Related Experiment Video
Updated: Oct 5, 2025
11:21
Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
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Investigating When, Which, and Why Users Stop Using a Digital Health Intervention to Promote an Active Lifestyle:
Helene Schroé1,2, Geert Crombez2, Ilse De Bourdeaudhuij1
1Department of Movement and Sports Sciences, Faculty of Medicine and Health, Ghent University, Ghent, Belgium.
JMIR Mhealth and Uhealth
|January 31, 2022
Summary
Nearly half of participants in a digital health intervention for physical activity (PA) and sedentary behavior (SB) dropped out, mainly early on. Psychological factors and time-consuming questionnaires predicted attrition, suggesting personalization and streamlined data collection are key.
Area of Science:
- Digital health interventions
- Behavioral science
- Public health
Background:
- Digital health interventions show promise for behavior change but suffer from high attrition rates.
- Understanding attrition is crucial to improve the potential and accessibility of these interventions.
- Psychological determinants of behavior change are underexplored as predictors of attrition.
Purpose of the Study:
- To examine when, which, and why users discontinued a digital health intervention.
- To investigate psychological determinants of behavior change as predictors of attrition.
Main Methods:
- 473 healthy adults used the MyPlan 2.0 intervention for physical activity (PA) or sedentary behavior (SB) reduction.
- Logistic regression analyzed demographic variables and Health Action Process Approach (HAPA) determinants predicting attrition.
- Questionnaires assessed reasons for discontinuation.
Main Results:
- 47.9% of participants dropped out, primarily during the initial phase.
- Gender and HAPA determinants (action planning, coping planning, self-monitoring) predicted intervention completion.
- Key reasons for attrition included time-consuming questionnaires, lack of time, content dissatisfaction, and technical issues.
Conclusions:
- Attrition in digital health interventions is significant and often occurs early.
- Personalization, minimizing questionnaires, and robust technical testing are vital for reducing attrition.
- Future research should focus on optimizing intervention design to enhance user engagement and adherence.
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