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重新思考在衡量主观评价时使用同意-不同意问题的方法。

Towards a reconsideration of the use of agree-disagree questions in measuring subjective evaluations.

机构信息

University of Wisconsin Survey Center, University of Wisconsin, Madison, USA; Department of Sociology, University of Wisconsin, Madison, USA.

University of Wisconsin Survey Center, University of Wisconsin, Madison, USA; Department of Sociology, University of Wisconsin, Madison, USA.

出版信息

Res Social Adm Pharm. 2022 Feb;18(2):2335-2344. doi: 10.1016/j.sapharm.2021.06.014. Epub 2021 Jun 24.

Abstract

Agree-disagree (AD) or Likert questions (e.g., "I am extremely satisfied: strongly agree … strongly disagree") are among the most frequently used response formats to measure attitudes and opinions in the social and medical sciences. This review and research synthesis focuses on the measurement properties and potential limitations of AD questions. The research leads us to advocate for an alternative questioning strategy in which items are written to directly ask about their underlying response dimensions using response categories tailored to match the response dimension, which we refer to as item-specific (IS) (e.g., "How satisfied are you: not at all … extremely"). In this review we: 1) synthesize past research comparing data quality for AD and IS questions; 2) present conceptual models of and review research supporting respondents' cognitive processing of AD and IS questions; and 3) provide an overview of question characteristics that frequently differ between AD and IS questions and may affect respondents' cognitive processing and data quality. Although experimental studies directly comparing AD and IS questions yield some mixed results, more studies find IS questions are associated with desirable data quality outcomes (e.g., validity and reliability) and AD questions are associated with undesirable outcomes (e.g., acquiescence, response effects, etc.). Based on available research, models of cognitive processing, and a review of question characteristics, we recommended IS questions over AD questions for most purposes. For researchers considering the use of previously administered AD questions and instruments, issues surrounding the challenges of translating questions from AD to IS response formats are discussed.

摘要

同意-不同意(AD)或李克特式问题(例如,“我非常满意:强烈同意……强烈不同意”)是社会科学和医学中最常用来衡量态度和意见的反应格式之一。本综述和研究综合重点关注 AD 问题的测量特性和潜在局限性。研究结果使我们主张采用替代的提问策略,即通过使用针对响应维度定制的响应类别来直接询问其基础响应维度的项目,我们称之为特定项目(IS)(例如,“你有多满意:一点也不……非常”)。在本综述中,我们:1)综合比较 AD 和 IS 问题数据质量的过去研究;2)提出 AD 和 IS 问题的概念模型,并回顾支持受访者对 AD 和 IS 问题认知处理的研究;3)概述 AD 和 IS 问题之间经常存在差异并可能影响受访者认知处理和数据质量的问题特征。尽管直接比较 AD 和 IS 问题的实验研究得出了一些混合结果,但更多的研究发现 IS 问题与理想的数据质量结果(例如有效性和可靠性)相关,而 AD 问题与不理想的结果(例如默认、响应效应等)相关。基于现有的研究、认知处理模型以及问题特征的回顾,我们建议在大多数情况下使用 IS 问题而不是 AD 问题。对于考虑使用先前管理的 AD 问题和工具的研究人员,讨论了将问题从 AD 转换为 IS 响应格式所面临的挑战。

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