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Journal of studies on alcohol and drugs, Vol. 71, No. 6. (November 2010), pp. 837-846 Key: citeulike:11903023
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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 modified to create the Important People Inventory (IPI), which was used to measure the contextual influence 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. 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. As unique effects, alcohol-specific 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. The IPI is a useful instrument for describing network support of alcohol-use disorder patients entering treatment. Measures of alcohol-specific support are prognostic of drinking outcomes. The patient's network support should be systematically assessed prior to tailored treatment planning.
Longabaugh and colleagues (2010) sought to explore the interrelationship between social networks and drinking by assessing network support as measured by the contextual influence of the patient's social network to predicting drinking during and following treatment. As part of a large multisite RCT of 1,373 patients six network constructs were tested for predicting patient drinking. The two network constructs predictive of abstinent days and heavy drinking days following treatment were number of people drinking and opposition to patient drinking within their social network. They concluded that alcohol-specific support influence drinking outcomes and such support should be systematically assessed for treatment planning.
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