Perspectives on the sustained engagement with digital health tools: protocol for a qualitative interview study among people living with Inflammatory Bowel Disease or irritable bowel syndrome
Bibliographic record
Abstract
INTRODUCTION: Digital health tools can be beneficial in the care of patients with chronic conditions and have the potential for widespread impact as readily scalable and cost-effective health interventions. However, benefits are often contingent on users sustaining their engagement with these tools over time. Sustained engagement with digital health tools can be challenging, and high rates of attrition from digital interventions are common. Inflammatory Bowel Disease (IBD) and irritable bowel syndrome (IBS) are prominent gastrointestinal conditions resulting in significant burdens for individuals and society. Emerging evidence suggests digital health tools can be beneficial for IBD and IBS management; however, it is not clear what barriers and enablers are experienced by people living with these conditions to sustaining their engagement with these tools, when necessary. Such knowledge could inform the tailoring of new and existing digital health tools to the needs of people living with IBD and/or IBS. This study will seek to identify the barriers and enablers of sustained engagement with digital health tools among adults living with IBD and/or IBS. METHODS AND ANALYSIS: We will conduct semistructured interviews with a purposive sample of approximately 30 adults (>18 years) who (a) reside in Canada, (b) self-report that they have been diagnosed with IBD and/or IBS, (c) have ever used a digital health tool (ie, any application/platform) to manage their condition and (d) are capable of providing informed consent. Interviews will be audio and video recorded and transcribed verbatim. Data will be coded deductively and barriers and enablers to sustained engagement will be categorised in accordance with the Theoretical Domains Framework. Data analysis will be verified by a patient research partner. ETHICS AND DISSEMINATION: The study has been approved by the Ottawa Health Science Network Research Ethics Board. The findings will inform the codevelopment of strategies to overcome modifiable barriers and leverage identified enablers of sustained engagement with digital health tools for IBD and IBS care. These strategies can inform the design of new, or modifications to existing, digital health tools for IBD and IBS care where sustained engagement is desirable. Strategies will be compiled into a guidebook and disseminated via the Inflammation, Microbiome and Alimentation: Gastro-Intestinal and Neuropsychiatric Effects (IMAGINE) Strategy for Patient Oriented Research chronic disease network in Canada.
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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 | 0.089 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.029 | 0.005 |
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".