Identifying and Evaluating Mobile and Web Apps for Patients to Manage Hidradenitis Suppurativa: Systematic Search in App Stores and Content Analysis
Bibliographic record
Abstract
Background: Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease characterized by painful nodules, abscesses, and fistulas in intertriginous sites. It significantly impacts patients' quality of life. Early diagnosis and timely treatment are essential for disease control. Recurrent flares, suboptimal therapies, and prolonged misdiagnosis place a significant burden on both patients and health care systems. Objective: We aimed to identify mobile health apps (MHAs) for patients with HS and evaluate their quality through assessments by both patients and physicians. Methods: Two reviewers searched for mobile and web apps for HS, including those only available in German or English. Apps with advertising or non-patient-centered content and apps related to trials or conferences were excluded. Two apps met the criteria and were evaluated by 20 physicians and 27 patients using the Mobile App Rating Scale (MARS), user version of the MARS (uMARS), German Mobile App Usability Questionnaire, and technology affinity tools (Affinity for Technology Interaction Scale and Mobile Device Proficiency Questionnaire). Results: We identified 2 apps for managing HS that met the inclusion criteria-the HSR-Patients app and the EHSF-Hidradenitis Suppurativa app-from an initial pool of 29 proposed apps that included many nonmedical, non-HS-specific, and non-patient-centered apps. Patients rated the quality of the HSR-Patients app significantly higher than physicians (MARS: mean 3.01, SD 0.60 vs. uMARS: mean 3.53, SD 0.69; P=.009). In contrast, ratings for the EHSF-Hidradenitis Suppurativa app did not differ significantly (physicians: mean 2.81, SD 0.55; patients: mean 2.72, SD 0.79; P=.69). Usability, assessed with the German Mobile App Usability Questionnaire, showed no significant difference between physicians and patients for either app. For the HSR-Patients app, physicians and patients rated usability at 4.37 (SD 0.86) and 4.72 (SD 1.21; P=.27), respectively. For the EHSF-Hidradenitis Suppurativa app, physicians and patients rated usability at 3.88 (SD 0.77) and 3.38 (SD 1.35; P=.11), respectively. Patients showed a significantly higher general affinity for technology than physicians, as measured by the Affinity for Technology Interaction Scale (physicians: mean 3.62, SD 0.61; patients: mean 4.38, SD 1.30; P=.01). However, there was no significant difference in affinity for technology specifically when using mobile devices, as assessed by the Mobile Device Proficiency Questionnaire (physicians: mean 4.83, SD 0.25; patients: mean 4.69, SD 0.72; P=.41). Conclusions: This evaluation highlights the limited availability of high-quality, HS management-specific MHAs and underscores the need for more targeted digital tools. Differences in evaluations between patients and physicians were evident, with patients focusing on usability and practical guidance, while physicians prioritized content and usability. Neither the HSR-Patients app or the EHSF-Hidradenitis Suppurativa app demonstrated sufficient potential for long-term use, indicating the need for participatory development that includes all stakeholders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.024 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".