Crafting Mosaics: Person-Centered Religious Influence and Selection in Adolescent Friendships

Abstract

This research addresses the intersection of two key domains of adolescents' lives: religion and peer networks. Religion scholars have argued that religion is multi-faceted and hence better understood by focusing on combinations of indicators (i.e. mosaics), versus a more traditional variable-centered approach. We adopt this framework and investigate the interplay between religion and peer networks, both in how religious mosaics are shaped by friends and how profiles affect friend selection dynamics. With data from two schools in the National Longitudinal Study of Adolescent Health, we estimate these religious mosaics using latent class analysis (LCA) to identify profiles consisting of combinations of commonly available survey-based measures of religious attitudes, behaviors and identities. Finding evidence of theoretically-expected profiles, our second step is to use stochastic actor based models (SABMs) to investigate network dynamics for these LCA-based religious profiles. We demonstrate how the distinct structure of profile data can be integrated within the SABM framework to evaluate processes of friend selection and influence. Results show evidence of adolescents influencing one another's religious mosaics, but not selecting friends on that basis.

Are Birds of a Feather Praying Together? Assessing Friends’ Influence on Muslim Youths’ Religiosity in Germany

“…The conclusion, however, that religion rather than religiosity shapes youths’ friendship choices contrasts with findings from studies in the United States that found evidence of friendship selection on religiosity (Adams, Schaefer, and Ettekal 2020; Cheadle and Schwadel 2012; Cook, Schwadel, and Cheadle 2017). Because these studies examined youths that were older than those in our sample, developmental differences are one possible explanation for diverging findings because younger youths may be less able than older ones to accurately observe their peers’ religiosity.…”

Peer Network Processes in Adolescents’ Health Lifestyles

“…However, our results suggest such a shift can produce meaningful and useful results. As one of the first investigations of network selection and influence on clusters of behaviors (see also adams et al 2020), our approach complements existing strategies focused on individual behaviors. However, many mechanisms underpinning social influence may work equally well for clusters of behaviors as for individual behaviors.…”

“…The SABM behavior objective function predicts changes in individuals’ behavior as a product of their own attributes, others’ attributes (i.e., influence), and network structural features. SABMs have most often been used to model change in a single dichotomous or ordinal behavioral variable (Steglich et al 2010); however, they can accommodate latent classes (adams et al 2020), such as our categorical health lifestyles. To accomplish this, we adopted the strategy for modeling “behavioral” variables within an SABM as a two-mode network (Snijders, Lomi, and Torló 2013), coding each adolescent as having a membership state for each of the classes (or categories of affiliation), with 1 coded for the assigned class and 0 coded for the other classes.…”

“…This pattern is labeled network assortativity and is observed for numerous health behaviors and conditions (Schaefer and adams 2017; Valente 2010), including substance use (de la Haye et al 2013; Haas and Schaefer 2014; Kirke 2004), physical activity (de la Haye et al 2011), and psychological states such as depression (Schaefer, Kornienko, and Fox 2011). However, the vast majority of this research is conducted for single behaviors or conditions, with only one study examining multiple (religious) measures (adams et al 2020). Thus, we first seek to identify whether health lifestyles display observed assortativity, as prior research has done for single behaviors.…”

“…We seek to assess whether health lifestyles display network effects consistent with theoretical expectations. “Network assortativity” describes a general pattern whereby friends exhibit elevated similarity on a range of attributes, including health behaviors, like physical activity (de la Haye et al 2011) and substance use (Haas and Schaefer 2014; Kirke 2004), and core statuses that animate sociological research—gender (Kandel 1978), race (Moody 2001), and religious beliefs (adams, Schaefer, and Ettekal 2020). Beyond documenting the ubiquity of these patterns , network research can theoretically and empirically disentangle the causal processes responsible for observed assortativity (McPherson, Smith-Lovin, and Cook 2001).…”