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Health and study dropout: health aspects differentially predict attrition

BACKGROUND: Participant dropout poses significant problems in longitudinal survey studies. Although it is often assumed that a participant’s health predicts future study dropout, only a few studies have examined this topic, with conflicting findings. This study aims to contribute to the literature b...

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Autores principales: Beller, Johannes, Geyer, Siegfried, Epping, Jelena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8802529/
https://www.ncbi.nlm.nih.gov/pubmed/35094681
http://dx.doi.org/10.1186/s12874-022-01508-w
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author Beller, Johannes
Geyer, Siegfried
Epping, Jelena
author_facet Beller, Johannes
Geyer, Siegfried
Epping, Jelena
author_sort Beller, Johannes
collection PubMed
description BACKGROUND: Participant dropout poses significant problems in longitudinal survey studies. Although it is often assumed that a participant’s health predicts future study dropout, only a few studies have examined this topic, with conflicting findings. This study aims to contribute to the literature by clarifying the relationship between different aspects of health and study dropout. METHODS: The 2008 baseline sample of the German Aging Survey was used to predict study dropout (N = 4442). Indicators of health included physical health using the number of chronic conditions, physical functioning using the SF-36 Physical Functioning subscale, cognitive functioning using the digit symbol substitution test, and depression using the CESD-15. RESULTS: It was found that different aspects of health had differential associations with survey dropout: Worse physical functioning and in part worse cognitive functioning predicted increased dropout rates; contrarily, worse physical health predicted decreased dropout when controlling for other health aspects and covariates. Depression was not significantly related to study dropout. CONCLUSIONS: Therefore, participants with chronic conditions, but minimal physical and cognitive disability were most likely to participate in the future. These findings suggest that health has a complex relationship with survey dropout and must be accounted for in longitudinal studies. Neglecting this systematic attrition due to health problems bears the risk of severely under- or overestimating health-related effects and trends.
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spelling pubmed-88025292022-02-02 Health and study dropout: health aspects differentially predict attrition Beller, Johannes Geyer, Siegfried Epping, Jelena BMC Med Res Methodol Research Article BACKGROUND: Participant dropout poses significant problems in longitudinal survey studies. Although it is often assumed that a participant’s health predicts future study dropout, only a few studies have examined this topic, with conflicting findings. This study aims to contribute to the literature by clarifying the relationship between different aspects of health and study dropout. METHODS: The 2008 baseline sample of the German Aging Survey was used to predict study dropout (N = 4442). Indicators of health included physical health using the number of chronic conditions, physical functioning using the SF-36 Physical Functioning subscale, cognitive functioning using the digit symbol substitution test, and depression using the CESD-15. RESULTS: It was found that different aspects of health had differential associations with survey dropout: Worse physical functioning and in part worse cognitive functioning predicted increased dropout rates; contrarily, worse physical health predicted decreased dropout when controlling for other health aspects and covariates. Depression was not significantly related to study dropout. CONCLUSIONS: Therefore, participants with chronic conditions, but minimal physical and cognitive disability were most likely to participate in the future. These findings suggest that health has a complex relationship with survey dropout and must be accounted for in longitudinal studies. Neglecting this systematic attrition due to health problems bears the risk of severely under- or overestimating health-related effects and trends. BioMed Central 2022-01-30 /pmc/articles/PMC8802529/ /pubmed/35094681 http://dx.doi.org/10.1186/s12874-022-01508-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Beller, Johannes
Geyer, Siegfried
Epping, Jelena
Health and study dropout: health aspects differentially predict attrition
title Health and study dropout: health aspects differentially predict attrition
title_full Health and study dropout: health aspects differentially predict attrition
title_fullStr Health and study dropout: health aspects differentially predict attrition
title_full_unstemmed Health and study dropout: health aspects differentially predict attrition
title_short Health and study dropout: health aspects differentially predict attrition
title_sort health and study dropout: health aspects differentially predict attrition
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8802529/
https://www.ncbi.nlm.nih.gov/pubmed/35094681
http://dx.doi.org/10.1186/s12874-022-01508-w
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