. These figures were computed by subtracting the variances of the present model from the variances of the null model and dividing by the variances of the null model. Thus, they showed the proportion of total variance at each level that was explained after the

addition of the variable to the present model. In some cases, adding predictors to a model actually increased the variance and thus decreased the variance explained. These predictors unnecessarily complicated the models, using up degrees of freedom and thus increasing variance. In addition, if a predictor that models part of the within-group variability does not model part of the between-group variability, the decrease in the Level 1 variance must be balanced by an increase in the estimate of the Level 2 variance. Adding a Level 1 predictor results in a decrease in the similarity within groups and, consequently, an increase in the dissimilarity between groups (Snijders & Bosker, 1994). As shown in Table II, the variable that explained the most within-group variance for the probullying behavior outcome was antibullying attitudes. None of the other predictors resulted in sizeable decreases in variances. Indeed, while the ICCs indicated that the majority of the Aggr. Behav.

104

Amelia Kohm 0.20 0.10 0.00

Withdrawing Behavior Z-Score

Low

Mean

High

-0.10 -0.20

Girls Boys

-0.30 -0.40 -0.50 -0.60 -0.70 -0.80 -0.90

Mean Social Dilemma Related to Physical Bullying

Fig.1. Expected ranks for withdrawing behavior X mean social dilemmas (physical) X gender.

variance in the behavior is explained at the individual level, the predictors included in the present study’s models did not explain much of that variance. For the probullying behavior model, the predictors explained between 10% and 13% of the Level 1 variance. Eight percent of the variance for defending behavior and only 2% of the variance for withdrawing were explained by the predictors in the models. The predictors accounted for significantly more of the Level 2 variance. For the probullying models, the predictors explained 54% to 62% of the Level 2 variance. The predictors accounted for 33% of the between-group variance in withdrawing behavior and 97% of the between-group variance in defending behavior. For the probullying models (with the exception of reinforcing), adding gender resulted in sizeable increases in explained variance, particularly for bullying behavior (from 1.46% to 17.01%). The addition of antibullying attitudes resulted in even larger increases in explained variance. (Although attitudes were added at the individual level, housemates’ similarity in attitudes resulted in reductions in Level 2 variance.) For example, in the composite probullying model, adding antibullying attitudes increased explained variance from 8.42% to 22.28%. Antibullying norms and neutral norms also generally resulted in sizeable reductions in Level 2 variance for probullying behavior. Finally, although adding the individual reports of social dilemma conditions had very little effect on the overall explained variance in the probullying models, adding the mean Aggr. Behav.

social dilemma variables related to physical and relational bullying resulted in sizeable increases in explained Level 2 variance. For example, in the composite probullying model, adding mean social dilemmas related to physical bullying increased explained variance from 31.68% to 50.00%. For the withdrawing models, most of the predictors added resulted in decreases in explained Level 2 variance. Indeed, the only predictors that had a substantial effect were the mean social dilemma variables related to physical and relational bullying. Adding the mean social dilemma variable related to relational bullying increased explained variance at Level 2 from 7.76% to 32.76%. For the defending models, the additions of antibullying norms, mean social dilemmas related to verbal bullying, and mean social dilemmas related to relational bullying each resulted in substantial increases in explained variance. For example, adding mean social dilemmas related to verbal bullying increased explained variance from 31.90% to 83.62%. DISCUSSION

The present study produced support for both hypotheses: (1) Both group and individual factors predicted behavior in bullying situations; and (2) Attitudes, group norms, and social dilemmas each made a unique contribution to predicting student behavior in bullying situations. For the outcome behavior in the present study,

Childhood Bullying and Social Dilemmas 105

the ICCs ranged from 11.5% for defending and withdrawing behavior to between 19% and 20% for the probullying behavior. These findings supported the hypothesis that both individual and group factors would be associated with behavior in bullying situations. Moreover, the probullying behaviors were more closely associated with group factors than were withdrawing and defending. Salmivalli and Voeten (2004) did not report on ICCs for their models, although they detected variance at both levels, suggesting that both individual and group factors predicted behavior in bullying situations. As predicted by Hypothesis 2, results indicated that antibullying attitudes were predictors of behavior in bullying situations and that as antibullying attitudes increased, probullying ranks decreased and defending ranks increased. Antibullying attitudes did not appear to have a significant association with withdrawing behavior. Salmivalli and Voeten (2004) also found that antibullying attitudes were inversely related to probullying behavior and positively related to defending behavior. However, unlike the present study, Salmivalli and Voeten also found that antibullying attitudes were positively related to withdrawing behavior, which is in line with the hypotheses for the present study. The two samples might have had different societal norms concerning withdrawing behavior (which are not measured in either study). Students in the Finnish sample, who opposed bullying, might have felt that withdrawing is an acceptable response in bullying situations, whereas students with antibullying attitudes in the present study might have felt that defending is a more acceptable response. Investigation into the differences in cultural norms related to antisocial behavior, behavior in bullying situations, and social behavior in general between the United States and Finland and how these differences vary by age, race, region, institution, and gender fell outside of the scope of this study. Although some research has been conducted comparing the prevalence of bullying between countries, there is a dearth of research comparing attitudes toward bullying, their relation to behavior in bullying situations, and possible reasons (such as cultural norms) for differences in behavior between countries (Nansel, Craig, Overpeck, Saluja, & Ruan, 2004). The results of one study indicated few differences in England and Italy in children’s attitudes toward bullying (Menesini et al., 1997). Another study compared moral emotions and reasoning to children’s behavior in bullying situations in Spain and Italy. The research team found differences in egocentric disengagement motives between Italian and Spanish students and speculated on cultural norms that might account for such differences (Menesini et al., 2003). No similar comparisons between American and Finnish

students have been conducted. Other research has shown a link between attitudes and behavior; although people strive for attitude-behavior consistency, it is not always clear whether attitudes cause behavior or vice versa (Eagly & Chaiken, 1993). The present study showed that antibullying and neutral norms were group factors associated with probullying behavior and defending behavior. Specifically, and consistent with Hypothesis 2, as antibullying norms increased, probullying behavior ranks decreased. The antibullying norms’ coefficient for defending behavior approached significance and was positive, as expected. Student residences that rank higher on neutral norms tended to have students who ranked higher on probullying behavior and lower on defending. In addition, norms did not appear to have a significant association with withdrawing behavior. There were no significant interactions between either norms variable with gender or grade in the present study. Similarly, Salmivalli and Voeten (2004) found that antibullying norms were negatively associated with bullying and reinforcing behavior—but only for fifth- and sixth-grade students—and positively associated with defending behavior—but only for sixth-grade students. Fourth-grade students’ behavior was generally not associated with antibullying norms, although these students were more likely to withdraw when antibullying norms were lower than were students in the other grades. Neutral norms had variable relations with behavior in the Finnish study, depending on the grade and gender of participants. In the present study, by contrast, more positive relations were found between neutral norms and probullying behavior. There was no significant relation between neutral norms and withdrawing behavior in either study. In addition, in both studies, there was a negative relation between neutral norms and defending behavior. Because students in the present study attended a residential school that promotes a certain school identity, they might have been more influenced by school-wide norms than were the Finnish children who attended day schools, who, by contrast, might have been more influenced by their immediate classmates. However, because we measured norms in a somewhat different manner in the present study than in the Finnish study, differences in the findings should not be over interpreted. In line with the current study, a number of studies suggest that children tend to behave in ways that are deemed acceptable by others in their particular group, and behavior related to aggression and social withdrawal appears to be particularly influenced by classroom norms, while prosocial behavior does not appear to be as closely linked with norms (Chang, 2004; Stormshak et al., 1999Stormshak, Bierman, Bruschi, Dodge, & Coie, 1999). Aggr. Behav.

106

Amelia Kohm

The findings of the present study suggested that social dilemma dynamics help predict behavior in bullying situations. Moreover, unlike attitudes and norms, social dilemmas helped predict withdrawing behavior. In addition, and contrary to expectations, within-group variation in reporting social dilemma conditions generally did not predict behavior in bullying situations. However, as expected, the number of students in a residence reporting all three social dilemma conditions related to either physical or relational bullying tended to have a positive relation with probullying behavior and withdrawing. It should be noted that most of the coefficients for mean social dilemmas related to verbal bullying were not significant (with the exception of boys’ defending behavior). In addition, several significant interactions indicated that the relation between mean social dilemmas and behavior sometimes varied by gender or grade. Salmivalli and Voeten (2004) did not measure social dilemmas in their study, nor have any other studies examined the relation between social dilemmas and behavior in bullying situations. However, the findings regarding social dilemmas in the present study raised some important questions, primarily: (1) Why did social dilemmas predict behavior only at the group level? and (2) Why were social dilemmas better at predicting withdrawing behavior than were attitudes and norms? These issues are addressed below. Why Did Social Dilemmas Predict Only at the Group Level? Goal-Expectation Theory predicts that an individual, under social dilemma conditions, looks at the situation and understands that he or she is contributing to the problem but believes that a unilateral effort will have no impact on the situation; only a group effort will work. Moreover, because he or she has low expectations that enough other people will act in the interest of the group, he or she concludes that it is pointless to act in the interest of the group. In the present study, the social dilemma predictors at the individual level (whether a student agreed that the three social dilemma conditions existed in his or her residence) did not predict behavior well. However, students in residences where more students reported social dilemma conditions—regardless of their own assessment of social dilemma conditions—scored higher on probullying behavior and withdrawing and lower on defending behavior. One possible interpretation is that the more students who reported social dilemma conditions, the more likely it was that those conditions actually existed. To date, the most common method used in social dilemma research has been laboratory experiments in which researchers develop “games” that include social dilemma conditions and then observe how participants behave in those Aggr. Behav.

situations (Johnson & Johnson, 2001; Pellegrini, 2002; Piliavin, 2001). In addition, the relatively few field studies that have been conducted usually started with a situation in which social dilemma conditions naturally exist and then asked respondents how they behaved and why (Fujii, Garling, & Kitamura, 2001; Ohnuma, Hirose, Karasawa, Yorifuji, & Sugiura, 2005; Tyler & Degoey, 1995). The present study relied on students’ perceptions to establish whether social dilemma conditions existed within various residences. Thus it is possible that, even though an individual within a residence did not perceive the conditions, he or she was in a residence that had the conditions, and was acting accordingly, albeit not consciously. Another interpretation might be that individuals’ low expectations of peers led them to conclude that such behavior is the norm (a norm not measured by the instrument used to measure norms in the study since both the norms instrument and the social dilemmas instrument explained unique variance). The perceived norm, in turn, led them to behave “noncooperatively” and perhaps to adjust their attitudes accordingly. Why Were Social Dilemmas Better at Predicting Withdrawing Behavior Than Were Attitudes and Norms? Residences with more students perceiving social dilemma conditions were characterized, in particular, by a larger number of students reporting that they did not expect their housemates to defend a victim in a bullying situation. If students in such residences expected their peers to withdraw from bullying rather than defend a victim, then these students might have been more likely to act in kind to conform to a withdrawing norm. Limitations Although the study produced interesting findings that warrant further investigation, it is important to note its limitations. The cross-sectional design did not allow an assessment of the causal direction between the predictors and behavior. Thus, although one hypothesis was that attitudes, norms, and social dilemmas would lead to certain behavior in bullying situations, it could be that the behavior led to the attitudes, norms, and/or social dilemmas. For example, sometimes individuals infer their attitudes from their behavior. In addition, the statistically significant associations that were found between the predictor variables and the outcome variables could result from both predictors, in a statistical sense, and outcomes being associated with a third, unmeasured, variable. Missing data might also limit the reliability of the findings of the present study. The response rate was 75% of the total middle school population. The lack of

Childhood Bullying and Social Dilemmas 107

participation by 25% of the population primarily was due to parents and guardians not responding to the request for consent. In addition, 34.9% of participants had missing data on at least one predictor, and 10 (of 37) residences had 50% or more students (who participated in the study) with missing data on at least one predictor variable. As discussed above, assessment of the impact of missing data suggested that those participants with missing data did not significantly differ from those without missing data. The instruments employed to measure the variables of interest also had potential limitations. The PRQ generally shows good psychometric properties, and the bully, assistant, and reinforcer roles appear conceptually distinct. However, the subscales used to assess these three probullying roles might be measuring the same underlying concept, according to results from earlier studies. Thus, a conservative approach to interpretation of findings would focus only on the “composite probullying role.” In addition, as noted, the outsider scale’s reliability was low in the present study (the Cronbach’s alpha coefficient was .55), which limited understanding of how the independent variables were related to this dependent variable. Another limitation might have been the way social dilemmas were measured. As noted above, the study relied on students’ perception of the conditions of a social dilemma because there was no way to clearly establish the existence of those conditions as one might in situations in which the costs and benefits of acting selfishly and cooperatively can be objectively demonstrated as in laboratory studies. However, relying on perceptions may be problematic with middle school students, who might not be socially sophisticated enough to understand the costs and benefits of unilateral versus multilateral action. Social dilemmas also might have been measured more accurately had more items related to each social dilemma condition been included in the survey instrument. In the present study, there were only one to two items per condition, which did not allow a very rigorous testing of reliability. Moreover, social dilemmas were treated as a categorical variable (i.e., social dilemma conditions either existed or did not exist, according to student reports). A continuous variable might have provided a more subtle understanding of how such conditions, as they grow stronger, affect individual and group behavior. Contribution The study furthered inquiry into group factors related to bullying. Past research in this area has focused on norms as the key group factor that might affect bullying. The current study examined another group factor: the role of social dilemmas in bullying. The study also

contributed to the literature on real-life social dilemmas. Social dilemma research has been criticized for relying on computer simulations and laboratory experiments, in which real or virtual participants play games that present dilemmas. If future research supports the importance of unraveling social dilemmas to the reduction of bullying in schools, then interventions that employ strategies that tend to moderate social dilemmas in other types of circumstances might be tested. Bullying research, in recent years, has focused more on the role of bystanders in encouraging bullying or passively allowing it to continue. The present study provides a possible explanation for their behavior and a possible direction for future interventions. ACKNOWLEDGMENTS

I am unable to reveal the funding source of the research because I must maintain the confidentiality assurances made to the University of Chicago Human Subjects Committee to protect identifying information of the human participants in the research. There is also the same requirement to protect human participants’ identifying information in the agreement with the funder as a condition of the award. REFERENCES Adler, P. A., & Adler, P. (1995). Dynamics of inclusion and exclusion in preadolescent cliques. Social Psychology Quarterly, 58, 145–162. doi: 10.2307/2787039. Adler, P. A., & Adler, P. (1996). Preadolescent clique stratification and the hierarchy of identity. Sociological Inquiry, 66, 111–142. doi: 10.1111/ j.1475–682x.1996.tb00213.x. Atlas, R. S., & Pepler, D. J. (1998). Observations of bullying in the classroom. Journal of Educational Research, 92, 86–99. doi: 10.1080/ 00220679809597580. Bishop, J. H., Bishop, M., Bishop, M., Gelbwasser, L., Green, S., Peterson, E., & Zuckerman, A. (2004). Why we harass nerds and freaks: A formal theory of student culture and norms. Journal of School Health, 74, 235–251. doi: 10.1111/j.1746–1561.2004.tb08280.x. Chang, L. (2004). The role of classroom norms in contextualizing the relations of children’s social behavior to peer acceptance. Developmental Psychology, 40, 691–702. doi: 10.1037/0012– 1649.40.5.691. Craig, W. M., & Pepler, D. J. (2000). Observations of bullying and victimization in the school yard. In W.M. Craig (Ed.), Childhood social development: The essential readings, (pp. 116–136). Malden, MA: Blackwell Publishers. Dawes, R. M., McTavish, J., & Shaklee, H. (1977). Behavior, communication, and assumptions about other people’s behavior in a commons dilemma situation. Journal of Personality and Social Psychology, 35, 1–11. doi: 10.1037/0022–3514.35.1.1. Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes, Fort Worth, TX: Harcourt Brace Jovanovich College Publishers. Franzoi, S. (1996). Social Psychology, Dubuque, IA: Time Mirror Higher Education Group, Inc. Fujii, S., Garling, T., & Kitamura, R. (2001). Changes in drivers’ perceptions and use of public transport during a freeway closure: Effects of temporary structural change on cooperation in a real-life Aggr. Behav.

108

Amelia Kohm

social dilemma. Environment and Behavior, 33, 796–808. doi: 10.1177/00139160121973241. Goldbaum, S., Craig, W. M., & Shelley, D. (2003). Predicting participant roles in bullying. Paper session presented at the Society for Research in Child Development Biennial Meeting, Tampa, FL. Gulliford, M. C., Ukoumunne, O. C., & Chinn, S. (1999). Components of variance and intraclass correlations for the design of community-based surveys and intervention studies: Data from the health survey for England 1994. American Journal of Epidemiology, 149, 876–883. doi: 10.1093/oxfordjournals.aje.a009904. Hawkins, D. L., Pepler, D. J., & Craig, W. M. (2001). Naturalistic observations of peer interventions in bullying. Social Development, 10, 512–527. doi: 10.1111/1467–9507.00178. Hox, J. (1998). Multilevel modeling: When and why. In I. Balderjahn R. Mathar & M. Schader (Eds.), Classification, data analysis, and data highways: Proceedings of the 21st Annual Conference of the Gesellschaft für Klassifikation e. V., University of Potsdam, March 12– 14, 1997, (pp. ix, 414) New York: Springer. Johnson, D. W., & Johnson, R. T. (2001). Psychology of cooperation and competition. In N. J. Smelser & P. B. Baltes (Eds.), International encyclopedia of the social and behavioral sciences, Oxford, UK: Elsevier Science. Kollock, P. (1998). Social dilemmas: The anatomy of cooperation. Annual Review of Sociology, 24, 183–214. doi: 10.1146/annurev.soc.24.1.183. Kreft, I., & De Leeuw, J. (1998). Introducing multilevel modeling. London: Sage. Menesini, E., Eslea, M., Smith, P. K., Genta, M. L., Giannetti, E., Fonzi, A., & Costabile, A. (1997). Cross-national comparison of children’s attitudes towards bully/victim problems in school. Aggressive Behavior, 23, 245–257. doi: 10.1002/(sici)1098–2337(1997) 23:4 (245::aid-ab3 ) 3.0.co;2-j. Menesini, E., Sanchez, V., Fonzi, A., Ortega, R., Costabile, A., & Lo, F. (2003). Moral emotions and bullying: A cross-national comparison of differences between bullies, victims and outsiders. Aggressive Behavior, 29, 515–530. doi: 10.1002/ab.10060. Merten, D. E. (1997). The meaning of meanness: Popularity, competition, and conflict among junior high school girls. Sociology of Education, 70, 175. doi: 10.2307/2673207. Murray, D. M., Rooney, B. L., Hannan, P. J., Peterson, A. V., Ary, D. V., Biglan, A., & Futterman, R. (1994). Intraclass correlation among common measures of adolescent smoking: Estimates, correlates, and applications in smoking prevention studies. American Journal of Epidemiology, 140(11), 1038–1050. Retrieved from http://aje.oxfordjournals.org/content/140/11/1038.full.pdf. Nansel, T. R., Craig, W., Overpeck, M. D., Saluja, G., & Ruan, W. J. (2004). Cross-national consistency in the relationship between bullying behavior and psychosocial adjustment. Archives of Pediatric Adolescent Medicine, 158, 730. doi: 10.1001/archpedi. 158.8.730. Noruésis, M. J. (1993). SPSS for Windows SPSS base system for Windows (Version V6.0.) [Computer program]. Chicago: SPSS, Inc. O'Connell, P. D. (1999). Peer processes and bullying: Naturalistic observation on the playground. Unpublished doctoral dissertation, York University, Toronto, Canada. O’Connell, P., Pepler, D., & Craig, W. (1999). Peer involvement in bullying: Insights and challenges for intervention. Journal of Adolescence, 22, 437–452. doi: 10.1006/jado.1999.0238. Ohnuma, S., Hirose, Y., Karasawa, K., Yorifuji, K., & Sugiura, J. (2005). Why do residents accept a demanding rule? Fairness and social benefit as determinants of approval of a recycling system. Japanese Psychological Research, 47, 1–11. doi: 10.1111/j.1468–5584.2005. 00267.x. Olthof, T., Goossens, F. A. (2003, April). Emotional and motivational correlates of playing a particular role in bullying. Paper session

Aggr. Behav.

presented at the Society for Reseach in Child Development Biennial Meeting, Tampa, Florida. Pellegrini, A. D. (2002). Bullying, victimization, and sexual harassment during the transition to middle school. Educational Psychologist, 37, 151–163. doi: 10.1207/s15326985ep3703_2. Piliavin, J. A. (2001). Sociology of altruism and prosocial behavior. In N. J. Smelser & P. B. Baltes (Eds.), International encyclopedia of the social and behavioral sciences, (pp. 411–415) (Oxford, UK: Elsevier Science. Pruitt, D. G. (1998). Social conflict, In D. T. Gilbert S. T. Fiske & G. Lindzey (Eds.), The handbook of social psychology 4th ed., 2, (pp. 470–503). Boston: McGraw-Hill. Pruitt, D. G., & Kimmel, M. J. (1977). Twenty years of experimental gaming: Critique, synthesis, and suggestions for the future. Annual Review of Psychology, 28, 363–392. doi: 10.1146/annurev. ps.28.020177.002051. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods, 2nd eds. Thousand Oaks, CA: Sage. Salmivalli, C. (1999). Participant role approach to school bullying: Implications for interventions. Journal of Adolescence, 22, 453–459. doi: 10.1006/jado.1999.0239. Salmivalli, C. (2001). Group view on victimization: Empirical findings and their implications. In J. Juvonen & S. Graham (Eds.), Peer harassment in school: The plight of the vulnerable and victimized,(pp. 398–419). New York, NY: New York Guilford. Salmivalli, C., Lappalainen, M., & Lagerspetz, K. M. J. (1998). Stability and change of behavior in connection with bullying in schools: A twoyear follow-up. Aggressive Behavior, 24, 205–218. doi: 10.1002/(sici) 1098–2337(1998)24:3 3.0.co;2-j. Salmivalli, C., & Voeten, M. (2004). Connections between attitudes, group norms, and behavior in bullying situations. International Journal of Behavioral Development, 28, 246–259. doi: 10.1080/ 01650250344000488. Siddiqui, O., Hedeker, D., Flay, B. R., & Hu, F. B. (1996). Intraclass correlation estimates in a school-based smoking prevention study: Outcome and mediating variables, by sex and ethnicity. American Journal of Epidemiology, 144, 425–433. doi: 10.1093/oxfordjournals.aje.a008945. Snijders, T. A. B., & Bosker, R. J. (1994). Modeled variance in two-level models. Sociological Methods and Research, 22, 342–363. doi: 10.1177/0049124194022003004. Stormshak, E. A., Bierman, K. L., Bruschi, C., Dodge, K. A., & Coie, J. D. (1999). The relation between behavior problems and peer preference in different classroom contexts. Child Development, 70, 169–182. doi: 10.1111/1467–8624.00013. Sutton, J., & Smith, P. K. (1999). Bullying as a group process: An adaptation of the participant role approach. Aggressive Behavior, 25, 97–111. doi: 10.1002/(sici)1098–2337(1999)25:2 3.0.co;2–7. Tani, F., Greenman, P. S., Schneider, B. H., & Fregosao, M. (2003). Bullying and the big five: A study of childhood personality and participant roles in bullying incidents. School Psychology International, 24, 131–146. doi: 10.1177/0143034303024002001. Tyler, T. R., & Degoey, P. (1995). Collective restraint in social dilemmas: Procedural justice and social identification effects on support for authorities. Journal of Personality and Social Psychology, 69, 482– 497. doi: 10.1037/0022–3514.69.3.482. Van Lange, P. A. M., Liebrand, W. B. G., Messick, D. M., & Wilke, H. A. M. (1992). Introduction and literature review. In W. B. G. Liebrand D. M. Messick & H. A. M. Wilke (Eds.), Social dilemmas: Theoretical issues and research findings, pp. vii, 334. Oxford, UK: Pergamon Press. Xie, H., Swift, D. J., Cairns, B. D., & Cairns, R. B. (2002). Aggressive behavior in social interaction and developmental adaptation: A narrative analysis of interpersonal conflicts during early adolescence. Social Development, 11, 205–221. doi: 10.1111/1467–9507.00195.

Copyright of Aggressive Behavior is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.