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理解数据质量:在行为经济学香烟需求的众包调查中,教学理解作为一种实用的度量标准。

Understanding data quality: Instructional comprehension as a practical metric in crowdsourced investigations of behavioral economic cigarette demand.

机构信息

Fralin Biomedical Research Institute.

出版信息

Exp Clin Psychopharmacol. 2022 Aug;30(4):415-423. doi: 10.1037/pha0000579.

Abstract

Crowdsourcing platforms allow researchers to quickly recruit and collect behavioral economic measures in substance-using populations, such as cigarette smokers. Despite the broad utility and flexibility, data quality issues have been an object of concern. In two separate studies recruiting cigarette smokers, we sought to investigate the association between a practical quality control measure (accuracy on an instruction quiz), on internal consistency of number of cigarettes smoked per day and purchasing patterns of tobacco products in an experimental tobacco marketplace (ETM; Study 1), and in a cigarette purchase task (CPT; Study 2). Participants (N = 312 in Study 1; N = 119 in Study 2) were recruited from Amazon mechanical turk. Both studies included task instructions, a quiz, a purchase task, cigarette usage and dependence questions, and demographics. The results show that participants who answered all instruction items correctly: (a) reported the number of cigarettes per day more consistently (partial η² = 0.11, p < .001, Study 1; partial η² = 0.09, p = .016, Study 2), (b) demonstrated increased model fit among the cigarette demand curves (partial η² = 0.23, p < .001, Study 1; partial η² = 0.08, p = .002, Study 2), and purchased tobacco products in the ETM more consistently with their current usage. We conclude that instruction quizzes before purchase tasks may be useful for researchers evaluating demand data. Instruction quizzes with multiple items may allow researchers to choose the level of data quality appropriate for their studies. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

摘要

众包平台允许研究人员快速招募和收集物质使用人群(如吸烟者)的行为经济学措施。尽管具有广泛的实用性和灵活性,但数据质量问题一直是人们关注的焦点。在两项分别招募吸烟者的研究中,我们试图调查一种实用的质量控制措施(在指令测验上的准确性)与每日吸烟量的内部一致性以及实验烟草市场(ETM;研究 1)和香烟购买任务(CPT;研究 2)中烟草产品购买模式之间的关联。参与者(研究 1 中为 312 人;研究 2 中为 119 人)是从亚马逊机械土耳其招募的。这两项研究都包括任务说明、测验、购买任务、吸烟和依赖问题以及人口统计数据。结果表明,回答所有指令项目的参与者:(a)报告的每日吸烟量更一致(部分 η²=0.11,p<.001,研究 1;部分 η²=0.09,p=0.016,研究 2),(b)在香烟需求曲线中表现出更高的模型拟合度(部分 η²=0.23,p<.001,研究 1;部分 η²=0.08,p=0.002,研究 2),并且在 ETM 中购买烟草产品与他们目前的使用更一致。我们的结论是,购买任务之前的指令测验可能对评估需求数据的研究人员有用。具有多个项目的指令测验可能允许研究人员选择适合其研究的数据质量水平。(PsycInfo 数据库记录(c)2022 APA,保留所有权利)。

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