O'Connor Susan M, Davies John B, Heffernan Dorothy D, van Eijk Robert
Department of Psychological Medicine, University of Glasgow, Gartnavel Royal Hospital, Glasgow, UK.
Alcohol Alcohol. 2003 Nov-Dec;38(6):568-73. doi: 10.1093/alcalc/agg112.
To test the predictive validity of a vignette methodology based on a Signal Detection model by examining treatment attrition within an alcohol clinic.
Participants were asked to categorize vignettes that described individuals drinking alcohol as problem or nonproblem alcohol use at the beginning of a 4-week intensive course of treatment. These participants were divided retrospectively into two groups: those who completed treatment and those who dropped-out of treatment. A matched post-treatment long-term abstainer group was also tested.
Signal Detection analyses demonstrated that response bias scores predicted who would drop out of treatment (P = 0.01).
The vignette methodology provided useful levels of prediction in an applied clinical setting. It was argued that verbal reports from problem alcohol users may be more usefully conceptualized in terms of sensitivity and response bias than in terms of memory or 'truth'.
通过研究酒精诊所内的治疗脱落情况,检验基于信号检测模型的 vignette 方法的预测效度。
在为期4周的强化治疗课程开始时,要求参与者将描述饮酒个体的 vignette 分类为问题饮酒或非问题饮酒。这些参与者被回顾性地分为两组:完成治疗的人和退出治疗的人。还测试了一个匹配的治疗后长期戒酒者组。
信号检测分析表明,反应偏差分数可预测谁会退出治疗(P = 0.01)。
vignette 方法在应用临床环境中提供了有用的预测水平。有人认为,问题饮酒者的口头报告从敏感性和反应偏差的角度来概念化可能比从记忆或“真实性”的角度更有用。