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本文引用的文献

1
Network support as a prognostic indicator of drinking outcomes: the COMBINE Study.网络支持作为饮酒结局的预后指标:COMBINE 研究。
J Stud Alcohol Drugs. 2010 Nov;71(6):837-46. doi: 10.15288/jsad.2010.71.837.
2
A factor analysis of the important people inventory.重要人物量表的因素分析
Alcohol Alcohol. 2007 Jul-Aug;42(4):347-53. doi: 10.1093/alcalc/agm012. Epub 2007 May 17.
3
The need for substance abuse after-care: longitudinal analysis of Oxford House.药物滥用后续照护的必要性:牛津之家的纵向分析
Addict Behav. 2007 Apr;32(4):803-18. doi: 10.1016/j.addbeh.2006.06.014. Epub 2006 Jul 14.
4
Decomposing the relationships between pretreatment social network characteristics and alcohol treatment outcome.剖析治疗前社交网络特征与酒精治疗效果之间的关系。
J Stud Alcohol. 2002 Jan;63(1):114-21.
5
Network support for drinking, Alcoholics Anonymous and long-term matching effects.对饮酒的网络支持、匿名戒酒互助会及长期匹配效应。
Addiction. 1998 Sep;93(9):1313-33. doi: 10.1046/j.1360-0443.1998.93913133.x.
6
Effect of the social environment on alcohol involvement and subjective well-being prior to alcoholism treatment.社会环境对酒精成瘾治疗前饮酒行为及主观幸福感的影响。
J Stud Alcohol. 1993 May;54(3):283-96. doi: 10.15288/jsa.1993.54.283.
7
Measurement of drinking behavior using the Form 90 family of instruments.使用90型系列工具测量饮酒行为。
J Stud Alcohol Suppl. 1994 Dec;12:112-8. doi: 10.15288/jsas.1994.s12.112.
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The Fifth Edition of the Addiction Severity Index.《成瘾严重程度指数》第五版
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《重要他人量表三因素模型预测性的纵向研究》

A longitudinal investigation of the predictability of the three-factor model of the Important People Inventory.

机构信息

Center for Community Research, DePaul University, Chicago, IL, USA.

出版信息

Am J Drug Alcohol Abuse. 2011 Jul;37(4):259-63. doi: 10.3109/00952990.2011.591017. Epub 2011 Jun 27.

DOI:10.3109/00952990.2011.591017
PMID:21702726
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3582215/
Abstract

OBJECTIVE

Because of psychometric limitations and varied adaptations of the Important People Inventory (IP; a measure of alcohol social support), Groh et al. (7) performed factor analyses and created a three-factor model (i.e., Support for Drinking from Network Members, Drinking Behaviors of Network Members, and General Social Support). This present study examined the ability of the three-factor model to predict alcohol use.

METHODS

This study consisted of 293 women and 604 men who were US residents of a network of self-run recovery homes known as Oxford House (OH). Logistic regression models were run. The first model examined which of the three IP factors was the best predictor of alcohol use over a 4-month period; next, models compared Drinking Behaviors of Network Members (the three-factor model) and Network Support for Drinking from Network Members (the original two-factor model) as predictors of 4-month alcohol use.

RESULTS

Of the three factors measuring general support, network drinking behaviors, and support for drinking, Drinking Behaviors of Network Members was the only significant predictor of alcohol use over a 4-month period. Additionally, this component was a better predictor of drinking than the Support for Drinking from Network Members summary score from the original model.

CONCLUSIONS

Compared to the original model, this new three-factor model of the IP is shorter, has stronger internal reliability, and is a better predictor of alcohol use over time. It is strongly recommended that researchers continue to explore the utility of this new model.

摘要

目的

由于心理计量学的限制和重要人物清单(IP;衡量酒精社会支持的一种方法)的不同适应性,Groh 等人进行了因素分析并创建了一个三因素模型(即,来自网络成员的饮酒支持、网络成员的饮酒行为和一般社会支持)。本研究检验了三因素模型预测饮酒行为的能力。

方法

这项研究包括 293 名女性和 604 名男性,他们是美国自我经营的康复之家网络 Oxford House(OH)的居民。进行了逻辑回归模型。第一个模型检验了三个 IP 因素中的哪一个是预测 4 个月内饮酒行为的最佳因素;接下来,模型比较了网络成员的饮酒行为(三因素模型)和网络成员对饮酒的支持(原始的两因素模型)作为预测 4 个月内饮酒的因素。

结果

在衡量一般支持、网络饮酒行为和支持饮酒的三个因素中,网络成员的饮酒行为是唯一能预测 4 个月内饮酒行为的因素。此外,该组成部分比原始模型中来自网络成员的饮酒支持总分更能预测饮酒。

结论

与原始模型相比,IP 的这个新的三因素模型更短,内部可靠性更强,并且是预测随时间推移的饮酒行为的更好指标。强烈建议研究人员继续探索这个新模型的效用。