Matching treatment focus to patient social investment and support: 18-month follow-up results.

Self Cite

156

160

ABSTRACT. Objective: To increase understanding of the interrelationship between a patient's social network and patient drinking, the Important People and Activities (IPA) instrument was developed. To meet the aims of the COMBINE (Combining Medications and Behavioral Interventions) Study, the IPA was modifi ed to create the Important People Inventory (IPI), which was used to measure the contextual infl uence of the patient's social network on patient outcomes and treatment effects. The aims of the present article were to describe the IPI and its differences from the IPA and to test the relationship of network support as measured by the IPI in predicting drinking during and following treatment. Method: Alcohol-dependent patients (N = 1,373) seeking outpatient treatment in the COMBINE randomized clinical trial were administered the IPI before treatment. Six network constructs were tested for predicting patient drinking. Results: As unique effects, alcohol-specifi c support, as measured by network drinking and opposition to patient drinking, is predictive of patient abstinent days during and following treatment and heavy drinking days following treatment. Other measures of network support have variable relationships to patient drinking at different phases: Some are predictive of patient drinking during treatment but diminish, whereas others are unrelated to drinking during treatment but become increasingly predictive of drinking as time from treatment increases. Conclusions: The IPI is a useful instrument for describing network support of alcohol-use disorder patients entering treatment. Measures of alcohol-specifi c support are prognostic of drinking outcomes. The patient's network support should be systematically assessed prior to tailored treatment planning. (J. Stud. Alcohol Drugs, 71, 837-846, 2010)

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Network Support as a Prognostic Indicator of Drinking Outcomes: The COMBINE Study

Longabaugh

Wirtz²,

Zywiak³

et al. 2010

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156

160

“…This may be because, in the eyes of these social network members, these particular subjects were not perceived to be stereotypically alcoholic. Thus, there may be an important opportunity to intervene with these individuals to see if they can be converted to "white hats"; broader public health message initiatives might need to focus on dispelling the commonly held "skid row" alcoholic stereotypes (Litt et al, 2009;Longabaugh et al, 1995Longabaugh et al, , 2010.…”

Section: Discussionmentioning

confidence: 99%

Association Between Social Influences and Drinking Outcomes Across Three Years

Stout

Kelly

Magill

et al. 2012

ABSTRACT. Objective:Multiple studies have shown social network variables to mediate and predict drinking outcome, but, because of selfselection biases, these studies cannot reliably determine whether the infl uence is causal or correlational. The goal of this study was to evaluate evidence for a causal role for social network characteristics in determining long-term outcomes using state-of-the-art statistical methods. Method: Outpatient and aftercare clients enrolled in Project MATCH (N = 1,726) were assessed at intake and at 3, 6, 9, 12, and 15 months; the outpatient sample was also followed to 39 months. Generalized linear modeling with propensity stratifi cation tested whether changes in social network ties (i.e., number of pro-abstainers and pro-drinkers) at Month 9 predicted percentage of days abstinent and drinks per drinking day at 15 and 39 months, covarying for Alcoholics Anonymous (AA) attendance at Month 9. Results: An increase in the number of pro-drinkers predicted worse drinking outcomes, measured by percentage of days abstinent and drinks per drinking day, at Months 15 and 39 (p < .0001). An increase in the number of pro-abstainers predicted more percentage of days abstinent for both time periods (p < .01). The social network variables uniquely predicted 5%-12% of the outcome variance; AA attendance predicted an additional 1%-6%. Conclusions: Network composition following treatment is an important and plausibly causal predictor of alcohol outcome across 3 years, adjusting for multiple confounders. The effects are consistent across patients exhibiting a broad range of alcohol-related impairment. Results support the further development of treatments that promote positive social changes and highlight the need for additional research on the determinants of social network changes.

“…However, this undesirable relationship is dependent on what type of alcohol treatment one receives. Longabaugh et al (1995) indicated that, for clients with social networks supportive of drinking, receiving a treatment with the goal of decreasing support for drinking or increasing support for abstinence will be effective in improving subsequent alcohol treatment outcomes. The results of the current study provide further empirical evidence for client-treatment matching.…”

Section: Discussionmentioning

confidence: 99%

Network Support for Drinking: An Application of Multiple Groups Growth Mixture Modeling to Examine Client-Treatment Matching

Witkiewitz

2008

Objective-The current study re-examined the Project MATCH (Matching Alcoholism Treatments to Client Heterogeneity) hypothesis that individuals with high network support for drinking would have the best treatment outcomes if they were assigned to twelve-step facilitation (TSF).Method-Drinking consequences, as measured by the Drinking Inventory of Consequences, was the primary outcome measure. Growth mixture models with multiple groups were used to estimate the drinking consequence trajectories of 952 outpatients during the 12 months following treatment for each of the three Project MATCH treatment conditions. Growth factors within latent trajectory classes were regressed on network support for drinking to assess whether treatment condition moderated the relationship between network support for drinking and drinking consequences over time.Results-Three latent classes were identified, representing low (n = 154, 16.2%), medium (n = 400, 42%), and high (n = 398, 41.8%) levels of drinking consequences. Classes did not differ across treatment groups. Greater network support for drinking predicted more drinking consequences over time but only for clients assigned to cognitive-behavioral therapy and motivational enhancement therapy, not TSF.Conclusions-This study provides further support for one of the original Project MATCH matching hypotheses: Clients with social networks supportive of drinking had better outcomes immediately after treatment if they were assigned to TSF. Because the original Project MATCH studies found this matching effect only at the 3-year follow-up, these results add validity to the network support for drinking matching effect. The study also provides additional evidence that accounting for heterogeneity in alcohol treatment outcomes is important for accurately estimating treatment effectiveness.