Mobile App for Patients With Chronic Obstructive Pulmonary Diseases During Home-Based Exercise Care: Usability Study
Bibliographic record
Abstract
BACKGROUND: Digital health tools have demonstrated promise in the treatment and self-management of chronic diseases while also serving as an important means for reducing the workload of health care professionals (HCPs) and enhancing the quality of care. However, these tools often merely undergo large-scale testing or enter the market without undergoing rigorous user experience analysis in the early stages of their development, leading to frequent instances of low use or failure. OBJECTIVE: This study aims to assess the usability of and satisfaction with a mobile app designed for the clinical monitoring of patients with chronic obstructive pulmonary disease undergoing pulmonary rehabilitation at home. METHODS: This study used a mixed methods approach involving two key stakeholders-patients with chronic obstructive pulmonary disease and HCPs-across three phases: (1) mobile app mock-up design, (2) usability testing, and (3) satisfaction evaluation. Using convenience sampling, participants were grouped as HCPs (n=12) and patients (n=18). Each received a tablet with mock-ups for usability testing through interviews, with audio recordings transcribed and analyzed anonymously in NVivo12.0, focusing on mock-up features and usability insights. Task difficulty was rated from 1 (very easy) to 5 (very difficult), with noncompletion deemed a critical error. Usability satisfaction was measured on a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree). RESULTS: The research indicated a notable difference in app usability perceptions: 66% (8/12) of HCPs found tasks "very easy," compared to only 22% (4/18) of patients. Despite this, no participant made critical errors or withdrew, and satisfaction was high. HCPs completed tasks in about 20 minutes, while patients took 30. Older adults faced challenges with touch screens and scroll menus, suggesting the need for intuitive design aids like auditory support and visual health progress indicators, such as graphs. HCPs noted potential data delays affecting service, while non-native-speaking caregivers faced interpretation challenges. A secure pairing system for privacy in teleconsultations proved difficult for older users; a simpler icon-based system is recommended. This study highlights the need to consider stakeholder abilities in medical app design to enhance function implementation. CONCLUSIONS: Most HCPs (11/12, 91%) found the app intuitive, though they recommended adding icons to show patient progress to support clinical decisions. In contrast, 62% (11/18) of patients struggled with tablet navigation, especially with connectivity features. To ensure equitable access, the design should accommodate older users with diverse abilities. Despite challenges, both groups reported high satisfaction, with patients expressing a willingness to learn and recommending the app. These positive usability evaluations suggest that, with design improvements, such apps could see increased use in home-based care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".