Clinical psychology

Psychiatry

Machine learning

Cognition

Psychology

Dentistry

Dropout (neural networks)

Health and Retirement Study

Computer science

Attrition

Gerontology

Medicine

BMC Medical Research Methodology

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.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.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.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.

Health and study dropout: health aspects differentially predict attrition