Back

Dolodoc, a mobile application for the self-management of chronic pain: Acceptability and usability study

Guebey, J.; Gosetto, L.; Rehberg-Klug, B.; Lovis, C.; Ehrler, F.; Molinard-Chenu, A.

2025-10-31 health systems and quality improvement
10.1101/2025.10.28.25338623 medRxiv
Show abstract

BackgroundApproximately 19% of adults in Europe are affected by chronic pain, which reduces quality of life. Pain management apps (mHealth) offer a promising solution for self-management, but users engagement and adherence can be a limitation to their clinical impact. User experience design and studies play an important role in optimizing usability and long-term adoption of digital health interventions. ObjectiveThis study aims to evaluate the user experience of Dolodoc, a mobile application for chronic pain self-management, using a mixed-methods approach that evaluates acceptability through a content quality survey and examines usability by analyzing overall usage patterns. MethodsA cross-sectional acceptability study was conducted among chronic pain patients recruited from the Geneva University Hospitals pain center and through snowball sampling. Participants rated 84 evidence-based self-management strategies using a five-point Likert scale based on 5 acceptability criterias: understandability, motivation, feasibility, relevance, and alignment with the related quality-of-life dimension. Usability was assessed through usage metrics that were collected over six months using Piwik PRO analytics to observe the usage behaviors of real-world Dolodoc users. ResultsIn the acceptability study, a total of 33 participants rated the self-management strategies positively across all dimensions. On a scale from -2 to 2, the strategies were well understood (mean = 1,47), motivational (1.12), feasible(1.01), relevant (0.99), and aligned with the dimensions (1.33). The usability study demonstrated that 60% of patients used Dolodoc only once, indicating that long-term adherence remains a challenge. Within Dolodoc, pain tracking, useful links and medication logging were the most actively used features. DiscussionThis study highlights the gap between acceptability and long-term adherence to mHealth solutions. Improving personalization and accessibility could increase user engagement and long-term adherence. Future iterations of the app should incorporate tailored interventions and real-time feedback mechanisms. In addition, taking advantage of a digital navigation follow-up could facilitate user adoption and sustained engagement.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.