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A Network Analysis of Factors Leading Adolescents to Befriend Substance-Using Peers

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Abstract

Objective

Our interest is in the systematic network selection processes that lead adolescents into friendships with substance-using peers. Theory suggests that adolescents with certain risk factors (i.e., weak attachments to conventional society and low self-control) are more likely to select substance-using friends. Our goal is to evaluate whether adolescents with particular risk factors have a greater risk for befriending substance-using peers, while controlling for common network selection processes that can produce the same friendship pattern. These selection processes are important as they help to set the stage for later peer influence on substance use.

Methods

We use a Stochastic Actor-Oriented Model to examine network change among 1373 adolescents from the National Longitudinal Study of Adolescent Health. We test whether low self-control and indicators of weak attachments (to family, school, and religion) predict selecting friends engaged in alcohol, tobacco, and marijuana use.

Results

We find widespread evidence of the hypothesized friendship pattern within adolescent friendship networks. In most cases this pattern is a product of selection based on the risk factor and substance use, and not attributable to other selection mechanisms.

Conclusions

We highlight the need to broaden the study of delinquency to account for how adolescents come to acquire friends who may be negative sources of peer influence. We offer theoretical and methodological insight to this question, ultimately finding that only in limited cases are adolescents with particular risk factors more likely to select friends involved in substance use. We discuss implications for theory and future investigations of peer influence.

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Fig. 2

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Notes

  1. See Young (2011) for a network-based study of the related question of how self-control affects friend selection.

  2. It may be possible to relax the assumption that adolescents naturally prefer deviant associates. Even if there is no initial preference for deviant peers, the simple absence of a preference one way or another ought to be sufficient for the socialization argument. That is, should inadequately-socialized adolescents have no preference among peers while socialized adolescents prefer non-delinquent friends, then inadequately-socialized peers will be relatively more likely to have delinquent friends (i.e., default selection).

  3. There will also be more ties from adolescents without the risk factor directed toward substance users than expected by chance. By contrast, there will be fewer ties from adolescents, with or without the risk factor, to non-users than expected by chance.

  4. For many schools, the Wave I in-home survey contained a programming error that reduced the possible number of friendship nominations to 1 male and 1 female friend instead of 5 male and 5 female friends. In the two largest schools analyzed here, 6% of students received the erroneous friendship question. In the 5 schools excluded due to this error, 40% of students received the truncated friendship roster.

  5. At present, there is no consensus on how to treat network data missing at the first observation. Prior studies have shown that results are different when ties are imputed versus treated as absent and allowed to form endogenously. However, there are no recommendations for which approach is preferable or less biased (e.g., Hipp et al. 2015).

  6. For a slightly different approach to the truncated roster issue see Haynie et al. (2014).

  7. Number of actors at distance 2 captures the tendency to avoid intransitive relations (i.e., triads with only two friendship ties). The transitive triplets effect captures avoiding intransitivity by forming or keeping ties to one’s friends’ friends. Number of actors at distance 2 captures the avoidance of intransitivity by failing to form ties or dropping ties to peers who have many friends who are not one’s own friends—a process that goes unrecognized by the transitive triplets effect.

  8. The valence of the estimated 3-cycles parameter contrasts with many early SABM studies that obtained a negative estimate. However, prior studies typically haven’t controlled for the interaction between transitivity and reciprocity, which is a structure that contains a 3-cycle. Our results are consistent with Block (2015) who called attention to the likely interaction between transitivity and reciprocity, and whose models also found that with this interaction included a previously negative 3-cycles effect shifted to positive.

  9. When multiple attribute effects are present (e.g., ego, alter, similarity) the clearest way to interpret the attribute’s effect on selection is to calculate predicted tie likelihood based upon the joint values of ego and alter through an ego-alter selection table (see Snijders et al. 2010). These calculations require the range and mean similarity of each measure (available in Table 2).

  10. The seeming difference in effect magnitude evident in Fig. 2 is a consequence of the different scaling used for each substance.

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Acknowledgements

Funding was provided by National Institute of Child Health and Human Development (Grant Nos. 1R21-HD060927, 5R21HD71885-2).

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  1. School of Human Evolution and Social Change, Arizona State University, PO Box 872402, Tempe, AZ, 85287, USA

    David R. Schaefer

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Correspondence to David R. Schaefer.

Appendices

Appendix 1

See Tables 4, 5 and 6.

Table 4 Coefficients and standard errors from Full SAOMs for alcohol use
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Table 5 Coefficients and standard errors from full SAOMs for smoking
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Table 6 Coefficients and standard errors from full SAOMs for marijuana use
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Appendix 2

See Table 7.

Table 7 Coefficients and standard errors from followup SAOMs
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Schaefer, D.R. A Network Analysis of Factors Leading Adolescents to Befriend Substance-Using Peers. J Quant Criminol 34, 275–312 (2018). https://doi.org/10.1007/s10940-016-9335-4

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