Accepted for/Published in: JMIR Human Factors
Date Submitted: Nov 30, 2024
Date Accepted: Nov 20, 2025
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Dynamic Indicators of Adherence and Retention in Digital Health Studies: Insights from the Brighten Study
ABSTRACT
Background:
Making optimal use of mobile health technologies requires the validation of digital biomarkers, which demands high levels of participant adherence and retention. However, current remote digital health studies have high attrition rates and low participant adherence, which may introduce bias and limit the generalizability of the findings.
Objective:
The objective of the study is to identify longitudinal indicators of participant retention and adherence, which may serve to develop strategies to improve data collection in digital health studies and improve understanding of how study cohorts are shaped by participant withdrawal and non-adherence.
Methods:
We performed secondary analyses on the Brighten study, which consisted of two remote, smartphone-based randomized controlled trials evaluating mobile apps for depression treatment, enrolling 2,193 participants. Participants were asked, after baseline assessment, to complete 7 digital questionnaires regularly. We assessed adherence to digital questionnaires, engagement (post-baseline participation), and retention rates (proportion of participants who continue completing questionnaires over time) as outcomes. We investigated the relationship between these outcomes and both static measures (e.g., demographics, average questionnaire scores) and dynamic measures (e.g., changes in questionnaire scores over time).
Results:
The study included 2201 participants, of whom 1093 completed at least one non-baseline questionnaire, with a median completion rate of 37.6%. We found significantly higher adherence rates in participants who were less depressed on average over the course of the study (P<.001) and in those who perceived clinical improvement (P=.001). There were significant demographic differences in adherence and engagement, specifically between gender, race, education, income, and income satisfaction. Participants who were more depressed at baseline were more likely to withdraw before completing any non-baseline questionnaire (t-score=-2.53, P=.01). However, participants who showed improvement in depressive symptoms during the study showed better adherence (Mann-Whitney U=127,084; P<.001) and retention (HR=0.78, 95% CI: [0.67, 0.91], P=.002), despite showing greater depressive symptoms at baseline.
Conclusions:
We show that the clinical trajectory of participants regarding their depressive symptoms, as well as their own perception of their improvement, are important indicators of engagement, adherence, and retention. Expanding knowledge regarding these longitudinal indicators may improve interpretation of outcomes and help build strategies to improve retention and adherence in future clinical trials.
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