Impressions and Perceptions of a Smartphone and Smartwatch Self-Management Tool for Patients With COPD: A Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Patients with chronic obstructive pulmonary disease (COPD) often do not seek care until they experience an exacerbation. Improving self-management for these patients may increase health-related quality of life and reduce hospitalizations. Patients are willing to use wearable technology for real-time data reporting and perceive mobile technology as potentially helpful in COPD management, but there are many barriers to the uptake of these technologies. OBJECTIVE: We aimed to understand patients' experiences using a wearable and mobile app and identify areas for improvement. METHODS: We conducted semi-structured interviews as part of a larger prospective cohort study wherein patients used a wearable and app for 6 months. We asked which features patients found accessible, acceptable and useful. RESULTS: We completed 26 interviews. We summarized our research findings into four main themes: (1) information, support and reassurance, (2) barriers to adoption, (3) impact on communication with health care providers, and (4) opportunities for improvement. Most patients found the feedback received through the app to be reassuring and useful. Some patients experienced technical difficulties with the app and found the wearable to be uncomfortable. CONCLUSIONS: Patients found a wearable device and mobile application to be acceptable and useful for the management of COPD. We identified barriers to adoption and opportunities for improvement to the design of our app. Further research is needed to understand what people with COPD and their healthcare providers want and will use in a mobile app and wearable for COPD 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".