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Alcohol relapse repetition, gender, and predictive validity
William H Zywiak1, Robert L Stout, Winston B Trefry
1Decision Sciences Institute, Pacific Institute for Research and Evaluation, Providence, RI 02906, USA. zywiak@pire.org
Journal of Substance Abuse Treatment
|May 24, 2006
Summary
This study developed a scoring algorithm to classify alcohol relapse types. Men showed more consistent relapse patterns than women, with distinct triggers for initial posttreatment relapses.
Area of Science:
- Psychology
- Addiction Research
- Clinical Psychology
Background:
- Previous research on the Reasons for Drinking Questionnaire (RDQ) yielded interesting findings but suffered from low consistency in relapse type (63%).
- Objective classification of alcohol relapse types is crucial for understanding and intervening in addiction.
- Gender differences in relapse patterns require further investigation.
Purpose of the Study:
- To introduce and validate a scoring algorithm for objectively classifying alcohol relapse into three types: negative affect, social pressure, or craving/cued.
- To examine gender differences in the types of initial posttreatment alcohol relapses.
- To identify predictors for different relapse types in men and women.
Main Methods:
- Development of a scoring algorithm to categorize alcohol relapses based on the RDQ.
- Analysis of relapse consistency between the first and second relapse episodes.
- Examination of gender-specific relapse patterns and their correlation with psychological assessments (e.g., Beck Depression Inventory, Alcohol Dependence Scale).
Main Results:
- The scoring algorithm objectively classifies alcohol relapses into negative affect, social pressure, or craving/cued types.
- Relapse consistency was significantly higher in men (81%) compared to women (44%).
- Women were more prone to negative affect relapses, while men were more likely to experience social pressure relapses.
- For men, negative affect relapses were predicted by Beck Depression Inventory scores.
- For women, negative affect relapses were predicted by Alcohol Dependence Scale scores, and craving/cued relapses by situational craving.
Conclusions:
- The developed scoring algorithm provides an objective method for classifying alcohol relapse types.
- Significant gender differences exist in alcohol relapse patterns and their predictors.
- Understanding these gender-specific triggers is vital for tailoring more effective relapse prevention strategies.