Evidence map›Paper›PMID 38460115›Full record

SynthesisThe journals of gerontology. Series B, Psychological sciences and social sciences2024

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

Abstract readMeta-Analysis
In one paragraph

Synthesis in The journals of gerontology. Series B, Psychological sciences and social sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Stefan SchneiderCenter for Self-Report Science & Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA.
Pey-Jiuan LeeCenter for Self-Report Science & Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA.
Raymond HernandezCenter for Self-Report Science & Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA.
Doerte U JunghaenelCenter for Self-Report Science & Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA.
Arthur A StoneCenter for Self-Report Science & Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA.
Erik MeijerCenter for Economic and Social Research, University of Southern California, Los Angeles, California, USA.ORCID 0000-0001-7959-4670
Haomiao JinSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
Arie KapteynCenter for Economic and Social Research, University of Southern California, Los Angeles, California, USA.
Bart OrriensCenter for Economic and Social Research, University of Southern California, Los Angeles, California, USA.
Elizabeth M ZelinskiLeonard Davis School of Gerontology, University of Southern California, Los Angeles, California, USA.

Funding

Enhancing engagement and participation of marginalized community residents in the UASU01AG077280 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Arie Kapteyn · 2023 to 2026
$50.9M
The Mexican Health and Aging Study - IIR01AG018016 · NIA · UNIVERSITY OF TEXAS MED BR GALVESTON · PI Rebeca Wong · 1999 to 2026
$22.6M
Testing early markers of cognitive decline and dementia derived from survey response behaviorsR01AG068190 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Doerte Ulrike Junghaenel, Stefan Schneider · 2020 to 2026
$4.8M
NIA NIH HHS R01 AG018016NIA NIH HHS R01 AG068190NIA NIH HHS R01AG068190NIA NIH HHS U01 AG077280NIH HHS R01AG068190
6 · The paper itself

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. DISCUSSION: Lower-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.

Indexed as

AgingCognitionAgedEpidemiologic StudiesHumansMiddle AgedReproducibility of ResultsSurveys and QuestionnairesAssessmentCognitionMeasurementResearch methods and issues

Identifiers

PMID38460115
PMCPMC10998342

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.