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.
| Original language | English |
|---|---|
| Journal | Journal of health psychology |
| DOIs | |
| Publication status | E-pub ahead of print/First online - 14 Sept 2024 |
Keywords
- UT-Hybrid-D
- n/a OA procedure
- eHealth
- Older adults
- Patient characteristics
- Demographics
- Drop-out