The association between peer rejection and aggression types zhang

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Child Abuse & Neglect 135 (2023) 105974
Available online 13 December 2022
0145-2134/© 2022 Elsevier Ltd. All rights reserved.
The association between peer rejection and aggression types: A 
meta-analysis 
Xiao Yue, Qian Zhang * 
Center for Studies of Education and Psychology of Ethnic Minorities in Southwest Area, Southwest University, Chongqing 400715, China 
Department of Early Childhood Education in Faculty of Education, Southwest University, Chongqing 400715, China 
A R T I C L E I N F O 
Keywords: 
Peer rejection 
Aggression 
Overt aggression 
Relational aggression 
meta-analysis 
A B S T R A C T 
Background: Although previous studies have assessed the association between peer rejection and 
aggression, the results are mixed. 
Objective: This article presents a meta-analysis of the association between peer rejection and 
aggression types (overt vs. relational) among children and adolescents. 
Participants and setting: A total of 61 eligible studies with 70 independent effect sizes were 
included in the analysis (45,966 participants, Mage = 10.34, SD = 3.13). 
Methods: First, random-effects meta-analyses were conducted to explore the association between 
peer rejection and aggression types (overt vs. relational). Next, moderation analyses were con-
ducted based on the Q statistics for categorical variables (culture, reporting method of peer 
rejection, reporting method of aggression) and the meta-regression analyses for continuous var-
iable (age). 
Results: Peer rejection was positively correlated with overall aggression (r = 0.42, 95 % CI [0.38, 
0.47], p 0.50) in children and adolescents (Gülay & Önder, 2011; Wang et al., 2014; Zhao et al., 
2013). Evidence from longitudinal studies also reflects this correlation, suggesting that experiences of peer rejection in elementary 
school predict externalizing behavior problems in secondary school, such as physical (overt) aggression and delinquency (Laird et al., 
2001). In particular, one study that tracked 585 children from kindergarten to third grade at 12 different time points has found that 
peer rejection predicts subsequent aggression, both overt and relational. However, the authors also point out that aggression predicts 
later peer rejection (Lansford et al., 2010). These results suggest that the correlation between peer rejection and aggression can be 
bidirectional. According to the Social Information Processing Theory, children who are often rejected by their peers may have higher 
hostile intent attributions that induce aggression (Dodge et al., 2003; Reijntjes et al., 2011). In addition, aggressive children may not be 
accepted by their peers because they violate basic social norms, and peers reject aggressive children in order to conform to these norms 
(Killen & Brenick, 2011). Previous research has also shown that aggressive children are at risk for problem behavior if they are rejected 
by their peers, suggesting that the interaction between peer rejection and aggression may exacerbate externalizing behavior problems 
(Okado & Bierman, 2015). Thus, there is strong evidence that peer rejection is associated with aggression regardless of the specific 
direction of the relationship. 
Some other studies, however, have shown a weak link between peer rejection and aggression. For example, one cross-sectional 
study reported a fairly weak association between peer rejection and aggression types (The r range is − 0.08 to 0.13) among pre-
schoolers in the United States (Ostrov et al., 2013). Another study involving Chinese children reported similar results, with a corre-
lation coefficient of 0.08 (Miao, 2015). These studies suggest that not all aggressive children are rejected by their peers; In contrast, 
some so-called popular aggressive children may be accepted by their peers despite demonstrating both overt aggression and relational 
aggression (Cillessen & Mayeux, 2007). This discrepancy can be attributed to the different attitudes toward aggression in peer groups 
(Rodkin et al., 2000). Certain peer groups, such as those associated with juvenile delinquency, may favor or even encourage aggressive 
behavior, thus making aggressive children more popular. Similarly, children may be encouraged to use relational aggression to 
establish their cliques and manipulate the social dynamics of a group. Importantly, cultural differences influence how children 
perceive aggressive behavior amongShandong Normal 
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	The association between peer rejection and aggression types: A meta-analysis
	1 Introduction
	1.1 The association between peer rejection and aggression
	1.2 Factors that may influence the peer rejection-aggression link
	1.3 The present study
	2 Methods
	2.1 Literature search strategy
	2.2 Inclusion and exclusion criteria
	2.3 Coding
	2.4 Procedure and data analysis
	2.4.1 Primary analyses
	2.4.2 Auxiliary analyses
	3 Results
	3.1 Sample
	3.2 Effect sizes and heterogeneity test
	3.3 Moderation analysis
	3.4 Additional moderation analysis in partial data
	3.5 Publication bias
	4 Discussion
	4.1 Limitations and implications
	5 Conclusions
	CRediT authorship contribution statement
	Declaration of competing interest
	Data availability statement
	Acknowledgments
	References11References marked with an asterisk indicate the studies used in our meta-analysis.their peers (Chen, 2012b). Based on this assumption, it is crucial to assess the association between 
peer rejection and aggression types by highlighting the potential cultural differences among peer groups. 
Although aggression is generally positively associated with peer rejection (e.g., Ji et al., 2012; Murray-Close & Crick, 2006), ev-
idence suggests that the magnitude of this association depends on the aggression subtype (Bowker et al., 2012; Ettekal & Ladd, 2015). 
One meta-analysis has found that direct (e.g., overt) aggression is strongly associated with poor peer relationships in comparison with 
indirect (e.g., relational) aggression (Card et al., 2008). Another longitudinal study has found that while physical (overt) aggression 
predicts subsequent peer rejection (measured at an interval of 3.5 months), relational aggression measured at time 1 does not predict 
peer rejection at time 2 (Godleski et al., 2015). By nature, overt aggression is more directly confrontational than relational aggression 
and is more likely to cause social exclusion. To test this hypothesis, Salmivalli et al. (2000) have reported that peer rejection is 
associated with an increase in overt aggression, but not relational aggression. In contrast, other researchers have claimed that peer 
rejection is more closely related to relational aggression than overt aggression (e.g., Tan, 2009; Wang et al., 2015). Given these in-
consistencies in the extant literature, it is necessary to distinguish the differential effects of aggression types through meta-analysis to 
help identify potential risk factors and outcomes for peer rejection and aggression. 
1.2. Factors that may influence the peer rejection-aggression link 
Several factors may affect the association between peer rejection and aggression types, such as age, culture, and reporting methods. 
First, age is an important factor that may moderate the relationship between peer rejection and aggression (Coie et al., 1982). With the 
development of moral judgment, children can decide whether to punish peers who exhibit antisocial behavior such as aggression 
(Smetana et al., 2012). For example, the association between peer rejection and aggression is stronger for 12th-graders than for 9th- 
graders across adolescence (Beeson et al., 2020). In contrast, younger children may not necessarily reject aggressive peers in envi-
ronments where a certain level of aggression is tolerated, because they may be more susceptible to peer influence than older children. 
For example, one study of 597 American preadolescents aged between 9 and 11 has found that those who used more relational 
aggression are later perceived as more likable by their peers (Kawabata et al., 2014). However, this result was not obtained in a 
longitudinal study of 198 Taiwanese fifth-grade students (Mage = 10.35, SD = 0.31) in which both relational and physical aggression 
were associated with peer rejection (Tseng et al., 2013). Thus, this discrepancy reveals possible cultural differences in the rejection- 
X. Yue and Q. Zhang 
Child Abuse & Neglect 135 (2023) 105974
3
aggression link. 
Second, culture plays a key role in determining the association between peer rejection and aggression (Bass et al., 2016). Conflict, 
including aggressive behavior, is generally avoided in collectivist societies, where social acceptance and group harmony are priori-
tized, while interpersonal conflict is often condoned in individualistic societies (Chen, 2012b). For example, both American men and 
women demonstrate higher levels of direct and indirect aggression than their Chinese counterparts (Forbes et al., 2009). Meanwhile, 
Chinese adolescents who accept more collectivist values display less overt and relational aggression than those who reject these values 
(Li et al., 2010). Thus, we hypothesize that culture (collectivist vs. individualist) will moderate the association between peer rejection 
and aggression. 
Third, reporting method of peer rejection may influence the association between peer rejection and aggression in children (García- 
Bacete et al., 2019). Peer nomination is one of the most commonly used methods to assess a child's social status among their peers (Coie 
et al., 1982), and previous researchers have also used both self- and teacher/parent-reporting methods to assess peer rejection (Crick 
et al., 1997; Smokowski et al., 2016). Children's peer rejection differs significantly among self-report, peer-nomination, and teacher- 
report (Lynch et al., 2016; White & Kistner, 2011). Specifically, the association between self-reported rejection and aggression is not as 
strong as the association between peer-nominated rejection and aggression (Zimmer-Gembeck et al., 2013). Therefore, it is necessary 
to consider the reporting method of peer rejection (self-report vs. peer-nomination vs. adult-report) when evaluating the association 
between peer rejection and aggression, as the reporting method of peer rejection may moderate this association. 
Finally, reporting method of aggression (e.g., self-report vs. peer-nomination vs. adult (teacher/parent)-report vs. observation) may 
also influence the association between peer rejection and aggression (e.g., Crick & Bigbee, 1998; Tur-Porcar et al., 2018; Vlachou et al., 
2013). The association between teacher-reported aggression and peer rejection is stronger than the association between observation- 
based aggression and peer rejection (Ostrov, 2008). In view of this, it is necessary to test whether reporting method of aggression 
affects the association between peer rejection and aggression. 
1.3. The present study 
So far, two meta-analyses have assessed the correlation between peer rejection and aggression, one between peer rejection and 
direct versus indirect aggression (Card et al., 2008), and the other between peer rejection and relational aggression (Casper et al., 
2020). Based on the previous meta-analyses, this study has three objectives: First, our meta-analysis will further expand previous work 
by focusing on specific form of aggression (overt vs. relational) and overall aggression (overt and relational), as aggressive children 
may not only display one type of aggression but also overall aggression, which may be an important indicator of peer rejection 
(Donohue et al., 2020). Next, the second objective is to apply partial correlation in the analysis, whereas the first two meta-analyses 
used semi-partial correlation to test the association between peer rejection and aggression. We used partial correlation in the meta- 
analysis because partial correlation is superior to semi-partial correlation of homogeneity test in the meta-analysis of correlational 
data (Aloe, 2013). Finally, the third objective is to test whether age, reporting methods, and culture moderate the association between 
peer rejection and aggression. Specifically, we will report age effects, reporting method of peer rejection, and reporting method of 
aggression in our analysis of the association between peer rejection and aggression. Most importantly, our meta-analysis also includes 
research data from collectivist (e.g., China) and individualist (e.g., the United States) samples, which allows us to assess cross-cultural 
differences. 
2. Methods 
2.1. Literature search strategy 
To identify relevant research literature, we used a three-step method to search the literature published between 2000 and 2021. It 
should be noted that we chose the past two decades as the time frame for the literature because there is a growing body of research 
work on the association between peer rejection and aggression during this period. Thus, it is necessary for us to use this time frame to 
systematically analyze and summarize the previous research results. In step 1, articles in the Englishlanguage were retrieved through a 
detailed search of PsycINFO, PsycArticles, Web of Science (e.g., Medline), Google Scholar, Sociological Abstracts, and ProQuest 
Dissertations & Theses. Three major Chinese academic electronic databases were also used, including China National Knowledge 
Internet, Chongqing VIP Information and Wanfang Database. The search keywords were as follows: peer rejection, rejected children, 
social exclusion, excluded children, disliked children, aggression, aggressive behaviors, bullying, cyberbullying and bullying behav-
iors. In step 2, references of each article were retrieved to avoid losing any valid data. In step 3, several dissertations and unpublished 
research papers were obtained through personal contacts with the authors. 
2.2. Inclusion and exclusion criteria 
The initial literature search returned 5353 citations. After examining the titles and abstracts of all the articles and discarding the 
apparently irrelevant studies, a total of 770 studies were considered appropriate for further examination. The inclusion criteria were as 
follows: (a) Studies must use quantitative research methods; (b) Studies must report statistical data such as sample size and Pearson's 
correlation coefficient; (c) Participants must be children and adolescents aged 3 to 18; and (d) Studies must be published either in 
English or Chinese. Studies were excluded if they (a) were review articles; (b) reported social preference to indicate social status, 
because social preference is more closely related to peer acceptance than to peer rejection (Manring et al., 2018); and (c) reported 
X. Yue and Q. Zhang 
Child Abuse & Neglect 135 (2023) 105974
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individual peer relationships (e.g., one-on-one friendship). If multiple studies used the same sample, only one study was included. 
Following these criteria, 61 studies were finally selected for meta-analysis (see Fig. 1). 
2.3. Coding 
Table 1 showed the characteristics of eligible studies, all of which were independently coded. The first author and a graduate 
student encoded all information according to the coding manual, which specified the coding categories and possible codes to be used 
for each study. Agreement reached 96 % of the two coders' coding, and all disagreements were resolved by consensus. The criteria used 
to obtain the effect size were as follows: (a) The cross-sectional effect size of each type of aggression and peer rejection was included in 
the analysis; (b) If a study reported multiple outcomes of the same construct, the simple average correlation coefficient was calculated 
(e.g., separate effect sizes for different sub-types of aggression were combined into an overall mean effect size, while the effect sizes for 
physical and verbal aggression were combined into an overall effect size for overt aggression) (Anderson et al., 2010); (c) If a study 
simultaneously reported several independent samples, then each sample was included separately (e.g., two independent data points 
were collected if a study reported the Pearson's correlation coefficients separately by sex); (d) For longitudinal studies, the effect size 
was calculated at baseline; (e) Based on the Cultural Dimension Theory (Hofstede et al., 2010), participants from collectivistic societies 
with low individualism (e.g., China, Japan, South Korea) were classified as belonging to collectivist cultures, while participants from 
individualistic societies with high individualism (e.g., the United States, Canada, Germany) were classified as belonging to individ-
ualist cultures. 
n
oitacifit
ne
dI
S
cr
ee
n
in
g
E
li
g
ib
il
it
y
In
cl
u
d
ed
Records identified through 
database searching
(n = 3,582)
Additional records identified 
through Chinese sources
(n = 1,771)
Reviewed abstracts for possible inclusion 
and removed duplicates (n = 4, 538)
Full-text articles 
assessed for eligibility
(n = 345)
Full-text articles excluded 
(n = 345)
Not measure peer rejection and 
aggression/bullying: 233
Age under 3 and over 18: 56
Studies reporting social 
preference: 27
Studies reporting individual peer 
relationship: 29
Reports included in 
quantitative synthesis 
(meta-analysis)
(n = 61)
Full articles roughly read (n = 770)
Articles excluded 
(n = 425)
No relevant articles: 241
Not an empirical study: 150
Could not obtain/not in English 
or Chinese: 34
Fig. 1. Flow of literature search and screening for study inclusion. 
X. Yue and Q. Zhang 
Child Abuse & Neglect 135 (2023) 105974
5
Table 1 
Original studies included in the meta-analysis of the association between peer rejection and aggression. 
Author (s) Country Year Publication 
state 
Sample 
size 
Male 
(%) 
Age Peer rejection 
measure 
Aggression 
measure 
r 
Barnow, Lucht, & 
Freyberger, 
Germany 2005 Yes 168 48% 14.48 YSR, CBCL YSR, CBCL 0.36 
Beeson, Brittain, & 
Vaillancourt Canada 2020 Yes 544 45% 14.96 BASC-2 SRP-A ABS 0.28 
Blair et al. USA 2016 Yes 338 45% 7 PN PN 0.49 
Bowker et al. India 2012 Yes 194 52% 13.35 PN PN 0.56 
Chen, Cen, Li, & He China 2005 Yes 266 51% Grade 4 PN RCP 0.68 
Chen USA 2012a No 678 53.2 6.20 TOCA TOCA 0.50 
Chu, Zhou, Fan China 2020 Yes 703 59% 13.37 PN E-BS 0.39 
Coplan, Closson, & Arbeau Canada 2007 Yes 139 53% 5.40 CBS CBS 0.27 
Dick Canada 2017 No 615 46% Grade 7 BASC-2 ABS 0.24 
Dijkstra, Lindenberg, & 
Veenstra (a) Netherlands 2008 Yes 1675 100% 14.02 PN PN 0.42 
Dijkstra, Lindenberg, & 
Veenstra (b) 
Netherlands 2008 Yes 1637 0% 14.02 PN PN 0.29 
Dishion, Véronneau, & 
Myers 
Canada 2010 Yes 998 53% 11-12 PN SR 0.11 
Donohue, Tillman, & Luby USA 2020 Yes 129 - 13.20 HBQ HBQ 0.29 
Ettekal & Ladd (a) USA 2015 Yes 240 0% 10 PN PN 0.54 
Ettekal & Ladd (b) USA 2015 Yes 237 100% 10 PN PN 0.48 
Gao et al.(a) China 2010 Yes 208 53.37% 10.65 PN RCP 0.57 
Gao et al.(b) China 2010 Yes 190 50.53% 14.97 PN RCP 0.61 
García-Bacete et al. Spain 2019 Yes 809 - 6.39 PN SSBS 0.57 
Giunta et al. (a) Italy 2018 Yes 269 0% 10 PN mix 0.17 
Giunta et al. (b) Italy 2018 Yes 338 100% 10 PN mix 0.36 
Godleski et al. USA 2015 Yes 97 57% 5.37 PSBS-TF Observation 0.15 
Gorman et al. USA 2011 Yes 418 45% 12.20 PN PN 0.50 
Gülay & Önder Turkey 2011 Yes 150 50% 5-6 CBS CBS 0.64 
Hunter Australia 2005 No 350 48% 11 PN CSBS 0.28 
Janssens et al. USA 2015 Yes 563 48% 13.81 PN YSR 0.09 
Ji et al. China 2012 Yes 1806 50% 11.27 PN PN 0.50 
Kalvin USA 2014 No 1192 66% 5.62 PN TOCA 0.29 
Keresteš & Milanović Croatia 2006 Yes 80 100% 
Grade 4- 
6 PN DIAS 0.23 
Keresteš & Milanović Croatia 2006 Yes 71 0% 
Grade 4- 
6 PN DIAS 0.52 
Kholodova Russia 2011 Yes 295 50% 11.11 PR PNI-PR 0.47 
Khoury-Kassabri et al. Israel 2020 Yes 502 47.4% 3-5 AR PSBS–TF 0.21 
Laird et al. India 2001 Yes 585 48% 5 PN CBC 0.14 
Lancaster et al. USA 2018 Yes 218 44% 12 TEPS YSR 0.23 
Lee(a) South Korea 2009 Yes 164 100% 10-11 PN PN 0.45 
Lee(b) South Korea 2009 Yes 174 0% 10-11 PN PN 0.20 
L’Écuyer et al. Canada 2021 Yes 1038 62% 5.43 PN PN 0.63 
McAuliff, Hubbard, & 
Romano 
USA 2009 Yes 127 50% Grade 2 PN BASC 0.60 
Mercer & DeRosier USA 2008 Yes 1193 49% Grade 3 PN PR 0.48 
Mikami et al. USA 2008 Yes 228 0% 9.50 PN CSBS 0.49 
Moore, Shoulberg, & 
Murray-Close USA 2012 Yes 193 43% 10.72 PN CSBS 0.47 
Morrow et al. USA 2008 Yes 533 46% 10.13 PN PR 0.38 
Murray-Close & Crick USA 2006 Yes 590 50% Grade 4 PN CSBS 0.53 
Okado & Bierman USA 2015 No 317 65% 6.50 PN TTRF 0.24 
Ostrov (a) USA 2008 Yes 69 0% 3.70 PSBS-TF TOCA 0.22 
Ostrov (b) USA 2008 Yes 51 100% 3.70 PSBS-TF TOCA 0.16 
Peeters, Cillessen, & 
Scholte (a) 
Netherlands 2010 Yes 77 100% 13.37 PN PN 0.50 
Peeters,Cillessen, & 
Scholte (b) Netherlands 2010 Yes 93 0% 13.37 PN PN 0.42 
Perron-Gélinas, Brendgen, 
& Vitaro 
Canada 2017 Yes 291 50% 11.47 PN PEI 0.18 
Reijntjes et al. USA 2010 Yes 121 47% 11.50 PN PN 0.51 
Rohlf, Krahé, & Busching Germany 2016 Yes 1284 48% 8.35 SDQ CSBS-T 0.27 
Salmivalli, Kaukiainen, & 
Lagerspetz 
Finland 2000 Yes 209 43% 15 PN DIAS 0.32 
Sentse et al. (a) USA 2015 Yes 1942 0 11.20 PN B-VQ 0.13 
Sentse et al. (b) USA 2015 Yes 1962 100% 11.20 PN B-VQ 0.19 
USA 2011 Yes 119 0% 12.47 PN CSBS-T 0.21 
(continued on next page) 
X. Yue and Q. Zhang 
Child Abuse & Neglect 135 (2023) 105974
6
2.4. Procedure and data analysis 
2.4.1. Primary analyses 
Comprehensive Meta-Analysis (CMA) 3.0 software was used for data analysis. First, the correlational coefficients were standardized 
by converting all raw effect sizes to Fisher-Z, and the converted effect sizes were converted back to correlations for interpretation. 
These individual effect sizes were then synthesized to estimate the mean effect size (Borenstein et al., 2009). The method used to assign 
weights to the studies depended on whether fixed or random models were used. The fixed model was appropriate for a relatively high 
homogeneity sample, while the random model was appropriate for a relatively low homogeneity sample (Borenstein et al., 2010). 
Cochran's I2 and Q statistics were applied to test the homogeneity among studies. The outcome was assumed to be substantial and the 
random effect was accepted if results showed I2 > 75 % (Higgins et al., 2003); otherwise, the fixed effect was accepted. 
The effect sizes of peer rejection with each type of aggression were then computed, while moderation analysis was conducted based 
on the Q statistics for categorical variables (e.g., culture, reporting method of peer rejection, reporting method of aggression) and 
meta-regression analysis for continuous variables (e.g., age). Afterwards, the fail-safe number and Egger's test were used to check 
publication bias, and a funnel plot were used to provide a graphical description. Finally, the p-curve analysis was used to assess se-
lection bias during publication, with an application from www.p-curve.com. We expected to observe a right-skewed p-curve, indi-
cating a lower significant p-value (Simonsohn et al., 2014). 
2.4.2. Auxiliary analyses 
A set of auxiliary analyses were performed. Studies were selected from raw data to form a new data subset, including the partial 
correlation between aggression types (overt vs. relational) and peer rejection. This new data subset only included the studies on the 
bivariate association between peer rejection and aggression types, and the bivariate association between peer rejection and overt/ 
relational aggression. For example, Giunta et al. (2018) only reported the association between overt aggression and peer rejection, so 
their work was not included in the subset. The remaining 23 studies (n = 8391) were included in this subset. 
In the subset, partial correlations were calculated to assess the unique and independent associations between aggression types and 
peer rejection. Specifically, the correlation coefficient between overt aggression and peer rejection was computed after controlling for 
relational aggression in each study. Likewise, overt aggression was included as the control variable when computing the correlation 
coefficient between peer rejection and relational aggression (cf. Aloe, 2013). The mathematical expressions were as follows: 
rp overt =
rp overt − rrelationalrcorr
̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅
(1 − r2
relational)
√ (
1 − r2
corr
) and rp relational =
rrelational − rovertrcorr
̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅(
1 − r2
overt
)√ (
1 − r2
corr
)
Table 1 (continued ) 
Author (s) Country Year Publication 
state 
Sample 
size 
Male 
(%) 
Age Peer rejection 
measure 
Aggression 
measure 
r 
Sijtsema, Shoulberg, & 
Murray-Close 
Smokowski et al. USA 2016 Yes 4065 48% 
High 
school 
SSP YSR 0.24 
Stenseng et al. Norway 2014 Yes 936 50.50% 4.55 TRF CBCL 0.20 
Tan China 2009 Yes 549 55.01% 10.40 RCP RCP 0.52 
Tseng et al. China 2013 Yes 198 53% 10.35 PN PN 0.61 
Tur-Poran, Doménech, & 
Mestre Spain 2018 Yes 1447 50% 9.27 PN PVS 0.24 
Verlinden et al. USA 2014 Yes 4017 49.73% 7.90 PN ABS 0.51 
Wang China 2011 Yes 827 53.08% 12.09 PN RCP 0.60 
Wang et al. China 2015 Yes 686 50% 13.37 PN PN 0.61 
Wang, Duong, Schwartz, 
Chang, & Luo 
China 2014 Yes 818 50% Grade 3- 
4 
PN PN 0.61 
Wei et al. China 2015 Yes 2097 52.12% 12.27 PN CBCL 0.40 
Werner & Crick USA 2004 Yes 759 52% Grade 3 PN CSBS 0.44 
Wright & Li USA 2013 Yes 261 42.50% 13.05 PN SR 0.23 
Wu & Wang China 2019 Yes 122 54.92% 9.34 PN RCP 0.77 
Yang, Bian, Chen and 
Wang 
China 2016 Yes 924 52% 12.65 PN PN 0.20 
Zhao, Liu, & Zhang China 2013 Yes 424 77% 13.92 PN RCP 0.70 
Zimmer-Gembeck et al. Australia 2013 Yes 359 50% 11 SR SR 0.12 
Note. CBCL = Child Behavior Check List; YSR = Youth Self Report; BASC-2 SRP-A = Behavioral Assessment System for Children-2th edition Self 
Report of Personality-Adolescents; ABS = Aggressive Behavior Scale; PN = Peer Nomination; AR = Adult Report; PR = Peer Report; SR = Self Report; 
CSAS = Children’s Social Acceptance Scale; TRA = Teacher Ratings of Aggression; RCP = Revised Class Play; TOCA = Teacher Observation of 
Classroom Adaptation; CSBS = Child Social Behavior Scale; CBS = Child Behavior Scale; HBQ = Health and Behavior Questionnaire; TRF = Teacher 
Report Form; SSBS = School Social Behavior Scales; PSBS-TF = Preschool Social Behavior Scale-Teacher Form; DIAS = Direct Indirect Aggression 
Scale; PNI-PR = Peer Nomination Instrument-Peer Report; SDQ = Strength and Difficulties Questionnaire; TEPS = Teacher’s Estimation of Peer 
Status; PEI = Pupil Evaluation Inventory; SSP = School Success Profile; PVS = Physical and Verbal Scale; E-BS = E-Bullying Scale; B-VQ = Bully- 
Victim Questionnaire. 
X. Yue and Q. Zhang 
http://www.p-curve.com
Child Abuse & Neglect 135 (2023) 105974
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where rovert = the correlation between overt aggression and peer rejection; rrelational = the correlation between relational aggression 
and peer rejection; and rcorr = the correlation between overt aggression and relational aggression. 
The same analysis plan was also adopted for the subset to calculate the mean effect sizes and moderating effects of the four 
moderating variables (age, culture, reporting method of aggression, reporting method of peer rejection) on the association between 
peer rejection and specific types of aggression. The fail-safe number, Egger's test, and funnel plots were also included in the supple-
mentary materials to check publication bias. 
3. Results 
3.1. Sample 
The sample was derived from 61 eligible studies (45,966 participants, Mage = 10.34, SD = 3.13) with 70 independent effect sizes on 
the association between peer rejection and aggression. The proportion of males in the sample was 49 %. In terms of cultural back-
ground, these studies included samples from the following countries: the United States (n = 24); China (n = 14); Canada (n = 6); the 
Netherlands, Germany, India, Spain, Australia (n = 2 each); Italy, Turkey, Croatia, Russia, South Korea, Norway and Finland (n = 1 
each). 
3.2. Effect sizes and heterogeneity test 
The I2 value for overall aggression was 96.02 %, demonstrating a significantly high level of heterogeneity among the studies. The 
random effects model was therefore selected (see Table 2), with the effect sizes between peer rejection and overall aggression ranging 
from 0.09 to 0.77 in these studies. Using the random effects model, the averageeffect size was 0.42 (95 % CI [0.38, 0.47]) for the 
association between peer rejection and overall aggression. Furthermore, both types of aggression were significantly related to peer 
rejection, rovert = 0.46, 95 % CI [0.38, 0.54], p 0.05). In addition, culture did not moderate the partial correlation between peer rejection and 
relational aggression (Q = 0.23, p > 0.05). 
3.5. Publication bias 
The Fail-Safe Number (FSN) of the relationship between peer rejection and overall aggression was 7800, far exceeding the 
X. Yue and Q. Zhang 
Child Abuse & Neglect 135 (2023) 105974
8
minimum value recommended by Rosenthal (1979) (FSN > 5 k + 10 = 350). In addition, the result of Egger's test showed no significant 
intercept value, indicating no publication bias [t(68) = 1.15, p = 0.25]. Observations based on funnel plot showed most studies were at 
the top and evenly distributed around the mean value. These two characteristics indicated that the impact of publication bias might be 
minimal (see Fig. 2). The P-curve was right-skewed and no105974
9
The concurrent association between peer rejection and aggression types indicates that all types of aggression (e.g., overt, relational) 
are positively correlated with peer rejection, replicating research findings that aggressive children may experience more peer rejection 
than non-aggressive/average children (Evans et al., 2016; Gorman et al., 2011; Hubbard, 2001). Aggressive children are more likely to 
use several types of aggression, so children involved in one type of aggression are also at high risk of using other types of aggression 
(Lansford et al., 2012). Moreover, aggressive children may use different types of aggression depending on the situation and become 
victims of aggression (Giles & Heyman, 2005), indicating that there is no clear-cut resolution to the problem of whether one type of 
aggression is related to peer rejection. Thus, for studies reporting both relational and overt aggression (n = 23), the unique variance of 
these two aggression types is calculated. The results indicate that the unique variances of relational and overt aggression are positively 
associated with peer rejection (rprelational = 0.17; rpovert = 0.15). Overt aggression is considered to be a common outcome (Reijntjes et al., 
2010) and a strong contributing factor (Salmivalli et al., 2000), while relational aggression may be common among rejected children. 
By definition, relational aggression involves manipulating others (e.g., spreading rumors, excluding someone) in comparison with 
overt aggression, so the nature of relational aggression originates from and is reinforced by social networks (Crick & Grotpeter, 1995; 
Fig. 2. Funnel plot of effect sizes of the correlation between overall aggression and peer rejection. 
Fig. 3. P-curve for meta-analysis of peer rejection and aggression. 
X. Yue and Q. Zhang 
Child Abuse & Neglect 135 (2023) 105974
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Low et al., 2013). 
As predicted, culture moderates the association between peer rejection and overall aggression. The correlation between peer 
rejection and aggression is greater in collectivist cultures than in individualist cultures. The reality, however, is that the correlation 
exists in both cultures, but is stronger in individualist cultures. Why is this overstated in our study? One hypothesis is group harmony. 
Previous research has shown that collectivist cultures (versus individualist cultures) may perceive aggression as a threat to group 
harmony (Bass et al., 2016). Another explanation can also be associated to how data is collected, reported and interpreted across 
nations, especially as it relates to concepts of peer rejection and aggression across cultures. Still, the findings suggest that the cor-
relation between peer rejection and overt aggression is weaker in collectivist cultures than in individualist cultures. In other words, 
children rejected in individualist cultures are more likely to resort to overt aggression than children rejected in collectivist cultures. 
However, this cannot be misinterpreted to suggest that individualist cultures (versus collectivist cultures) see aggression as a positive 
thing and a means to achieving high social status. In addition, Cultural Dimension Theory (Hofstede et al., 2010) regards Individualism 
versus Collectivism as a key dimension of culture: collectivism emphasizes group harmony (e.g., common interests, conformity, 
interdependence), while individualism emphasizes individual rights (e.g., respect for privacy, enjoyment of challenges, freedom). Our 
findings relate to Cultural Dimension Theory. Specifically, children rejected in collectivist cultures may prioritize group harmony by 
avoiding overt aggression, while children rejected in individualist cultures may realize individual rights by displaying overt aggres-
sion, which is consistent with the view of the key dimension of Individualism versus Collectivism in Cultural Dimension Theory. 
Our meta-analysis has found that the age moderation effect is only confirmed in the unique association between peer rejection and 
relational aggression, which aligns with previous studies showing that children use more relational aggression as they mature (Aiz-
pitarte et al., 2019; Espelage et al., 2018; Romero-Abrio et al., 2019). As children get older and their cognitive and emotional skills 
improve, they may avoid physical aggression in favor of more sophisticated strategic relational aggression (Ettekal & Ladd, 2015). 
Furthermore, the reporting method of peer rejection moderates the association between peer rejection and aggression. Self- 
reported rejection produces the weakest correlation between peer rejection and aggression of all the reported methods, supporting 
previous studies showing that aggressive children tend to underestimate their level of peer rejection in compared to others' perceptions 
of their social status (García-Bacete et al., 2019; Lynch et al., 2016; White & Kistner, 2011; Zimmer-Gembeck et al., 2013). A possible 
explanation for this is that aggressive children are more likely to be associated with antisocial peers and thus may not feel rejected by 
others (Samek et al., 2016). Moreover, aggressive children may also deliberately underestimate their negative peer relationships to 
avoid negative emotions associated with them (e.g., shame). Nevertheless, the limited number of studies using self-reporting methods 
to assess peer rejection may be reflected in this moderating effect. 
Similarly, the reporting method of aggression moderates the association between peer rejection and overall aggression, which is 
consistent with previous meta-analyses (e.g., Card et al., 2008; Casper et al., 2020). Specifically, the correlation between self-reported 
aggression and peer rejection is the weakest. In contrast, aggression measured using other reporting methods (e.g., peer-nominated 
aggression) has a higher correlation with peer rejection, possibly because the peer-nomination method of aggression better reflects 
the rejection-aggression link than the self-reporting method of aggression. As for the self-reporting method of aggression, children may 
underestimate their own aggressive behavior for fear of punishment. Moreover, although peer-nomination method of aggression is 
sometimes considered less valid in measuring aggression, peers may underestimate aggressive behavior in problematic children (e.g., 
bullies) for fear of revenge (Killer et al., 2019). In the case of anonymous responses, the peer-nomination method of aggression can 
depict a more detailed and clear situation because aggressive children do not know if they have been nominated as aggressive by their 
peers. Alternatively, peers may be motivated by a sense of justice to report aggressive children more frequently. The correlation 
between peer-nominated aggression and peer rejection is stronger than that between adult-reported aggression and peer rejection, 
possibly because aggression occurs when adults (e.g., teachers, parents) are not present. 
4.1. Limitations and implications 
This study has several limitations that require further attention in future studies. First, all studies included in the meta-analysis are 
cross-sectional and do not focus on the long-term association between peer rejection and aggression. In the future, longitudinal 
research literature should be included to boost the reliability of these findings. Second, this study does not test for the moderating 
effects of gender, as only 11 studies report gender differences separately. For most studies included in the meta-analysis, the number of 
male and female respondents is basically even. Future work can explore greater differences between boys and girls. Finally, due to the 
limitation of language comprehension, this study does not include research articles published in Asian languagesother than Mandarin 
(e.g., Korean, Japanese), and the inclusion of these languages could improve the validity of this meta-analysis. 
The study has several practical implications. First, our meta-analysis replicates previous findings that peer rejection is closely 
associated with aggression using a large number of samples from diverse backgrounds. Second, results suggest that educators should 
pay close attention to the peer relationships of aggressive students, as these students may be at higher risk for peer rejection. Alter-
natively, specific strategies can be designed to help rejected students reduce their aggressive behaviors. Third, unique intervention 
programs should be designed and implemented for rejected students of different age groups to reduce relational aggression. 
5. Conclusions 
In conclusion, this study found a significant association between peer rejection and aggression types. Specifically, moderation 
analysis indicates that reporting methods of peer rejection and aggression, as well as culture, moderate the association between peer 
rejection and overall aggression. Peer rejection is positively associated with the unique variance of aggression types (e.g., overt, 
X. Yue and Q. Zhang 
Child Abuse & Neglect 135 (2023) 105974
11
relational). In addition, further moderation analysis suggests that culture moderates the association between peer rejection and overt 
aggression after controlling for relational aggression. However, age moderates the association between peer rejection and relational 
aggression after controlling for overt aggression. 
CRediT authorship contribution statement 
Yue and Zhang were mainly responsible for data analysis and writing the paper. Yue and Zhang made the revision of the paper. 
Zhang led the project to the paper. 
Declaration of competing interest 
On behalf of all authors, the corresponding author states that there is no conflict of interest. 
Data availability statement 
The data used in this study are available from the corresponding author upon reasonable request. 
Acknowledgments 
The study was supported by the National Social Science Fund of China (22BSH091), Chongqing Talent Plan Project (2021YC043), 
Innovation Research 2035 Pilot Plan of Southwest University (SWUPilotPlan004), and the 111 Project (B21036). We would like to 
thank Yue Zhou for her professional help in language editing. We also thank Dr. TianQiang Hu and Dr. Jin Zhang from Southwest 
University in China for their earlier comments on this study. 
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