Depression in Groups of Bullies and Victims: Evidence for the Differential Importance of Peer Status,Reciprocal Friends,School Liking,Academic Self-Efficacy,School Motivation and Academic Achievement

Abstract

The goals of this study were (1) to identify groups of bullies and victims, (2) to investigate level differences in depression, peer relationships, and academic variables, and (3) to examine how peer relationships and academic variables were associated with depression in these groups. The sample comprised 1,451 students (48.6% girls) aged 10–15 years (M = 12.31). Applying Latent Profile Analysis five groups were identified: non-involved adolescents (74%), bullies (9%), moderate victims (11%), severe victims (3%), and bully-victims (3%). Non-involved adolescents had lowest level of depression and highest level of school liking. Severe victims had fewest reciprocal friends and were perceived as most unpopular. Severe victims and bully-victims had highest level of depression and lowest levels of school liking. In non-involved adolescents, moderate victims, and in bully-victims academic variables, in bullies academic variables and peer relations, and in severe victims peer relations were related to depression.

Keywords

Bullying victimization peer relationships academic variables latent profile analysis

A huge body of research shows that bullying – a subcategory of aggressive behaviour – which is characterized by hostile intent, imbalance of power and repetition (e.g., Olweus, 1993; Roland, 1989) has many negative consequences (Hymel & Swearer, 2015). However, studies also demonstrate that there is variation regarding depression, peer relations, and academic variables within certain groups of bulliesand victims (e.g., van der Ploeg, Steglich, Salmivalli, & Veenstra, 2015).Furthermore, there is ample evidence that peer relations and academic variables are associated with depression among adolescents (Huang, 2015; Nangle, Erdley, Newman, Mason, & Carpenter, 2003) and that these associations vary between different groups of bullies and victims (Haynie et al., 2001). Therefore, it is important to take different forms and frequencies of bullying and victimization into account when categorizing adolescents into various groups of bullies and victims. Using peer nominations and self-reports the main goals of this study were to identify different groups of bullies and victims, to investigate level differences of depression, peer relations, and academic variables in these groups of bullies and victims, and to examine how peer and academic variables are associated with depression in these groups.

Groups of Bullies and Victims

It is important to understand that bullying can be carried out via various kinds of behaviour and that it varies in frequency. Usually, overt and relational forms of behaviour (Crick & Grotpeter, 1995) and sporadic versus frequent involvement in bullying and/or victimization are distinguished (Strohmeier et al., 2010). While the target of bullying is labelled as “victim”, the perpetrator of bullying is referred to as “bully” and a young person who is both a victim and a bully is labelled as “bully-victim” (Yang & Salmivalli, 2013). Importantly, there is considerable variation within groups of bullies and victims regarding the frequency and forms of bullying and victimization. In order to capture the heterogeneity among these groups, person-centred statistical approaches are applied (i.e., latent class analysis, LCA; latent profile analysis, LPA). It is important to understand that the results of these analyses depend on the measures used. Studies to date have several methodological shortcomings as they did not take into consideration both different forms and frequencies of behaviours. To begin with, bullying was measured only with one global item (e.g., Kochel, Ladd, Bagwell, & Yabko, 2015) or with one item for physical, verbal and relational bullying and victimization (e.g., Giang & Graham, 2008). Secondly, the frequency of bullying and / or victimization was insufficiently captured as dichotomous items were used (e.g., Goldweber, Waasdorp, & Bradshaw, 2013) or multiple answer formats were afterwards dichotomized (Bettencourt & Farrell, 2013). Thus, these approaches systematically neglected repetition - one of the three central criteria of bullying. Only two studies took different forms and frequency into account and these studies distinguished two victim groups based on their frequency of involvement: severe and moderate victims. However, these studies did not consider bullying (Berkowitz, de Pedro, & Gilreath, 2014; Nylund, Bellmore, Nishina, & Graham, 2007).

When studying different groups of bullies and victims, it is important to include demographic variables as well. While boys are overrepresented in the “bully” and “bully-victim” groups, gender differences are not consistent among “victims” (Strohmeier et al., 2010; Yang & Salmivalli, 2013). Consistent evidence shows that bullying and victimization decreases during adolescence (e.g., Pellegrini & Long, 2002; Solberg & Olweus, 2003). Although findings regarding the importance of immigrant status vary across nations (Walsh et al., 2016), in Austria immigrants are either underrepresented in bully, victim, and bully-victim groups or they do not differ from their non-immigrant peers (Spiel & Strohmeier, 2012).

Depression in Groups of Bullies and Victims

Both bullying and victimization are associated with depression (Juvonen & Graham, 2014). Depending on the frequency of the involvement in bullying episodes, adolescents are at different risk for depression. Being regularly victimized is a permanent negative stressor and creates feelings of helplessness (Roland, 2002) leading to depression (Swearer & Hymel, 2015). Victimized adolescents consistently display higher levels of depression compared to non-victimized adolescents (Ttofi, Farrington, Lösel, & Loeber, 2011). In line with the cumulative risk model (Gutman, Sameroff, & Cole, 2003), frequently victimized adolescents had significantly higher levels of depressive symptoms (van der Ploeg et al., 2015) and were more likely to be depressed compared to less frequently victimized adolescents (Brunstein-Klomek et al., 2007). There is also some evidence that bullies have higher levels of depressive symptoms (Brunstein-Klomek, Marrocco, Kleinman, Schonfeld, & Gould, 2007; Roland, 2002). Finally, adolescents in the bully-victim group showed highest levels of depression (Haynie et al., 2001).

Peer Relations in Bullies, Victims, and Bully-Victims: Reciprocal Friendships and Peer Status

Research on bullying already considered the broader peer context and compared different groups of bullies and victims regarding their peer status and friendship nominations (Salmivalli, Lagerspetz, Björkqvist, Österman, & Kaukiainen, 1996; Scholte et al., 2009). It is important to differentiate these two kinds of peer relations. While reciprocal friendships are an expression of mutual liking on a dyadic level (Newcomb & Bagwell, 1995), perceived popularity and unpopularity are indicators for the status position in the peer group. Although even one reciprocal friend was found to be protective against victimization (Hodges, Boivin, Vitaro, & Bukowski, 1999), victims are vulnerable and being a friend of a victim might be a risk of also becoming victimized. Thus, victims have fewer friends compared to bullies and non-involved adolescents (e.g., Scholte et al., 2009) and are also perceived as least popular by their peers (de Bruyn, Cillessen, & Wissink, 2010). Bullies are often perceived as popular (e.g., Sentse et al., 2015) and they usually have a powerful position in the class (e.g., Caravita, Di Blasio, & Salmivalli, 2009) which make them attractive as friends. However, bullies are also perceived as unpopular (e.g., Sentse, Kretschmer, & Salmivalli, 2015) and they have fewer friends compared to non-involved adolescents (e.g., Kochel et al., 2015). Peer relations in bully-victims are even more problematic as these youngsters are higher on overt aggression, emotion regulation problems, as well as hostile attribution bias leading to fewer friendships (Kochel et al., 2015) but also to high unpopularity in the peer group (Prinstein & Cillessen, 2003).

Bullies, Victims, and Bully-Victims and Academic Variables: School Liking, Motivation, Academic Self-Efficacy and Grades

Being regularly victimized is a stressor that might distract victims to focus on academic tasks (e.g., Espinoza, Gonzales, & Fuligni, 2013). Victimized youth were found to display low levels of academic achievement (e.g., Nakamoto & Schwartz, 2010), they enjoyed school less (Beran, Hughes, & Lupart, 2008), and had lower academic self-efficacy (Thijs & Verkuyten, 2008). But also bullies had lower academic achievements compared to non-involved peers (Spriggs, Iannotti, Nansel, & Haynie, 2007). The lower achievement of bullies was explained by their problematic teacher relationships (Stipek & Miles, 2008), their lower school attendance and an increase in disciplinary problems - at least among female bullies (Feldman et al., 2014). Female bullies were also found to be less interested in school related issues compared to other groups (Bergsmann, Finsterwald, Strohmeier, & Spiel, 2011).

The Present Study

The present study investigates adolescents between 12 and 15 years. This age group was chosen because bullying (7% to 9%) and victimization (12% to 13%) is highest between 11 and 13 year olds (e.g., Walsh & Cosma, 2016). Furthermore, depression increases during adolescence (Kandel & Davies, 1982) which is related to the manifold changes occurring in several life domains such as school and peer relations during this period (Graber & Brooks-Gunn, 1996).

Research Questions Related to Groups of Bullies and Victims

In our first set of research questions we focused on identifying groups of adolescents involved in bullying and victimization. We expected to find at least four different groups of adolescents: non-involved adolescents, bullies, victims, and bully-victims (e.g., Kochel et al., 2015; Yang & Salmivalli, 2013). Additionally, we expected to find further groups of bullies, victims, or bully-victims (e.g., Giang & Graham, 2008). We also explored whether these group differ depending on gender, grade, and immigrant status. We expected that more girls than boys would be in the group of non-involved students, and more boys than girls would be in the group of bullies and bully-victims (e.g., Ttofi et al., 2011). Compared to non-immigrant adolescents we expected equal or fewer immigrant adolescents in groups of bullies and victims (e.g., Stefanek, Strohmeier, van de Schoot, & Spiel, 2011).

Research Questions Related to Differences in Depression, Peer Relations, and Academic Variables

In the second set of research questions differences between these groups in depression, peer relations, and academic variables were investigated. We expected that victimized adolescents would have higher levels of depression compared to non-involved adolescents and bullies (e.g., Ttofi et al., 2011) and that bullies would have equal or higher levels of depression compared to non-involved adolescents (e.g., Roland, 2002). Bully-victims should have higher levels of depression compared to the other groups (Haynie et al., 2001). Furthermore, victims, and bully-victims should have fewer reciprocal friendships compared to bullies and non-involved adolescents (Kochel et al., 2015). Bullies should be perceived as more popular compared to victims and bully-victims (Prinstein & Cillessen, 2003; Sentse et al., 2007). Victims and bully-victims should show lower levels of school liking and academic self-efficacy compared to bullies and non-involved adolescents (Beran et al., 2008; Thijs & Verkuyten, 2008). Bullies and bully-victims were also expected to display lower levels of school motivation and grades compared to non-involved adolescents(Bergsman et al., 2011; Spriggs et al., 2007).

Research Questions Related to Associations between Peer Relations and Academic Variables with Depression in Groups of Bullies and Victims

In our third set of research questions we investigated whether peer relations and academic variables are differentially associated with depression in the various groups of bullies and victims. Because reciprocal friendships are protective against depression they might be stronger associated with depression among victimized children (e.g., Schmidt & Bagwell, 2007) compared to the other groups. To date no study investigated whether the association between perceived popularity and unpopularity and depression differs in various groups of bullies and victims. However, being perceived as unpopular might be especially hurtful for victimized children. It is assumed that non-involved adolescents are not so much troubled with their peer relations. Therefore, in this group academic variables should have a stronger association with depression. Because low academic achievement constitutes an additional source of stress for victimized adolescents, we expected that academic variables would be stronger associated with depression in victimized compared to non-involved adolescents (e.g., Nakamoto & Schwartz, 2010).

Method

Sample

The sample comprised 1,451 adolescents (48.6% girls) aged 10–15 (M = 12.31, SD = 1.20) from eleven secondary schools (grade 5 to grade 8) in Austria. Forty-six percent were non-immigrants as they and both of their parents were born in Austria, 36% were second generation immigrants as they were born in Austria but at least one parent was born abroad, and 18% were first generation immigrants as they and both of their parents were born abroad.

Procedure

Participation in the study was voluntary, strictly confidential and required written parental consent. Data were collected through internet based questionnaires which were completed during one regular school lesson in the schools’ computer labs, under the supervision of two trained research assistants. More than 90% of all eligible students participated in thestudy.

Measures

Bullying, victimization, and depression were measured with validated self-report scales. Reciprocal friendships, perceived popularity, and perceived unpopularity were measured via peer nominations.

Self Reports

Depression. The validated German version of the Child Depression Inventory (CDI) (Kovacs, 1985) was used (Stiensmeier-Pelster, Schürmann, & Duda, 2000). Participants responded to 26 items on a three-point scale such as: “I am sad once in a while”, “I am sad many times”, “I am sad all the time”. The reference period was the last two weeks. Due to ethnical reasons a forth answering option for each item was included: “I do not want to answer”. If adolescents chose this option this answer was coded as a missing value. All children who answered at least ten items were included in the present study as the 10-item short form of the Children’s Depression Inventory revealed satisfactory reliability in previous studies (e.g., Nylund et al., 2007).

Overt and Relational Aggression. Relational aggression (Cronbach’s α= .79) was measured with five items adapted from Crick and Grotpeter (1995), e.g. “Some kids leave other kids out on purpose when it’s time to play or do an activity. How often have you done that during the last two months?” Overt aggression (Cronbach’s α= .78) was measured with three items, e.g. “Some kids hit other kids. How often have you done that during the last 2 months?”.

Overt and Relational Victimization. Relational victimization (Cronbach’s α= .80) was measured with five items adapted from Crick and Grotpeter (1995), e.g. “How often has one or more of your classmates told lies about you in the last two months so that others wouldn’t like you anymore?” Overt victimization (Cronbach’s α= .74) was measured with three items, e.g. “How often have you been kicked or got your hair pulled by one or more of your classmates in the last two months?”.

Bullying Perpetration and Bullying Victimization. Self-reported bullying perpetration and bullying victimization was measured with one global item and three specific items (Strohmeier, Gradinger, Schabmann, & Spiel, 2012). The bullying scale (Cronbach’s α= .78) comprised items like “How often have you insulted or hurt other students during the last two months?” and the victimization scale (Cronbach’s α= .82) comprised items like “How often have other students insulted or hurt you during the last two months?”.

The answering format for all six scales were given on a five-point rating scale ranging from 0 (never), 1 (one or two times), 2 (two or three times per month), 3 (about once a week), to 4 (nearly every day).

School Liking (Cronbach’s α= .65) was measured with three items developed by Weichhold (2002), e.g. “I like going to school.”

School Motivation (Cronbach’s α= .73) was measured with three items developed by Kunter et al. (2002), e.g. “At school I’m learning something that is important for me.”

Academic Self-Efficacy (Cronbach’s α= .71) was measured with three items developed by Kunter et al. (2002), e.g. “I know that I can succeed in doing the things that are required from me at school.”

The answering format of these three scales were given on a four-point rating scale ranging from 0 (not at all true), 1 (somewhat true), 2 (mostly true), to 3 (very true).

Academic Achievement comprised six questions about the grades in the final school report and in the most recent exam in math, German, and English. In Austria grades range from 1 (excellent) to 5 (failed). The results of these values were recoded: Higher numbers imply better academic achievement.

Peer Nomination Measures

Reciprocal Friendships. Adolescents were asked “Who are your best friends in your class?” They could select up to three best friends from the class list containing all names - except of the nominating person - of the peers in their class. Adolescents had a reciprocal friendship when two adolescents choose each other as best friend.

Perceived Popularity and Perceived Unpopularity. Adolescents were asked “Who are the most popular kids in your class? / Who are the least popular kids in your class?” They could select up to three names from the class list. To control for class sizes, the number of nominations were divided by the number of peers present at the day of data collection.

Data Analysis Strategy

Latent profile analysis (LPA; Collins & Lanza, 2010) were estimated using Mplus 7.3 (Muthen & Muthen, 1998–2015). Three fit indices as well as theoretical considerations were used for the decision of the most appropriate profile solution: the Bayesian Information Criterion (BIC; Schwarz, 1978), entropy, and the Lo-Mendell-Rubin Likelihood Ratio Test (LMR-LRT). While the decrease in the BIC is an indicator for a better model fit, a high value of entropy, ranging from 0 to 1, indicates a better accuracy of classification. The LMR-LRT test provides a p value that can be used to determine if there is a statistically significant improvement in fit for the inclusion of one or more classes (Nylund et al., 2007, p. 538). Missing data were addressed using full information maximum likelihood estimation under the Missing at Random (MAR) assumption. After deciding for the best model solution, class memberships were saved and exported to SPSS 23. Finally, a multiple group model with bully-victim groups of adolescents was calculated in Mplus 7.3 (Muthen & Muthen, 1998–2015) to identify the relation between peer and school related variables on depression in groups of adolescents. Gender and immigrant status were included in the model as control variables.

Results

Groups of Bullies and Victims

In a first step LPA analysis with four to six profiles were calculated (Table 1). Comparing the BIC values a six profile solution seemed to provide the best model fit. According to the entropy value (0.97) a four profile solution seemed to be a more accurate classification. However, the entropy in the five profile solution (0.95) and in the six profile solution (0.93) was also close to one and the LMR-LRT test produced no significant p-values for all models. Thus, we inspected the mean values of the different profiles and interpreted them theoretically. In the four profile solution non-involved adolescents, bullies, victims, and bully-victims could be identified. In the five profile solution two groups of victims could be identified: moderate victims (11%), and severe victims (3%). The other three groups were labeled as non-involved (74%), bully (9%), and bully-victim group (3%). In the six profile solution a further bully-victim group could be identified with high levels of victimization and moderate levels of bullying. As the five profile solution already contained a bully-victim group, we decided to use the five profile solution for our further analyses.

Table 1

Means and Standard Deviations for Different Forms of Victimization and Aggression: LPA Models 4-6 Group Solutions

	N (%)	Overt	Relational	Bullying	Overt	Relational	Bullying	BIC /	Entropy
		aggression	aggression	perpetration	victimization	victimization	victimization	LMR-LRT
4 group solution								14895.09 /	0.97
Non-involved	1137 (78.5)	0.27 (0.36)	0.19 (0.25)	0.31 (0.38)	0.31 (0.47)	0.31 (0.41)	0.45 (0.49)	p = .262
Bully	143 (9.9)	1.79 (0.70)	0.80 (0.57)	1.43 (0.84)	0.85 (0.86)	0.40 (0.42)	0.83 (0.68)
Victim	129 (8.9)	0.68 (0.71)	0.42 (0.46)	0.91 (0.77)	2.01 (1.15)	1.89 (0.94)	2.62 (0.77)
Bully-Victim	39 (2.7)	2.97 (1.08)	2.71 (0.78)	1.81 (1.28)	1.21 (1.33)	1.12 (0.94)	1.20 (1.00)
5 group solution								14573.03 /	0.95
Non-involved	1074 (74.2)	0.27 (0.36)	0.18 (0.26)	0.30 (0.38)	0.28 (1.25)	0.26 (0.34)	0.39 (0.42)	p = .410
Bully	128 (8.8)	1.89 (0.65)	0.78 (0.56)	1.43 (0.88)	0.87 (0.92)	0.34 (0.34)	0.76 (0.64)
Moderate Victim	153 (10.6)	0.55 (0.57)	0.34 (0.38)	0.75 (0.58)	1.39 (1.01)	1.15 (0.57)	1.99 (0.81)
Severe victim	51 (3.5)	0.66 (0.69)	0.53 (0.51)	0.91 (0.90)	2.18 (1.25)	2.97 (0.67)	2.83 (0.77)
Bully-Victim	42 (2.9)	2.91 (1.06)	2.63 (0.81)	1.83 (1.25)	1.24 (1.36)	1.14 (0.91)	1.23 (1.05)
6 group solution								14241.49 /	0.93
Non-involved	1017 (70.2)	0.26 (0.34)	0.18 (0.24)	0.30 (0.37)	0.27 (0.41)	0.22 (0.28)	0.35 (0.02)	p = .445
Bully	130 (9)	1.75 (0.63)	0.82 (0.57)	1.27 (0.81)	0.64 (0.62)	0.31 (0.33)	0.64 (0.05)
Moderate Victim	159 (11)	0.29 (0.36)	0.26 (0.32)	0.52 (0.47)	0.82 (0.73)	1.21 (0.52)	1.66 (0.04)
Severe victim	47 (3.2)	0.59 (0.61)	0.51 (0.52)	0.77 (0.72)	2.11 (1.26)	3.03 (0.65)	2.84 (0.07)
Bully-Victim (severe)	57 (3.9)	1.53 (0.92)	0.55 (0.50)	1.61 (0.93)	2.63 (0.91)	1.00 (0.63)	2.34 (0.07)
Bully (severe) -Victim	38 (2.6)	2.96 (1.09)	2.74 (0.78)	1.78 (1.28)	1.16 (1.30)	1.11 (0.94)	1.10 (0.08)

Table 2

Affiliation to Latent Classes by Gender, Class Level, and Ethnicity

Group	n	Non-	Bully	Moderate	Severe	Bully-	χ ²	df	p
		involved		victim	victim	victim
Gender							21.83	4	<.001
Girl	705	78.4	5.8	10.5	3.3	2.0
Boy	743	70.1	11.7	10.6	3.8	3.8
Class level							16.39	12	.17
5th grade	205	73.2	4.9	13.7	4.9	3.4
6th grade	487	73.7	9.0	10.9	4.3	2.1
7th grade	387	73.1	9.8	11.1	2.1	3.9
8th grade	369	76.4	9.8	7.9	3.3	2.7
Immigrant Status							0.45	8	.452
Non-immigrant	666	72.5	9.2	11.3	3.8	3.3
First generation immigrant	262	77.5	5.3	10.3	3.4	3.4
Second generation immigrant	515	74.8	10.1	9.7	3.3	2.1

As shown in Table 2, the five groups were equally distributed in immigrant groups and grades. However, the proportion of male and female adolescents were differently distributed in the five groups, χ²(4) = 21.83, p < .001 with higher proportion of male adolescents in the bully and bully-victim group.

Level Differences in Groups of Bullies and Victims

For all dependent variables separate univariate 5×2×3 ANOVAs with groups of bullies and victims, gender, and immigrant status as factors and subsequent Alpha corrected Bonferroni post tests were conducted (Table 3).

Table 3

Means and Standard Deviations: Depression, Peer Relations, and Academic Variables

	Non-	Bullies	Moderate	Severe	Bully-	Girls	Boys	Natives	First	Second
	involved		victims	victims	victims				generation	generation
N	1074	128	153	51	42	705	746	666	265	515
Depression	0.43^c	0.62^b	0.67^b	0.96^a	0.83^a,b	0.50	0.50	0.49	0.54	0.49
Peer Relations
Reciprocal friends	1.56^a	1.41^a	1.39^a	0.83^b	1.34^a,b	1.60	1.41	1.56	1.35	1.49
Perceived popularity	0.10	0.12	0.08	0.07	0.11	0.10	0.10	0.10	0.10	0.10
Perceived unpopularity	0.07^c	0.08^b,c	0.14^b	0.30^a	0.14^b,c	0.08	0.10	0.10^a	0.10^a	0.08^b
Academic Variables
School liking	1.77^a	1.48^b,c	1.54^b	1.27^b,c	1.12^c	1.76	1.62	1.46^a	2.00^b	1.83^c
Motivation	1.56^a	1.25^a,b	1.49^a,b	1.71^a	1.16^b	1.50	1.53	1.26^a	1.83^b	1.71^b
Academic Self Efficacy	2.47	2.33	2.40	2.40	2.43	2.41	2.47	2.43	2.38	2.48
Grades Mean	3.15	3.09	3.14	3.22	3.10	3.16	3.04	3.18	3.03	3.15

Note. Means with different letters differ at the p < .05 level; ad grades: the higher grades, the better.

Depression

Results revealed a significant effect on groups of bullies and victims, F(4, 1277) = 45.91, p < .001, η² = 0.13. The other effects were non-significant. Non-involved adolescents indicated lowest level of depression. Bullies and moderate victims indicated lower levels of depression compared to severe victims. Bullies, moderate victims, and bully-victims did not differ in level of depression.

Reciprocal Friendships

There was a significant main effect of groups of bullies and victims, F(4, 1374) = 5.16, p < .001, η² = 0.02. No other effects were significant. Non-involved adolescents, bullies, and moderate victims had more reciprocal friendships compared to severe victims. There was no significant difference in reciprocal friendships between bully-victims and the other groups.

Perceived Unpopularity

There was a significant main effect of groups of bullies and victims, F(4, 1406) = 23.44, p < .001, η² = 0.06. Non-involved adolescents were perceived less unpopular compared to moderate and severevictims. Bullies and moderate victims were perceived less unpopular compared to severe victims. There was a significant main effect of immigrant status, F(2, 1406) = 5.55, p = .004, η² = .01. Second generation immigrant adolescents were perceived less unpopular compared to non-immigrant adolescents. There was a significant interaction effect group×immigrant status, F(8, 1406) = 2.87, p = .004, η² = .02 (see Table 3). Moderate victims (M = 0.09, SD = 0.13) and bully-victims (M = 0.07, SD = 0.11) in second generation immigrant adolescents were perceived less unpopular compared to moderate victims (M = 0.17, SD = 0.22) and bully-victims (M = 0.18, SD = 0.21) in non-immigrant adolescents and moderate victims (M = 0.18, SD = 0.20), and bully-victims (M = 0.16, SD = 0.17) in first generation immigrant adolescents. Severe victims (M = 0.16, SD = 0.14) in first generation immigrant adolescents were perceived less unpopular compared to severe victims (M = 0.35, SD = 0.30) in non-immigrant, and severe victims (M = 0.30, SD = 0.27) in second generation immigrant adolescents.

School Liking

There was a significant main effect of groups of bullies and victims, F(4, 1368) = 9.37, p < .001, η² = .03. Non-involved adolescents reported highest level of school liking. Moderate victims reported higher level of school liking compared to bully-victims. There was a significant main effect of immigrant status, F(2, 1368) = 12.85, p < .001, η² = .02. Non-immigrant adolescents reported lower levels of school liking compared to first and second generation immigrant adolescents.

School Motivation

There was a significant main effect of groups of bullies and victims, F(4, 1361) = 4.05, p = .003, η² = .01. Non-involved adolescents and severe victims indicated higher level of motivation compared to bully-victims. There was a significant main effect of immigrant status, F(2, 1361) = 12.35, p < .001, η² = .02. Non-immigrant adolescents indicated lower levels of motivation compared to first and second generation immigrant adolescents. No significant effects were found for perceived popularity, academic self-efficacy, and grades.

Associations between Peer Relations and Academic Variables with Depression in Groups of Bullies and Victims

As shown in Table 4, the associations differed in the five groups of bullies and victims. In non-involved adolescents being a first or a second generation immigrant was positively related to depression. School liking, academic self-efficacy, and grades were negatively associated with depression. In bullies perceived unpopularity was positively related to depression. Grades were negatively associated with depression. In moderate victims being a girl was positively associated with depression. Academic self-efficacy and motivation were negatively associated with depression. Reciprocal friendships and perceived unpopularity were negatively associated with depression in severe victims. Being female was positively associated with depression in severe victims. In bully-victims school liking was negatively associated with depression.

Table 4

Associations Between Peer Relations and Academic Variables with Depression Moderated by Groups of Bullies and Victims

	Non-involved		Bullies		Moderate victims		Severe victims		Bully-victims
N	1015		118		140		45		37
	B	SE	B	SE	B	SE	B	SE	B	SE
Socio demographic variables
Gender^a	–0.02	0.03	–0.07	0.08	–0.20*	0.08	–0.25*	0.13	–0.18	0.18
1st Generation Immigrant^b	0.14***	0.04	0.16	0.09	–0.01	0.09	–0.02	0.18	–0.03	0.18
2nd Generation Immigrant^b	0.10**	0.03	–0.10	0.09	–0.02	0.08	0.19	0.14	0.09	0.25
Peer Relations
Reciprocal friends	–0.05	0.03	–0.01	0.11	–0.11	0.10	–0.42**	0.11	0.07	0.19
Perceived Popularity	–0.01	0.03	–0.03	0.07	–0.06	0.07	0.03	0–11	0.10	0.21
Perceived Unpopularity	0.06	0.04	0.25*	0.10	–0.11	0.08	–0.31*	0.15	–0.00	0.18
Academic variables
School liking	–0.23***	0.05	–0.18	0.11	–0.11	0.10	–0.07	0.18	–0.40*	0.17
Academic Self Efficacy	–0.16***	0.04	–0.12	0.13	–0.27**	0.09	0.01	0.13	–0.19	0.25
Motivation	–0.01	0.05	0.06	0.11	–0.22*	0.09	–0.22	0.13	0.20	0.19
Grades Mean	–0.15***	0.04	–0.30**	0.09	–0.12	0.07	0.09	0.17	–0.10	0.15
R²	0.15***	0.03	0.29**	0.08	0.24***	0.06	0.35**	0.13	0.25	0.17

Note. *p < .05, **p < .01, ***p < .001. Reported regression coefficients are standardized. ^aReference group is girl, ^bReference group is Austrian native students.

Moderating effects of group membership were investigated by testing the difference in regression slopes between the five different groups for statistical significance. The association between reciprocal friendship and depression was significantly stronger in severe victims compared to bullies (b = 0.121, p = .013) and to non-involved adolescents (b = –0.108, p = .001). Also the association between unpopularity and depression were significantly stronger related in bullies compared to victims (b = –0.693, p = .005). The negative association was significantly stronger in severe victims compared to bullies (b = –0.914, p = .002) and to non-involved adolescents (b = –0.914, p = .002).

There were no significant differences in the associations between academic self-efficacy and depression between non-involved and severe victims or moderate victims. Associations between motivation and depression were stronger related to victims compared to bullies (b = –0.108, p = .049) and non-involved adolescents (b = –0.082, p = .028). Finally, associations between grades and depression were stronger in bullies compared to severe victims (b = –0.164, p = .030).

Discussion

This study compared different groups of bullies and victims regarding depression, peer relationships, and academic variables, and explored whether the associations between depression and these variables differ in groups of bullies and victims. To capture some of the heterogeneity within these groups of bullies and victims, we assessed both overt and relational forms of bullying and victimization. In addition, the frequency of bullying and victimization was also taken into account in the latent profile analyses that yielded a five-group solution: non-involved adolescents, bullies, moderate victims, severe victims, and bully-victims. Importantly, the present study identified moderate and severe victims and demonstrated that victims are not one homogenous group (Giang & Graham, 2008; Nylund et al., 2007). As expected boys were overrepresented in the groups of bullies and bully-victims compared to girls (e.g., Walsh & Cosma, 2016) and immigrant and non-immigrant adolescents were equally distributed in these groups (Stefanek et al., 2011).

Depression, Peer Relations, and Academic Variables in Groups of Bullies and Victims

The five groups differed with respect to depression, peer relations, and academic variables in meaningful ways. As expected, non-involved adolescents showed lowest levels of depression compared to the other groups. Bullies and moderate victims had lower levels of depression compared to severe victims (van der Ploeg et al., 2015) and bully-victims (e.g., Haynie et al., 2001). These findings are in line with the cumulative risk model (Gutman et al., 2003) as severe victims and bully-victims are more frequently exposed to a larger number of different forms of bullying and victimization compared to the other three groups.

Contrary to our expectations and to previous findings (e.g., Kochel et al., 2015; Scholte et al., 2009) only severe victims had fewer reciprocal friends compared to non-involved, bullies, and moderate victims. Non-involved, bullies, moderate victims, and bully-victims did not differ regarding their number of reciprocal friends. We assume that methodological differences between studies account for these differences. While Scholte et al. (2009) only compared non-involved, victims, and bully-victims, Kochel et al. (2015) allowed youth to nominate up to five (and not three) friends. In any case, the present results clearly demonstrate that it is important to distinguish moderate and severe victims as their reciprocal friendships differ from the other groups.

Results revealed that the five groups of bullies and victims did not differ with respect to perceived popularity but with respect to perceived unpopularity. Again, severe victims were perceived as most unpopular, followed by moderate victims and bully-victims. It could be that negative peer relations such as unpopularity or rejection, which are an important precursor for victimization, are more visible compared to positive relations like popularity, leading to higher numbers of unpopularity nominations in the three victimized groups (Sentse et al., 2015).

Non-involved adolescents showed highest level of school liking compared to the other groups. Bullies, moderate victims, and severe victims did not differ regarding their level of school liking, but bully-victims had significantly lower levels of school liking compared to bullies and victims. These results are in line with previous studies (Beran et al., 2008). Non-involved adolescents and severe victims had significantly higher levels of motivation compared to bullies and bully-victims. Moderate victims did not differ regarding school motivation compared to the other groups. These results are interesting as they show that in spite of their frequent victimization severe victims are still motivated on academic tasks. In line with Bergsmann et al. (2011) bullies showed lower levels of motivation compared to victims. Contrary to previous results the groups did neither differ regarding their academic self-efficacy (Thijs & Verkuyten, 2008) nor grades (e.g., Spriggs et al., 2007). To sum up, there is variation in these groups regarding depression, peer relations, and academic variables and an interesting pattern could be identified. Concerning depression and peer relations, moderate victims were more similar to bullies compared to severe victims, while the latter were more similar to bully-victims. Regarding school variables, moderate victims and severe victims were more similar compared to bullies and bully-victims. These results highlight the importance of applying a person-centered approach to capture the heterogeneity of young people involved in bullying andvictimization.

Associations of Peer Relationships and Academic Variables with Depression in Different Groups of Bullies and Victims

As this was the first study which investigated peer relations and academic variables as correlates of depression in different groups of bullies and victims our analyses were mainly exploratory. Among the five groups of youth, different variables were associated with depression. In line with our expectations reciprocal friendships were negatively related to depression in severe victims, which underlines the protective function of a friend (Hodges et al., 1999). Perceived popularity was not associated with depression in any group and perceived unpopularity was only among bullies positively related to depression. Surprisingly, perceived unpopularity was significantly negatively related to depression in severe victims. However, as many of these severe victims were highly depressed it could be that some of them receive no or only few unpopularity nominations, leading to this negative relation. Academic variables were strongest related to depression in non-involved adolescents and to some degree in moderate victims, confirming our hypothesis that academic variables are more influential compared to peer variables for adolescents who are less involved in bullying. Regarding sociodemographic variables being a girl was significantly related to depression in moderate and severe victims, indicating that victimization has a greater impact on girls psychological well-being compared to boys. Only in non-involved youth being a first or second generation immigrant was positively related to depression. This is in line with previous studies where immigrant adolescents were more vulnerable for depression (Stefanek, Fandrem, Strohmeier, & Spiel, 2012). Importantly, immigrant status was not related to depression among bullies, moderate or severe victims and bully-victims.

Limitations and Practical Implications

As our study was cross-sectional we could only investigate correlates of depression but are not able to make any inferences regarding the directions of these effects. Thus, we cannot provide evidence whether peer relations and /or academic variables cause depression, or whether depressive adolescents are less successful in building up positive peer relations and doing badly at school. Most likely, there is a dynamic interplay between these variables (Sentse et al., 2015). Thus, short term longitudinal studies with multiple measurement points are needed to investigate the temporal associations between these constructs. Furthermore, we used only self-reports to assess aggressive behaviour and victimization. However, as we combined self-reports and peer nominations we could compare these results and found evidence that severe victims had fewest friends and were perceived as most unpopular, which is in line with previous results.

Although we considered manifold forms of bullying and victimization, we did not include all possible forms like cyberbullying or bias-based bullying (Gradinger, Strohmeier, & Spiel, 2009). Thus, to include even more forms of bullying and victimization would be an important extension for future studies.

For violence prevention and intervention programs it might be useful to adapt their measures to the specific needs of each subgroup. For example, it would be important to empower severely victimized children to build up positive peer relations but also to provide a support structure for them on school level. Furthermore, when measuring program effectiveness the differential influence on specific subgroups need to be considered (Farrell, Henry, & Bettencourt, 2011).

Footnotes

Acknowledgments

We thank all schools, teachers and students who participated in the presents study. We are very grateful to the whole ViSC project team consisting of Dagmar Strohmeier, Christiane Spiel, Petra Gradinger, Takuya Yanagida, Elisabeth Stefanek, Eva-Maria Schiller, Christoph Burger, Bianca Pollhammer, Katharina Derndarsky, Marie Therese Schultes and Christine Hoffmann for their invaluable work during data collection. The writing of the present study has been supported by the Oesterrreichische Nationalbank Anniversary Fund, project number 16605 and by the Platform for Intercultural Competences, University of Applied Sciences Upper Austria (PI: Dagmar Strohmeier).

References

Beran

, Hughes

, & Lupart

(2008). A model of achievement and bullying: Analyses of the Canadian national longitudinal survey of children and youth data. Educational Research, 50, 25–39. doi: 10.1080/00131880801920379

Bergsmann

E. M.

, Finsterwald

, Strohmeier

, & Spiel

(2011). Motivation und Selbstreguliertes Lernen in SchülerInnengruppen mit unterschiedlicher Aggressionserfahrung [Academic motivation and self-regulated learning in stable bullies, victims, bully-victims, and non-participants]. Zeitschrift für Entwicklungspsychologie und Pädagogische Psychologie, 43, 89–98. doi: 10.1026/0049-8637/a000038

Berkowitz

, de Pedro

K. T.

, & Gilreath

T. D.

(2014). A latent class analysis of victimization among middle and high school students in California. Journal of School Violence, 14, 316–333. doi: 10.1080/15388220.2014.980424

Bettencourt

, & Farrell

A. D.

(2013). Individual and contextual factors associated with patterns of aggression and peer victimization during middle school. Journal of Youth and Adolescence, 42, 285–302. doi: 10.1007/s10964-012-9854-8

Brunstein-Klomek

, Marrocco

, Kleinman

, Schonfeld

I. S.

, & Gould

M. S.

(2007). Bullying, depression, and suicidality in adolescents. Journal of the American Academy of Child and Adolescents Psychiatry, 46, 40–49. doi: 10.1097/01.chi.0000242237.84925.18

Caravita

, Di Blasio

, & Salmivalli

(2009). Unique and interactive effects of empathy and social status on involvement in bullying. Social Development, 18, 140–163. doi: 10.1111/j.1467-9507.2008.00465.x

Collins

L. M.

, & Lanza

S. T.

(2010), Latent class and latent transition analysis: With applications in the social, behoral, and health sciences. New York: Wiley.

Crick

N. R.

, & Grotpeter

J. K.

(1995). Relational aggression, gender, and social-psychological adjustment. Child Development, 66, 710–722. doi: 10.1111/j.1467-8624.1995.tb00900.x

de Bruyn

E. H.

, Cillessen

A. H. N.

, & Wissink

I. B.

(2010). Associations of peer acceptance and perceived popularity with bullying and victimization in early adolescence. Journal of Early Adolescence, 30, 543–566. doi: 10.1177/0272431609340517

10.

Espinoza

, Gonzales

N. A.

, & Fuligni

A. J.

(2013). Daily school peer victimization experiences among Mexican-American adolescents: Associations with psychosocial, physical, and school adjustment. Journal of Youth and Adolescence, 42, 1775–1788. doi: 10.1007/s10964-012-9874-4

11.

Farrell

A. D.

, Henry

D. B.

, & Bettencourt

(2011). Methodological challenges examining subgroup differences: Examples from universal school-based youth violence prevention trials. Prevention Science, 14, 121–133. doi: 10.1007/s11121-011-0200-2

12.

Feldman

M. A.

, Ojanen

, Gesten

E. L.

, Smith-Schrandt

, Brannick

, Totura

C. M. W.

, &... Brown

(2014). The effects of middle school bullying and victimization on adjustment through high school: Growth modeling of achievement, school attendance, and disciplinary trajectories. Psychology in the Schools, 51, 1046–1062. doi: 10.1002/pits.21799

13.

Giang

M. T.

, & Graham

(2008). Using latent class analysis to identify aggressors and victims of peer harassment. Aggressive Behavior, 34, 203–213. doi: 10.1002/ab.20233.

14.

Goldweber

, Waasdorp

T. E.

, & Bradshaw

C. P.

(2013). Examining associations between race, urbanicity, and patterns of bullying involvement. Journal of Youth and Adolescence, 42, 206–219. doi: 10.1007/s10964-012-9843-y

15.

Graber

J. A.

, & Brooks-Gunn

(1996). Transitions and turning points: Navigating the passage from childhood through adolescence. Developmental Psychology, 32, 768–776. doi: 10.1037/0012-1649.32.4.768

16.

Gradinger

, Strohmeier

, & Spiel

(2009). Traditional bullying and cyberbullying: Identification of risk groups for adjustment problems. Zeitschrift für Psychologie / Journal of Psychology, 217, 205–213. doi: 10.1027/0044-3409.217.4.205

17.

Gutman

L. M.

, Sameroff

A. J.

, & Cole

(2003). Academic growth curve trajectories from 1st grade to 12th grade: Effects of multiple social risk factors and preschool child factors. Developmental Psychology, 39, 777–790. doi: 10.1037/0012-1649.39.4.777

18.

Haynie

D. L.

, Nansel

, Eitel

, Crump

A. D.

, Saylor

, Yu

, & Simons-Morton

(2001). Bullies, victims, and bully/victims: Distinct groups of at-risk youth. Journal of Early Adolescence, 21, 29–49. doi: 10.1177/0272431601021001002

19.

Hodges

E. V. E.

, Boivin

, Vitaro

, & Bukowski

W. M.

(1999). The power of friendship: Protection against an escalating cycle of peer victimization. Developmental Psychology, 35, 94–101. doi: 10.1037/0012-1649.33.6.1032

20.

Huang

(2015). Academic achievement and subsequent depression: A meta-analysis of longitudinal studies. Journal of Child and Family Studies, 24, 434–442. doi: 10.1007/s10826-013-9855-6

21.

Hymel

, & Swearer

S. M.

(2015). Four decades of research on school bullying. An introduction. American Psychologist, 70, 293–299. doi: 10.1037/a0038928

22.

Juvonen

, & Graham

(2014). Bullying in schools: The power of bullies and the plight of victims. Annual Review of Psychology, 65, 159–185. doi: 10.1146/annurev-psych-010213-115030

23.

Kandel

D. B.

, & Davies

(1982). Epidemiology of depressed mood in adolescents: An empirical study. Archives of General Psychiatry, 39, 1205–1212.

24.

Kochel

K. P.

, Ladd

G. W.

, Bagwell

C. L.

, & Yabko

B. A.

(2015). Bully/victim profiles’ differential risk for worsening peer acceptance: The role of friendshi. Journal of Applied Developmental Psychology, 41, 38–45. doi: 10.1016/j.appdev.2015.05.002

25.

Kovacs

(1985). The Children’s Depression Inventory (CDI). Psychopharmacology Bulletin, 2, 995–998.

26.

Kunter

, Schürmer

, Artelt

, Baumert

, Klieme

, Neubrand

, ... Weiß

(2002). PISA 2000: Dokumentation der Erhebungsinstrumente[PISA 2000: Documentation of the measures]. Berlin: Max-Planck-Institut für Bildungsforschung, 72. Retrieved from http://edoc.mpg.de/14414

27.

Muthen

L. K.

, & Muthen

B. O.

(1998–2015). Mplus user’s guide. (7th ed). Los Angeles, CA: Muthen & Muthen.

28.

Nakamoto

, & Schwartz

(2010). Is peer victimization associated with academic achievement? A meta-analytic review. Social Development, 19, 221–242. doi: 10.1111/j.1467-9507.2009.00539.x

29.

Nangle

D. W.

, Erdley

C. A.

, Newman

J. E.

, Mason

C. A.

, & Carpenter

E. M.

(2003). Popularity, friendship quantity, and friendship quality: Interactive influences on children’s loneliness and depression. Journal of Clinical Child & Adolescent Psychology, 32, 546–555. doi: 10.1207/S15374424JCCP3204_7

30.

Newcomb

A. F.

, & Bagwell

C. L.

(1995). Children’s friendship relations: A meta-analytic review. Psychological Bulletin, 117, 306–347. doi: 10.1037/0033-2909.117.2.306

31.

Nylund

, Bellmore

, Nishina

, & Graham

(2007). Subtypes, severity, and structural stability of peer victimization: What does latent class analysis say?Child Development, 78, 1706–1722. doi: 10.1111/j.1467-8624.2007.01097.x

32.

Olweus

(1993), Bullying at school: What we know and what we can do. Oxford: Blackwell Publishers.

33.

Pellegrini

A. D.

, & Long

J. D.

(2002). A longitudinal study of bullying, dominance, and victimization during the transition from primary school through secondary school. British Journal of Developmental Psychology, 20, 259–280. doi: 10.1348/026151002166442

34.

Prinstein

M. J.

, & Cillessen

A. H. N.

(2003). Forms and functions of adolescent peer aggression associated with high levels of peer status. Merrill-Palmer Quarterly, 49, 310–342. doi: 10.1353/mpq.2003.0015

35.

Roland

(1989). A system oriented strategy against bullying. In Roland

& Munthe

(Eds.), Bullying: An international perspective (pp. 143–151). London: David Fulton.

36.

Roland

(2002). Bullying, depressive symptoms and suicidal thoughts. Educational Research, 44, 55–67. doi: 10.1080/00131880110107351

37.

Salmivalli

, Lagerspetz

, Björkqvist

, Österman

, & Kaukiainen

(1996). Bullying as a group process: Participant roles and their relations to social status within the group. Aggressive Behavior, 22, 1–15. doi: 10.1002/(SICI)1098-2337(1996)22:1<1::AID-AB1>3.0.CO;2-T

38.

Schmidt

M. E.

, & Bagwell

C. L.

(2007). The protective role of friendships in overtly and relationally victimized boys and girls. Merill-Palmer Quarterly, 53, 439–460. doi: 10.1353/mpq.2007.0021

39.

Scholte

R. H. J.

, Overbeek

, ten Brink

, Rommes

, de Kemp

R. A. T.

, Goossens

, & Engels

R. C. M. E.

(2009). The significance of reciprocal and unilateral friendships for peer victimization in adolescence. Journal of Youth and Adolescence, 38, 89–100. doi: 10.1007/s10964-008-9287-6

40.

Schwarz

(1978). Estimating the dimension of a model. Annals of Statistics, 6, 461–465.

41.

Sentse

, Kretschmer

, & Salmivalli

(2015). The longitudinal interplay between bullying, victimization, and social status: Age-related and gender differences. Social Development, 24, 659–677. doi: 10.1111/sode.12115

42.

Sentse

, Scholte

, Salmivalli

, & Voeten

(2007). Person-group dissimilarity in involvement in bullying and its relation with social status. Journal of Abnormal Child Psychology, 35, 1009–1019. doi: 10.1007/s10802-007-9150-3

43.

Solberg

M. E.

, & Olweus

(2003). Prevalence estimation of school bullying with the Olweus Bully/Victim Questionnaire. Aggressive Behavior, 29, 239–268. doi: 10.1002/ab.10047

44.

Spiel

, & Strohmeier

(2012). Peer relations in multicultural schools. In Masten

A.S.

, Liebkind

, & Hernandez

D. J.

(Eds)., Realizing the potential of immigrant youth (pp. 376–396). Cambridge: Cambridge University Press.

45.

Spriggs

A. L.

, Iannotti

R. J.

, Nansel

T. R.

, & Haynie

D. L.

(2007). Adolescent bullying involvement and perceived family, peer and school relations: Commonalities and differences across race/ethnicity. Journal of Adolescent Health, 41, 283–293. doi: 10.1016/j.jadohealth.2007.04.009

46.

Stefanek

, Fandrem

, Strohmeier

, & Spiel

(2012). Depressive symptoms in native and immigrant adolescents. The role of critical life events and daily hassles. Anxiety, Stress, and Coping, 25, 201–217. doi: 10.1080/10615806.2011.605879

47.

Stefanek

, Strohmeier

, van de Schoot

, & Spiel

(2011). Bullying and victimization in ethnically diverse schools: Risk and protective factors on the individual and class level. International Journal of Developmental Science, 5, 73–84. doi: 10.3233/DEV-2011-11073

48.

Stiensmeier-Pelster

, Schürmann

, & Duda

(2000). Depressions-Inventar für Kinder und Jugendliche (DIKJ). Handanweisung[Children’s Depression Inventory. Manual] (2nd ed). Göttingen: Hogrefe.

49.

Stipek

, & Miles

(2008). Effects of aggression on achievement: Does conflict with the teacher make it worse?Child Development, 79, 1721–1735. doi: 10.1111/j.1467-8624.2008.01221.x

50.

Strohmeier

, Gradinger

, Schabmann

, & Spiel

(2012). Gewalterfahrungen von Jugendlichen: Prävalenzen und Risikogruppen. [Violence experiences among youth: Prevalence rates and risk groups.] In Eder

(Ed.), PISA 2009. Nationale Zusatzanalysen für Österreich [PISA 2009. National analyses for Austria] (pp. 166–209). Münster: Waxmann.

51.

Strohmeier

, Wagner

, Spiel

, & Von Eye

(2010). Stability and constancy of bully-victim behaviour - Looking at variables and persons. Zeitschrift für Psychologie / Journal of Psychology, 218, 185–193. doi: 10.1027/0044-3409/a000028

52.

Swearer

S. M.

, & Hymel

(2015). Understanding the psychology of bullying. Moving toward a social-ecological diathesis-stress model. American Psychologist, 70, 344–353. doi: 10.1037/a0038929

53.

Thijs

, & Verkuyten

(2008). Peer victimization and achievement in a multiethnic sample: The role of perceived academic self-efficacy. Journal of Educational Psychology, 100, 754–764. doi: 10.1037/a0013155

54.

Ttofi

M. M.

, Farrington

D. P.

, Lösel

, & Loeber

(2011). Do the victims of school bullies tend to become depressed later in life? A systematic review and meta-analysis of longitudinal studies. Journal of Aggression, Conflict and Peace Research, 3, 63–73. doi: 10.1108/17596591111132873

55.

van der Ploeg

, Steglich

, Salmivalli

, & Veenstra

(2015). The intensity of victimization: Associations with children’s psychosocial well-being and social standing in the classroom. PLos One, 10((10)), e0141490. doi: 10.1371/journal.pone.0141490

56.

Walsh

, & Cosma

(2016). Bullying: Being bullied and bullying others. In Inchley

(Ed.), Health Behor in School-aged Children (HBSC) study: International report from the / survey (pp. 197–205). Geneve: WHO.

57.

Walsh

S. D.

, De Clerq

, Molcho

, Harel-Fisch

, Davison

C. M.

, Madsen

K. R.

, & Stevens

G. W. J. M.

(2016). The relationship between immigrant school composition, classmate support and involvement in physical fighting and bullying among adolescent immigrants and non-immigrants in 11 countries. Journal of Youth and Adolescence, 45, 1–16. doi: 10.1007/s10964-015-0367-0

58.

Weichhold

(2002). Evaluation eines suchtpräventiven Lebenskompetenzprogramms [Evaluation of a life skills program against substance misuse]. Unpublished manuscript, University of Jena.

59.

Yang

, & Salmivalli

(2013). Different forms of bullying and victimization: Bully-victims versus bullies and victims. European Journal of Developmental Psychology, 10, 723–738. doi: 10.1080/17405629.2013.793596