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饮酒的网络支持:多组增长混合模型在检验客户与治疗匹配度中的应用

Network support for drinking: an application of multiple groups growth mixture modeling to examine client-treatment matching.

作者信息

Wu Johnny, Witkiewitz Katie

机构信息

1007 West Harrison Street (M/C 285), Department of Psychology, University of Illinois at Chicago, Chicago, Illinois 60607, USA.

出版信息

J Stud Alcohol Drugs. 2008 Jan;69(1):21-9. doi: 10.15288/jsad.2008.69.21.

Abstract

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.

摘要

目的

本研究重新审视了“匹配酒精成瘾治疗与客户异质性”项目(Project MATCH)的假设,即那些在社交网络中得到较多饮酒支持的个体,如果被分配到十二步促进疗法(TSF),将获得最佳治疗效果。

方法

以饮酒后果量表(Drinking Inventory of Consequences)所测量的饮酒后果作为主要结局指标。采用多组增长混合模型来估计952名门诊患者在“匹配酒精成瘾治疗与客户异质性”项目的三种治疗条件下接受治疗后的12个月内的饮酒后果轨迹。将潜在轨迹类别中的增长因素对饮酒的网络支持进行回归分析,以评估治疗条件是否调节了饮酒的网络支持与饮酒后果之间随时间变化的关系。

结果

确定了三个潜在类别,分别代表低(n = 154,16.2%)、中(n = 400,42%)和高(n = 398,41.8%)水平的饮酒后果。各治疗组之间的类别没有差异。随着时间的推移,更多的饮酒网络支持预示着更多的饮酒后果,但这仅适用于被分配到认知行为疗法和动机增强疗法的患者,而不适用于TSF组的患者。

结论

本研究为“匹配酒精成瘾治疗与客户异质性”项目最初的匹配假设之一提供了进一步支持:如果社交网络支持饮酒的客户被分配到TSF,他们在治疗后立即会有更好的治疗效果。由于最初的“匹配酒精成瘾治疗与客户异质性”项目研究仅在3年随访时发现了这种匹配效应,这些结果为饮酒网络支持的匹配效应增加了有效性。该研究还提供了额外的证据,即考虑酒精治疗结果的异质性对于准确估计治疗效果很重要。

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