Peer Relations and Developmental Psychop

Peer Relations and Developmental Psychopathology MITCHELL J. PRINSTEIN and MATTEO GILETTA horizontal relationships a dynamic systems perspective also is neces- sary for understanding the role of peer relations on the development of psychopathology (Magnusson & Stattin, 2006)

Ideas for which paper to present

Measure of peer acceptance (see Coie & Dodge, 1983) 

(Jiang & Cillessen, 2005)

Crick and Dodge’s (1994**)** social information processing model most often is cited in the study of peer relations and social information processing.

-> Links social cognition and interpersonal interactions

Recent work offers compelling evidence for transactions among peer rejection, aggression, and a hostile attribution bias in a manner that is consistent with dynamic sys- tems theory. Examining a developmental cascade model, Lansford, Malone, Dodge, Pettit, and Bates (2010) demon- strated mutually reinforcing, and gradually escalating longitudinal associations between these three constructs over time within a sample of young children over four years (i.e., kindergarten to grade three).

Cognitions have been cited as important mediators or moderators of the links between peer rejection and depres- sive symptoms in prior work. Some of these cognitions per- tain to youths’ perceptions of their own peer status. For example, youths’ perceptions of rejection by peers are more 

proximal longitudinal predictors of depression (e.g., Kist- ner, Balthazor, Risi, & Burton, 1999) and may mediate the association between actual peer rejection and later depres- sive symptoms (Panak & Garber, 1992). Youths’ underes- timations of their levels of peer acceptance are predicted by their depressive symptoms (De Los Reyes & Prinstein, 2004; Rudolph & Clark, 2001), and these underestimations reciprocally are associated with later increases in depres- sion (Cillessen & Bellmore, 1999).

-> Crazy pathway between immune system and social interactions

Researchers recently have acknowledged that the social environment also may regulate the activity of the genes involved in the innate immune response (see Irwin & Cole, 2011; Slavich & Cole, 2013). Speci cally, it has been sug- gested that adverse social experiences (i.e., interpersonal stress) may in uence the expression of in ammatory genes.

These social rejection experiences may be particularly harmful as they may directly threaten the innate human need to belong (Slavich, O’Donovan, Epel, & Kemeny, 2010).

-> Online aggression

Research suggests that cyber victimization occurs with remarkable frequency, and certainly with particularly dire consequences in some cases (Smith et al., 2008**)**. 

Accord- ingly, all adolescents who belonged to a moderate online victimization trajectory belonged either to a moderate or to a high of ine victimization trajectory, indicating that online victimization always occurred in the presence of of ine victimization (Sumter, Baumgartner, Valkenburg, & Peter, 2012).

professionals advocate that youth be given opportunities to develop vol- untary relationships with their peers.

METHODS An interesting recent study employing social net- work analyses offers supporting evidence for this hypothesis (Tilton-Weaver, Burk, Kerr, & Stattin, 2013**)**. Using network data, including friends’ own reports of their deviant behavior, results indicated that high parental rules reduced the probability that children would select deviant peers as friends only when accompanied by low (perceived) parental overcontrol.

(Rose, Carlson, & Waller, 2007).

(31) Relevant to Paly Study!!! The apparent strong associations between adolescents’ attitudes/behaviors and the attitudes/behaviors of their peers are among the most consistent and potent effects in all of developmental psychopathology research. Peer influence effects also have broad implications for many sectors of society. Among psychologists, there has been interest in peer in uence as a normative phenomenon (among developmental psychologists), to illustrate persua- sion and in uence theories (among social psychologists),

Educators and education policymakers have begun to re ect on peer in uence theories to determine students’ placements into academically tracked classrooms or detention centers that exclusively include other deviant youth (Vigdor, 2008).

Second, studies that have examined adolescents’ reports of their best friends’ behavior as a predictor in peer in uence research more precisely are measuring the social- ization effects of adolescents’ perceptions of their friends’ behavior. This may be a highly relevant construct to con- sider; studies suggest that adolescents’ perceptions of their friends’ behavior may be more proximal predictors of their own behavior and may even mediate the association between adolescents’ friends’ behavior and adolescents’ own behavior (Fromme & Ruela, 1994).

Moreover, substantial theory and research indicate that individuals are notoriously poor at accurately estimating the attitudes and behavior of others. False consensus effects demonstrate that individuals overestimate the similarities between their own and others’ behaviors (Ross, Greene, & House, 1977). The uniqueness bias indicates that people underestimate how many of their peers may engage in desirable behaviors that they themselves engage in (Goethals, Messick, & Allison, 1991).

PALY Empirical work has demonstrated that adolescents’ engagement in health risk behaviors is associated with their overestimations of others’ engagement in similar behaviors (Prentice, 2008)

Research on media influences has frequently proposed that adolescents’ behavior can be socialized by peers whom they have not even met. Empirical data sorely are needed regarding the relative power of different influential agents, as are data on the manner in which adolescents reconcile con icting messages from different socializing forces in their peer network. Recent data suggest that the most potent peer contexts for socialization may vary by the behavior that is being influenced. For example, recent work has suggested that socialization of depressive symptoms may be most likely to occur within best friendship dyads, while social- ization of alcohol use occur within larger social networks (Giletta et al., 2012). This may re ect differences in the mechanisms underlying peer in uence effects for different domains of adolescent adjustment and the contexts in which these mechanisms are most likely to occur.

METHODS An especially popular recent approach has involved stochastic actor-based modeling (Snijders et al., 2010). This approach is grounded on the notion that individual behaviors and social networks are dynamic and interrelated entities. That is, behavioral changes of individuals within a social network (i.e., actors) are strongly related to the characteristics of the social network and vice versa. Hence, stochastic actor-based models provide a method- ological tool to investigate the co-evolution of social networks and individual behaviors over time. These models address several limitations of earlier peer influence analytic approaches.

Similarly, Berger’s (2008) marketing model of social memes (i.e., fads, trends) posits that social comparison processes and alignment with salient, desirable groups (or nonconformity to undesirable groups) may explain peer socialization. Berger contends that individuals initially engage in a behavior that they feel helps differentiate them 

from others, particularly through identi cation with a special subgroup that matches their desired identity. For example, if alcohol use initially is associated with a typical high status schoolmate, then high status adolescents may be especially likely to adopt this behavior to signal their membership in this in-group. However, when alcohol use begins to become adopted among other, lower status adolescents (i.e., among out-groups), it loses its value as a marker for in-group status and will quickly fade as a preferred behavior among the high status adolescents themselves (see Berger, 2008).