Growing pains: Lessons learned from a failed mobile mindfulness clinical trial for patients with complex care needs
Why this work is in the frame
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Bibliographic record
Abstract
This paper discusses lessons learned from a failed clinical trial investigating the use of a mobile application (app) to deliver a mindfulness intervention to middle-aged and older adults receiving services at a rehabilitation hospital in Ontario, Canada. A randomized controlled trial with 82 participants was planned, with the experimental group receiving access to a mindfulness app and a wait-list control group receiving access to the app after 4 weeks; however, the study could not be completed due to low recruitment rates. This implementation failure was considered from the perspective of the PARIHS framework. More specifically, Three key recruitment challenges were identified, and recommendations for future research provided. Firstly, the increasingly complex care needs of the study population appeared to influence eligibility; it would be beneficial for future research to consider adopting strategies to better understand the needs of the target population. Secondly, participants' stage of care and readiness of change likely negatively influenced compliance and retention in this study, and should be assessed in future research. Finally, a lack of clinician integration into the research team negatively impacted recruitment in this study; future studies should consider integrating direct service providers into the research team as this may increase buy-in and referral rates. The challenges and recommendations outlined can inform design and implementation of future studies in this area.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | medium |
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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it