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奖励概率指数:一种衡量获得环境奖励机会的量表的设计与验证。

The reward probability index: design and validation of a scale measuring access to environmental reward.

机构信息

University of Tennessee-Knoxville, Knoxville, TN 37996, USA.

出版信息

Behav Ther. 2011 Jun;42(2):249-62. doi: 10.1016/j.beth.2010.05.004. Epub 2011 Jan 18.

Abstract

Behavioral models of depression implicate decreased response-contingent positive reinforcement (RCPR) as critical toward the development and maintenance of depression (Lewinsohn, 1974). Given the absence of a psychometrically sound self-report measure of RCPR, the Reward Probability Index (RPI) was developed to measure access to environmental reward and to approximate actual RCPR. In Study 1 (n=269), exploratory factor analysis supported a 20-item two-factor model (Reward Probability, Environmental Suppressors) with strong internal consistency (α=.90). In Study 2 (n=281), confirmatory factor analysis supported this two-factor structure and convergent validity was established through strong correlations between the RPI and measures of activity, avoidance, reinforcement, and depression (r=.65 to .81). Discriminant validity was supported via smaller correlations between the RPI and measures of social support and somatic anxiety (r=-.29 to -.40). Two-week test-retest reliability was strong (r=.69). In Study 3 (n=33), controlling for depression symptoms, hierarchical regression supported the incremental validity of the RPI in predicting daily diary reports of environmental reward. The RPI represents a parsimonious, reliable, and valid measure that may facilitate understanding of the etiology of depression and its relationship to overt behaviors.

摘要

抑郁的行为模型表明,反应相关的正强化(RCPR)减少是导致抑郁发生和持续的关键因素(Lewinsohn,1974)。鉴于缺乏对 RCPR 进行心理测量的可靠自评量表,因此开发了奖励概率指数(RPI)来衡量获得环境奖励的程度,并近似于实际的 RCPR。在研究 1(n=269)中,探索性因素分析支持了一个包含 20 个项目的两因素模型(奖励概率、环境抑制),具有很强的内部一致性(α=.90)。在研究 2(n=281)中,验证性因素分析支持了这两个因素结构,并且 RPI 与活动、回避、强化和抑郁的测量之间存在很强的相关性(r=.65 到.81),从而建立了收敛效度。通过 RPI 与社会支持和躯体焦虑测量之间的相关性较小(r=-.29 到 -.40),支持了判别效度。两周的重测信度较强(r=.69)。在研究 3(n=33)中,控制了抑郁症状,层次回归支持 RPI 在预测环境奖励的日常日记报告方面具有增量有效性。RPI 是一种简洁、可靠和有效的测量工具,可能有助于理解抑郁的病因及其与明显行为的关系。

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