ReviewFrontiers in psychology2025
Advancing the psychometrics of reverse-keyed items: enriching cognitive theory by a logical and linguistic perspective.
Review in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Cross-cultural adaptation and validation of the Chinese version of the Maternal Adaptation Scale: a methodological study.Women's health nursing (Seoul, Korea) · 2026Article
- Psychosocial and Social Security Risks Linked to Vaccine Misinformation in Romania: Implications for Vaccination Acceptance and Public Policy.Behavioral sciences (Basel, Switzerland) · 2026Article
- Adaptation of Parental Perception of Uncertainty Scale (PPUS): A psychometric study in a genetic research center in Indonesia.Belitung nursing journal · 2026Article
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4 authors.
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Abstract
Inclusion of reverse-keyed items in a questionnaire usually impacts its factor structure and reliability. Therefore, their presence or absence also affects measurement validity, yet a clear consensus on their use is missing. In this paper, we provide an overview of the literature on the use of reverse-keyed items. We outline the typical arguments for and against their use, along with the cognitive explanatory framework commonly used to account for the associated issues. We further argue that while the cognitive model of responding is theoretically meaningful, it cannot, on its own, identify specific error sources from reverse-keyed item sets, and that issue lies in the implicit assumption regarding how reverse-keyed items should function. Furthermore, we note that literature on reverse-keyed items is at an impasse, with conflicting recommendations and inconclusive results. As a solution, we introduce a logical and linguistic perspective to advance our understanding of reverse-keyed items. This perspective allows researchers to understand that response inconsistencies in a statistical model do not necessarily indicate logically inconsistent answers from the respondent. Enriching the cognitive model with a linguistic perspective, which has been missing in psychometric literature, allows us to differentiate between mere statistical and actual response inconsistency. Based on this combination of cognitive and linguistic theory, we advance the historical analysis of response bias by suggesting that future research should closely draw from linguistic concepts to arrive at a promising explanatory framework that can then better inform modeling decisions. However, further empirical studies are needed to test our hypotheses and evaluate the magnitude and relevance of the proposed linguistic effects.
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