Eigenvector centrality defines hierarchy and predicts graduation in therapeutic community units.

INTRODUCTION: Therapeutic communities (TCs) are mutual aid based residential programs for the treatment of substance abuse and criminal behavior. While it is expected that residents will provide feedback to peers, there has been no social network study of the hierarchy through which feedback flows. METHODS: Data for this study was drawn from clinical records of peer corrections exchanged between TC residents in six units kept over periods of less than two to over eight years. Four of the units served men while two served women. Hierarchy position was measured using eigenvector centrality, on the assumption that residents who were more central in the network of corrections were lower in the hierarchy. It was hypothesized that residents would rise in the hierarchy over time. This was tested using Wilcoxon paired samples tests comparing the mean and maximum eigenvector centrality for time in treatment with those in the last month of treatment. It was also hypothesized that residents who rose higher in the hierarchy were more likely to graduate, the outcome of primary interest. Logistic regression was used to test hierarchy position as a predictor of graduation, controlling for age, race, risk of recidivism as measured by the Level of Services Inventory-Revised (LSI-R) and days spent in the program. RESULTS: Residents averaged a statistically significantly lower eigenvector centrality in the last month in all units, indicating a rise in the hierarchy over time. Residents with lower maximum and average eigenvector centrality both over the length of treatment and in the last month of treatment were more likely to graduate in four of the six units, those with lower maximum and average eigenvector centrality in the last month but not over the length of treatment were more likely to graduate in one of the six units, while eigenvector centrality did not predict graduation in one unit. However, this last unit was much smaller than the others, which may have influenced the results. CONCLUSION: These results suggest that TC residents move through a social network hierarchy and that movement through the hierarchy predicts successful graduation.

Building the community: Endogenous network formation, homophily and prosocial sorting among therapeutic community residents.

BACKGROUND: Researchers have begun to consider the ways in which social networks influence therapeutic community (TC) treatment outcomes. However, there are few studies of the way in which the social networks of TC residents develop over the course of treatment. METHODOLOGY: We used a Temporal Exponential Random Graph Model (TERGM) to analyze changes in social networks totaling 320,387 peer affirmations exchanged between residents in three correctional TCs, one of which serves men and two of which serve both men and women. The networks were analyzed within weekly and monthly time-frames. RESULTS: Within a weekly time-frame residents tended to close triads. Residents who were not previously connected tended not to affirm the same peers. Residents showed homophily by entry cohort. Other results were inconsistent across TC units. Within a monthly time-frame participants showed homophily by graduation status. They showed the same patterns of triadic closure when connected, tendency not to affirm the same peers when not connected and homophily by cohort entry time as in a weekly time frame. CONCLUSIONS: TCs leverage three human tendencies to bring about change. The first is the tendency of cooperators to work together, in this case in seeking graduation. The second is the tendency of people to build clusters. The third is homophily, in this case by cohort entry time. Consistent with TC clinical theory, residents spread affirmations to a variety of peers when they have no previous connection. This suggests that residents balance network clustering with a concern for the community as a whole.