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用于从货币选择问卷和概率折扣问卷计算折扣指数的句法。

Syntax for calculation of discounting indices from the monetary choice questionnaire and probability discounting questionnaire.

作者信息

Gray Joshua C, Amlung Michael T, Palmer Abraham A, MacKillop James

机构信息

Department of Psychology, University of Georgia.

Peter Boris Centre for Addictions Research, McMaster University/St. Joseph's Healthcare Hamilton.

出版信息

J Exp Anal Behav. 2016 Sep;106(2):156-63. doi: 10.1002/jeab.221. Epub 2016 Sep 20.

Abstract

The 27-item Monetary Choice Questionnaire (MCQ; Kirby, Petry, & Bickel, 1999) and 30-item Probability Discounting Questionnaire (PDQ; Madden, Petry, & Johnson, 2009) are widely used, validated measures of preferences for immediate versus delayed rewards and guaranteed versus risky rewards, respectively. The MCQ measures delayed discounting by asking individuals to choose between rewards available immediately and larger rewards available after a delay. The PDQ measures probability discounting by asking individuals to choose between guaranteed rewards and a chance at winning larger rewards. Numerous studies have implicated these measures in addiction and other health behaviors. Unlike typical self-report measures, the MCQ and PDQ generate inferred hyperbolic temporal and probability discounting functions by comparing choice preferences to arrays of functions to which the individual items are preconfigured. This article provides R and SPSS syntax for processing the MCQ and PDQ. Specifically, for the MCQ, the syntax generates k values, consistency of the inferred k, and immediate choice ratios; for the PDQ, the syntax generates h indices, consistency of the inferred h, and risky choice ratios. The syntax is intended to increase the accessibility of these measures, expedite the data processing, and reduce risk for error.

摘要

27项货币选择问卷(MCQ;柯比、佩特里和比克尔,1999年)和30项概率折扣问卷(PDQ;马登、佩特里和约翰逊,2009年)分别是广泛使用的、经过验证的衡量对即时奖励与延迟奖励以及确定性奖励与风险奖励偏好的指标。MCQ通过让个体在即时可得的奖励和延迟后可得的更大奖励之间进行选择来衡量延迟折扣。PDQ通过让个体在确定性奖励和赢得更大奖励的机会之间进行选择来衡量概率折扣。许多研究表明这些指标与成瘾及其他健康行为有关。与典型的自我报告指标不同,MCQ和PDQ通过将选择偏好与个体项目预先配置的函数数组进行比较,生成推断的双曲时间和概率折扣函数。本文提供了用于处理MCQ和PDQ的R和SPSS语法。具体而言,对于MCQ,该语法生成k值、推断k的一致性以及即时选择比率;对于PDQ,该语法生成h指数、推断h的一致性以及风险选择比率。该语法旨在提高这些指标的可及性、加快数据处理速度并降低错误风险。

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