Comments on Adolescent Peer Crowd Affiliation: A Response to

In Volume 38, Issue 6, Cross and Fletcher (2009) review the literature on adolescent peer crowds or reputation-based peer groups highlighting the different methods that have been used across studies to assess adolescent peer crowd affiliation. We think that the detailed comparison of peer crowd research methodologies that they provide was long overdue. In that regard, we found the review to be very informative. However, we disagree with some of Cross and Fletcher’s (2009) key arguments that are directly or indirectly related to our own review on adolescent peer group identification (Sussman et al. 2007).

Mainly, the authors state four problems with this research arena. First, they contend that studies on adolescent peer crowds do not often agree on how a peer crowd is conceptualized and operationalized, thus hindering the comparability of findings across studies. Second, they argue that none of the current methods of assessing peer crowd affiliation is rigorous enough to accurately classify adolescents into distinct crowds, especially those who affiliate with multiple groups. Hence, they suggest these methodologies are susceptible to serious errors of inference that might threaten the validity of their results. Third, they claim that among the adolescent peer crowd researchers the emphasis has been on “naming crowds to the exclusion of an understanding of the function of crowds” (p. 761). Fourth, they doubt that the current adolescent peer crowd research may potentially guide the intervention efforts concerning adolescent health risk behaviors. In the following sections we critique these four arguments that Cross and Fletcher (2009) advance in an attempt to show that although the field of adolescent peer crowd study has a vast room for future research, the current research in the field is not as misguided as one may infer from their review.

Methodological Issues

Cross and Fletcher (2009) claim that “there is a disconnect in the [current adolescent peer crowd] research between crowd affiliation (a choice made by the adolescent) and crowd placement (an assignment made by an adolescent’s peers) (p. 748).” Thus, they conclude, “different phenomena may be under investigation when researchers employ different self- and peer-identification crowd methods” (p. 753). In our view, “crowd affiliation” and “crowd placement” are different means of attaining or representing a crowd membership (manifest variables) whereas the crowd itself is the phenomenon of interest (the latent variable).

Currently, not much is known about the typical extent of overlap/non-overlap between self-identified and peer-identified crowd membership in the same sample of adolescents. One recent study indicated that more than half of a diverse sample of high school students identified with a crowd different from the one with which most peer associated them, often, apparently, for face-saving reasons (Brown et al. 2008). However, in the systematic review of 44 peer-reviewed, data-based studies published on adolescent peer crowd affiliation in the past forty years, Sussman et al. (2007) found that whether adolescents identified themselves as, for example, “Deviants” or were identified by others as “Deviants,” Deviants were consistently more likely to show higher problem behavior compared to any other type of crowds.

Sussman et al. (2007) found four basic ways of assessing adolescents’ crowd affiliation prevalent in the literature: (1) adolescents’ self-report on their peer crowd affiliation (i.e., self-identification); (2) investigators’ classifying of adolescents into peer crowds based on use of ethnographic methods; (3) peer ratings of adolescents into groups according to the perceived “social types” prevalent at their schools (i.e., social-type rating); and (4) investigators’ classifying of adolescents into peer crowds based on their behavioral characteristics (e.g., aggression), social aspiration among peers, and social involvement. Furthermore, Sussman et al. (2007) found that the entire list of peer crowd names that appeared across the 44 studies and which were assessed through these different methods could be condensed into five general categories: Elites (crowds higher in social status or popularity), Athletes (athletically-oriented crowds), Academics (academically-oriented crowds), Deviants (high risk crowds), and Others (crowds that are not easily classifiable but which tend to represent adolescents relatively low in peer status, social involvement, and academic involvement). The same types of peer crowd names appeared repeatedly across studies, and peer crowd names within the same category of classification showed a consistent pattern of behavioral and psychosocial correlates.

Some of the factors that Sussman et al. (2007) considered to create their crowd categories included social approval or desirability, academic and athletic orientation, and the tendency to engage in problem behavior. Factors such as these are rooted in the implicit personality theory (Rosenberg et al. 1968) that adolescents use to define themselves and their peers within their social context. Sussman et al. (2007) derived and tested the five general categories based on the previous research on multidimensional scaling of social perceptions among adolescents and young adults (Brown et al. 1994; Stone and Brown 1999; Ashmore et al. 2007). Multidimensional scaling involves eliciting the dimensions that adolescents use to organize their knowledge of the social types they come across in their peer environment (Ashmore et al. 2007).

With Sussman et al. (2007) in point, Cross and Fletcher (2009) ask: “How much confidence should be placed in the findings of differences among crowd member behavior when the samples were identified with widely differing methods?” A good deal, we think. As suggested by Campbell and Fiske (1959), one of the best ways to test construct validity is to use multiple methods to examine the same construct and compare the results. In fact, this logic is central to Campbell and Fiske’s (1959) Multitrait Multimethod Matrix (MTMM) method. In our view, the fact that different methods of assessing crowd affiliation have resulted in a similar pattern of normatively distinct crowds validates the phenomenon of adolescent crowds and its potential to affect adolescent behavior. Nevertheless, given discrepancies between self- and peer ratings of crowd affiliation, it is important for more studies such as Brown et al. (2008) to pursue the meaning of, and consistency of, crowd identifications and assignments to an adolescent’s development.

Crowd Definition

According to Cross and Fletcher (2009), there is currently no one “accepted definition of the adolescent crowd” which is the reason why “the boundaries of the crowd are not sufficiently delineated” (p. 753) in the existing methodological approaches. Hence, they argue, “without a decision about who is to be studied (i.e., how to define the crowd)” the current approaches in studying adolescent crowds are prone to making “both Type I- and Type II-like errors” (p. 753). A Type-I-like error would occur when someone is wrongly classified to a crowd, the “null hypothesis” being that he or she is not a member of that group. A Type-II-like error would occur when someone is not rightly classified as a member of a crowd to which they belong. Thus, higher Type-I- and Type-II-like errors represent concepts similar to specificity and sensitivity in epidemiology.

In our view, despite the differences in methodologies used to study adolescent peer crowds, one may infer a consensus across research studies regarding what adolescent peer crowds signify. Researchers in general tend to agree that adolescent peer crowd affiliation represents the tendency of adolescents “to place themselves and others into consensually recognized and labeled social types” (Sussman et al. 2007, p. 1). Undoubtedly, adolescent peer crowd affiliation represents a phenomenon involving a complex interplay among different types of self- and other-related social perceptions such as adolescents’ perceptions of themselves, their perceptions of what their peers perceive them to be, their peers’ actual perceptions of them, and how they would want their peers to perceive them.

The diverse approaches taken to conceptualize and operationalize peer crowd affiliation in the current literature attest to the complexity of the peer crowd phenomenon. However, as illustrated by Sussman et al. (2007), the convergence of findings related to peer crowd names and characteristics across a methodologically varying set of studies suggests a general consensus among researchers regarding the nature of the peer crowd construct itself. That said, we do agree that more future research is needed to better understand the factors that influence adolescent crowd membership and the extent to which peer social network overlaps with peer crowd affiliation.

We find Cross and Fletcher’s (2009) concern for sensitivity and specificity an important one. Although they don’t identify a method that might strike the right balance between specificity and sensitivity, we would welcome an advance in this direction. However, it should be noted that researchers have taken some precautions to increase the sensitivity and specificity of their measures. For example, in a self-identification measure an open-ended option is usually included for subjects to report the crowd names that do not appear on the provided list of names (Sussman et al. 2000, 2004).

We agree with Cross and Fletcher (2009) that adolescents’ identification with multiple groups poses a common methodological problem in the study of peer crowds. More research that examines multiple crowd identification is needed. Also, more research is needed to determine the relative impact of each crowd on the behavior of adolescents who identify with multiple groups. This is a different sort of research question, of course, from asking youth to indicate the crowd about which they most closely identify. We feel that both types of research have value.

Crowd Functions

Cross and Fletcher’s (2009) claim that researchers have neglected to study the functions of adolescent peer crowds is puzzling because researchers have long tried to study the functions of peer crowd affiliation (e.g., Ashmore et al. 2002; Ashmore et al. 2007; Brown et al. 1994; Coleman 1961; Eckert 1989). Adolescent peer crowd affiliation is largely shaped by social perception or social cognition (Brown et al. 1994; Ashmore et al. 2002, 2007). Fiske (1992, p. 878) has interpreted social cognition in terms of pragmatism: “people make meaning and think about each other in the service of interaction; their interactions depend on their goals, which in turn depend on their immediate roles and the larger culture.” For adolescents, peer crowds represent social types with distinct life-style norms. By affiliating with a peer crowd adolescents not only define themselves but also choose the type of peers they want to model themselves after (Brown et al. 1994). Peer crowds may function as a strong source of reinforcement in learning and developing certain behaviors (e.g., substance use) and beliefs (Akers et al. 1979). Certainly, more research is needed here, including an increased integration of quantitative work with ethnographic work.

Prospects for Intervention

Cross and Fletcher (2009) downplay the significance of the possible effects of crowd norms on adolescents’ behavior. In particular, they claim that Sussman et al.’s (2007) suggestion regarding the possibility of tailoring prevention efforts to high risk peer groups is “extremely premature” (p. 760). In our view, the lack of a perfect method of assessment that would correctly assign a hard-to-classify individual to a distinct group does not mean that researchers should not investigate the behavioral patterns of identifiable crowd members; there is practical value of continuing to engage in such work. We believe that findings from adolescent crowd affiliation literature have important implications for prevention interventions, particularly media-based interventions.

Identity-based media campaigns have been widely used by marketers to promote products to specific groups of people (Leiss et al. 2005; Sivulka 1998). In particular, the tobacco industry has used psychographic data to identify and market to certain crowds, such as “Progressives,” “Bohemians,” “Spoiled Brats,” and “Uptown Girls” (e.g., Braun et al. 2008; Cook et al. 2003). Recently, health campaigners have begun to take notice of the potential utility of peer crowd affiliation and identity (Basu and Wang 2009; Howgill 1998; Ling 2007). For example, Berger and Rand (2008) successfully used college students’ crowd affiliation or disaffiliation in a campaign to spark healthier food choices. Undergraduates were less likely to choose junk food options from a menu when they were told that eating junk food was typical of a peer crowd with which they were disaffiliated. Peer crowd affiliation research identifies groups known to engage in risky health behaviors and thus is likely to help health campaign designers target the desired audience. Additionally, campaign designers can use adolescents’ peer crowd affiliation to better tailor campaigns that resonate with members of at-risk groups. Although the intervention aspect of adolescent peer crowd affiliation is an area that deserves much further consideration, we believe that research effort in this direction will ultimately prove fruitful to researchers, health practitioners and campaign designers.

Conclusion

As highlighted in Sussman et al. (2007), crowd names have a long history of existence in adolescent culture; some of these crowds embody drastically different norms (e.g., Jocks versus Goths) which appear to differentially affect adolescents’ behaviors, including health risk behaviors. In addition, crowd names signifying similar norms may be grouped together in conceptually coherent categories (Brown et al. 1994) based on problem behavior characteristics, social status, and academic and extracurricular proclivities. Cross and Fletcher’s (2009) review does not consider the full breadth of the adolescent peer crowd literature. We do believe that their review will help entertain a research dialogue that may increase the number of research paths one may follow to get a better understanding of this arena. As such, it is a needed booster to the field.