Mobile Phone Apps for Inflammatory Bowel Disease Self-Management: A Systematic Assessment of Content and Tools
Bibliographic record
Abstract
BACKGROUND: The rising incidence of inflammatory bowel disease (IBD) over the past decade has resulted in increased health care utilization and longer IBD outpatient waiting lists. Self-management is recognized as an important aspect of chronic disease management but its application to IBD has been limited. The age of IBD onset in a majority of patients is in their 20s to 30s. Mobile phone apps are a technology familiar to young adults and represent an opportunity to explore self-management as a new model of health care delivery for IBD. OBJECTIVE: The aim of this study was to explore the content and tools of existing IBD apps to identify functionalities that may facilitate patient self-management. METHODS: We systematically assessed apps targeted at IBD patients via searches of Google (Android devices) and Apple (iOS devices) app stores with pre-defined inclusion and exclusion criteria. Apps were assessed for specific functionalities; presence of professional medical involvement; consistency with international IBD guidelines based on "complete," "partial," or "absent" coverage of consensus statements derived from the European Crohn's and Colitis Organisation, American College of Gastroenterology, and the Gastroenterology Society of Australia; comprehensiveness of data that could be entered; and average pricing. RESULTS: Of the 238 apps screened, 26 apps were assessed, including 10 available on Android platforms, 8 on iOS platforms, and 8 on both. Over half (14/26, 54%) of the apps had diary functionalities; over a third (10/26, 39%) provided health information about IBD. None of the apps offered decision support to facilitate the self-initiation of medical therapy. Five of 26 (19%) had professional medical involvement in their design. Apps demonstrated "complete" coverage of only 38% of the international consensus statements explored. The average price of the apps was AUD$1.37. CONCLUSIONS: Apps may provide a useful adjunct to the management of IBD patients. However, a majority of current apps suffer from a lack of professional medical involvement and limited coverage of international consensus guidelines. Future studies and app design for IBD should include professional medical involvement, evidence-based guidelines, and functionalities with decision support that are specifically tailored to patient self-management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".