Attrition of older adults in web-based health interventions: Survival analysis within an observational cohort study

To identify demographics and personal motivation types that predict dropping out of eHealth interventions among older adults. We conducted an observational cohort study. Participants completed a pre-test questionnaire and got access to an eHealth intervention, called Stranded, for 4 weeks. With survival and Cox-regression analyses, demographics and types of personal motivation were identified that affect drop-out. Ninety older adults started using Stranded. 45.6% participants continued their use for 4 weeks. 32.2% dropped out in the first week and 22.2% dropped out in the second or third week. The final multivariate Cox-regression model which predicts drop-out, consisted of the variables: perceived computer skills and level of external regulation. Predicting the chance of dropping out of an eHealth intervention is possible by using level of self-perceived computer skills and level of external regulation (externally controlled rewards or punishments direct behaviour). Anticipating to these factors can improve eHealth adoption.

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Publication Details

Journal
Journal of Health Psychology
Published
2024-09-14
DOI
https://doi.org/10.1177/13591053241274097
Primary Topic
Mobile Health and mHealth Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Attrition of older adults in web-based health interventions: Survival analysis within an observational cohort study

Hermie Hermens, Marian Z.M. Hurmuz, Stephanie Jansen-Kosterink, Lex van Velsen
Journal of Health Psychology
Mobile Health and mHealth Applications
article

Attrition of older adults in web-based health interventions: Survival analysis within an observational cohort study

Hermie Hermens, Marian Z.M. Hurmuz, Stephanie Jansen-Kosterink, Lex van Velsen
article en

Abstract

To identify demographics and personal motivation types that predict dropping out of eHealth interventions among older adults. We conducted an observational cohort study. Participants completed a pre-test questionnaire and got access to an eHealth intervention, called Stranded, for 4 weeks. With survival and Cox-regression analyses, demographics and types of personal motivation were identified that affect drop-out. Ninety older adults started using Stranded. 45.6% participants continued their use for 4 weeks. 32.2% dropped out in the first week and 22.2% dropped out in the second or third week. The final multivariate Cox-regression model which predicts drop-out, consisted of the variables: perceived computer skills and level of external regulation. Predicting the chance of dropping out of an eHealth intervention is possible by using level of self-perceived computer skills and level of external regulation (externally controlled rewards or punishments direct behaviour). Anticipating to these factors can improve eHealth adoption.

Journal of Health PsychologyVol. 30(8)
Roessingh Research and Development (NL), University of Twente (NL)
Eurostars
Quality Education
Openalex Percentile: Top 73%
Mobile Health and mHealth Applications
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