User‐centered design features for digital health applications to support physical activity behaviors in solid organ transplant recipients: A qualitative study
Bibliographic record
Abstract
INTRODUCTION: Digital health tools may be effective in engaging solid organ transplant (SOT) recipients in physical activity (PA). This study examined the perspectives of SOT recipients regarding PA, and desired features for digital health tools. METHODS: Semi-structured interviews were used to explore perspectives of SOT recipients about barriers and motivators to physical activity, and core features of a digital health tool to support PA. Interviews were analyzed via thematic analysis. RESULTS: Participants included 21 SOT recipients (11 men, 10 women, 21-78 years, 1.5-16 years post-transplant) from various organ groups (four heart, five kidney, five liver, three lung, and four multi-organ). Barriers to PA included risk aversion, managing non-linear health trajectories, physical limitations and lack of access to appropriate fitness training. Facilitators of PA included desire to live long and healthy lives, renewed physical capabilities, access to appropriate fitness guidelines and facilities. Desired features of a digital health tool included a reward system, affordability, integration of multiple functions, and the ability to selectively share information with healthcare professionals and peers. CONCLUSIONS: SOT recipients identified the desired features of a digital health tool, which may be incorporated into future designs of digital and mobile health applications to support PA in SOT recipients.
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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) | 0.001 | 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".