Cognitive Functioning and the Quality of Survey Responses: An Individual Participant Data Meta-Analysis of 10 Epidemiological Studies of Aging

Stefan Schneider, Pey-Jiuan Lee, Raymond Hernandez, Doerte U Junghaenel, Arthur A Stone, Erik Meijer, Haomiao Jin, Arie Kapteyn, Bart Orriens, Elizabeth M Zelinski and Alyssa Gamaldo

The Journals of Gerontology: Series B, 2024, vol. 79, issue 5, 289-300

Abstract: ObjectivesSelf-reported survey data are essential for monitoring the health and well-being of the population as it ages. For studies of aging to provide precise and unbiased results, it is necessary that the self-reported information meets high psychometric standards. In this study, we examined whether the quality of survey responses in panel studies of aging depends on respondents’ cognitive abilities.MethodsOver 17 million survey responses from 157,844 participants aged 50 years and older in 10 epidemiological studies of aging were analyzed. We derived 6 common statistical indicators of response quality from each participant’s data and estimated the correlations with participants’ cognitive test scores at each study wave. Effect sizes (correlations) were synthesized across studies, cognitive tests, and waves using individual participant data meta-analysis methods.ResultsRespondents with lower cognitive scores showed significantly more missing item responses (overall effect size ρ^ = −0.144), random measurement error (ρ^ = −0.192), Guttman errors (ρ^ = −0.233), multivariate outliers (ρ^ = −0.254), and acquiescent responses (ρ^ = −0.078); the overall effect for extreme responses (ρ^ = −0.045) was not significant. Effect sizes were consistent across studies, modes of survey administsration, and different cognitive functioning domains, although some cognitive domain specificity was also observed.DiscussionLower-quality responses among respondents with lower cognitive abilities add random and systematic errors to survey measures, reducing the reliability, validity, and reproducibility of survey study results in aging research.

Keywords: Assessment; Cognition; Measurement; Research methods and issues (search for similar items in EconPapers)
Date: 2024
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