Older Adults’ Attrition to Web-Based Health Interventions: Survival Analysis Within an Observational Cohort Study

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

Research output: Working paperPreprintAcademic

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Abstract

Background: Drop-outs within eHealth interventions often reach a high number, which impacts their added value on a population level. To improve eHealth adoption, it is necessary to know which demographics predict dropping out of an eHealth intervention in order to develop countermeasures.

Objective: The goal of this study is to identify demographics and personal motivation types that predict dropping out of eHealth interventions among older adults.

Methods: An observational cohort study was conducted with older adults in the Netherlands. Participants completed a pre-test questionnaire and got access to an eHealth service, called Stranded, for four weeks. With survival and Cox-regression analyses, demographics and types of personal motivation were identified that affected drop-out.

Results: Ninety older adults started using Stranded. 45.6% of these participants continued their use for four weeks. 32.2% of the 90 participants dropped out in the first week (N=29). The remaining 22.2% dropped out in the second or third week of this study (N=13 in week 2, N= 7 in week 3). The final multivariate Cox-regression model which predicts drop-out, consisted of the following variables: perceived computer skills (HR=0.69, BI=0.49-0.99, P=.04) and level of external regulation (HR=1.19, BI=1.03-1.37, P=.02).

Conclusions: Predicting the chance of dropping out of an eHealth intervention is possible by using their level of self-perceived computer skills and their level of external regulation (externally controlled rewards or punishments direct behavior). Anticipating to these factors can improve eHealth adoption.
Original languageEnglish
PublisherSocial Science Research Network (SSRN)
Number of pages33
DOIs
Publication statusPublished - 13 Apr 2021

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