A network of helping: generalized reciprocity and cooperative behavior in response to peer and staff affirmations and corrections among therapeutic community residents

Abstract

Background: Clinical theory in therapeutic communities (TCs) for substance abuse treatment emphasizes the importance of peer interactions in bringing about change. This implies that residents will respond in a more prosocial manner to peer versus staff intervention and that residents will interact in such a way as to maintain cooperation.

Method: The data consist of electronic records of peer and staff affirmations and corrections at four corrections-based TC units. We treat the data as a directed social network of affirmations. We sampled 100 resident days from each unit (n = 400) and used a generalized linear mixed effects network time series model to analyze the predictors of sending and receiving affirmations and corrections. The model allowed us to control for characteristics of individuals as well as network-related dependencies.

Results: Residents show generalized reciprocity following peer affirmations, but not following staff affirmations. Residents did not respond to peer corrections by increasing affirmations, but responded to staff corrections by decreasing affirmations. Residents directly reciprocated peer affirmations. Residents were more likely to affirm a peer whom they had recently corrected. Residents were homophilous with respect to race, age and program entry time.

Conclusion: This analysis demonstrates that TC residents react more prosocially to behavioral intervention by peers than by staff. Further, the community exhibits generalized and direct reciprocity, mechanisms known to foster cooperation in groups. Multiple forms of homophily influence resident interactions. These findings validate TC clinical theory while suggesting paths to improved outcomes.

Keywords:

• Substance abuse treatment
• mutual aid
• therapeutic communities
• evolutionary psychology
• social network analysis
• self-organization

Acknowledgements

The authors thank George De Leon, Ian Hamilton and Jessica Linley for valuable discussions.

Disclosure statement

The authors report no conflict of interest.