Evidence map›Paper›PMID 42134789›Full record

ArticleJMIR human factors2026

A Chronic Pain Self-Management Mobile App (Dolodoc): Cross-Sectional Acceptability Study.

Julie Guebey, Laetitia Gosetto, Benno Rehberg, Christian Lovis, Frederic Ehrler, Aude Molinard-Chenu

Abstract read
In one paragraph

Article in JMIR human factors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Julie GuebeyDivision of Medical Information Science, University Hospital of Geneva, Geneva, Switzerland.ORCID 0009-0009-3758-4656
Laetitia GosettoDivision of Medical Information Science, University Hospital of Geneva, Geneva, Switzerland.ORCID 0000-0002-9432-2160
Benno RehbergAnesthesiology, University Hospital of Geneva, Geneva, Switzerland.ORCID 0000-0002-3145-1555
Christian LovisDivision of Medical Information Science, University Hospital of Geneva, Geneva, Switzerland.ORCID 0000-0002-2681-8076
Frederic EhrlerDivision of Medical Information Science, University Hospital of Geneva, Geneva, Switzerland.ORCID 0000-0001-9734-3242
Aude Molinard-ChenuDivision of Medical Information Science, University Hospital of Geneva, Geneva, Switzerland.ORCID 0000-0002-2552-9520

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundApproximately 19% of adults in Europe are affected by chronic pain, which reduces the quality of life. Pain-management mobile health (mHealth) apps offer a promising solution for self-management, but user engagement and adherence can limit their clinical impact. User experience design and research play a crucial role in optimizing usability and long-term adoption of digital health interventions.

objectiveThis study aims to evaluate the user experience of Dolodoc, a mobile app for chronic pain self-management, using a mixed methods approach that assesses acceptability through a content quality survey and examines use by analyzing overall use patterns.

methodsA cross-sectional acceptability study of the main content of Dolodoc was conducted among patients with chronic pain recruited from the Geneva University Hospitals pain center and through snowball sampling. Participants rated 84 evidence-based self-management strategies by using a 5-point Likert scale based on 5 acceptability criteria: understandability, motivation, feasibility, relevance, and alignment with the related quality-of-life dimension. To reduce participant fatigue and avoid random responses, the 84 strategies were randomly divided across survey versions. Use was assessed through metrics collected over 6 months with Piwik PRO Analytics to observe real-world use behaviors among Dolodoc users.

resultsIn the acceptability study, 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, SD 0.76), motivational (mean 1.12, SD 0.96), feasible (mean 1.01, SD 1.05), relevant (mean 0.99, SD 1.09), and aligned with the dimensions (mean 1.33, SD 0.89). The use study demonstrated that 60% (486/802) of the 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.

conclusionsThis 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, leveraging a digital navigation follow-up could facilitate user adoption and sustained engagement.

Indexed as

Chronic PainMobile ApplicationsPatient Acceptance of Health CareSelf-ManagementAdultAgedCross-Sectional StudiesDigital HealthFemaleHumansMaleMiddle AgedSurveys and QuestionnairesTelemedicinechronic paindigital healthmHealthmobile healthself-managementuser experience

Identifiers

PMID42134789
PMCPMC13219990

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.