Schedule:
Friday, January 14, 2011: 2:30 PM
Meeting Room 12 (Tampa Marriott Waterside Hotel & Marina)
* noted as presenting author
Background and Purpose: Assessment of personal social networks can be helpful in understanding addictive behaviors. Establishing positive network resources and rebuilding drug free networks is often a challenge for women in recovery. This NIDA funded study describes personal social networks among women in substance abuse treatment and examines network differences by stage of treatment. Methods: Data were collected from 100 women upon intake to three community based substance abuse treatment programs. All women were in treatment for one week, with a diagnosis of substance dependence: alcohol and /or drug. The presence of co-occurring mental disorders was assessed with the computerized Diagnostic Interview Schedule (CDIS). A social network software program, Ego Net available from SourceForge.net, (a) elicited 25 network members (b) asked about the supportive nature of each relationship and (c) asked about each unique pair of relationships. Ego Net also produced a visual display of network composition. Stage of treatment was assessed using the Substance Abuse Treatment Scale (SATS), an ordinal level rating scale completed by the treatment provider. Participants were divided into three treatment stages; engagement (n=11), persuasion (n=66) and active treatment (n=21); 2 were missing stage data. A Kruskal-Wallis test compared the three treatment stage groups; the Bonferroni correction method evaluated pairwise differences. Results: Study participants averaged 37.16 years of age (SD=10.32, R=18-62). 57% were African American and 37% were Caucasian. 40% did not have a high school education. The majority (76.3%) were dually diagnosed. More than half (58.2%) reported alcohol dependence and cocaine dependence (63.3 %). Of the 25 network members listed, on average social networks consisted of mostly family (9), others (e.g. neighborhood, friend) (7), treatment program staff (3), and professional helpers (1). While availability of concrete, emotional and informational support did not differ by stage of treatment, a Kruskal-Wallis test did reveal significant differences among the three treatment stage groups in network composition. Women in the persuasion stage reported fewer network members from treatment programs or AA (M=2.12 (SD=3.04)) and fewer non-using network members (M=15.15 (SD=4.90)) than women in active treatment (M=4.38 (SD=5.23), p=.035, and M=18.1(SD=4.85), p=.012, respectively). Women in the persuasion stage reported more network members who used alcohol and drugs (M=5.11 (SD=3.64)) and network members they had used with (M=7.86 (SD=5.23)) compared to those in active treatment (M= 3.19 (SD=3.34), p=.017, and M=4.95 (SD=3.76), p=.021, respectively). Both the engagement (M= 2.55 (SD=2.84) and active treatment groups (M= 2.33 (SD=2.13) reported significantly more professional helpers than women in the persuasion group (M= 0.83 (SD=1.47), both p≤ .01). Conclusions and Implications: Two thirds of the women began treatment in the persuasion stage. Their social network profile in this stage suggests they may be at risk due to lack of sobriety support. Visual displays of social network compositions could be an adjunct to intervention as patterns of relationships are more readily apparent. Future research will examine changes in social networks as a predictor of post treatment outcomes.