Feasibility of a Mobile Phone App to Promote Adherence to a Heart-Healthy Lifestyle: Single-Arm Study
Bibliographic record
Abstract
BACKGROUND: Long-term maintenance of preventive activities is fundamental for achieving improved outcomes in cardiac rehabilitation (CR). Despite this, it has been shown to be a major challenge for many patients to follow recommendations and thereby adhere to a heart-healthy lifestyle. Mobile phone apps have been emphasized as potential tools to promote preventive activities after attendance in a CR program. Before commencing a trial to assess the potential effect of using an app to promote long-term adherence to preventive activities after attendance in CR, a study to assess if it is feasible to use an app is warranted. OBJECTIVE: The goal of the research is to assess if it is feasible to use a mobile phone app for promoting and monitoring patients' adherence to a heart-healthy lifestyle after CR. METHODS: The study included an experimental, pre-post single-arm trial lasting for 12 weeks. All patients received access to an app aimed to guide individuals to change or maintain a heart-healthy lifestyle. During the study period, patients received weekly, individualized monitoring through the app, based on their own goals. Feasibility outcomes assessed were recruitment rate, adherence to the app, resource requirements, and efficacy regarding capability to detect a change in quality of life, health status, and perceived goal achievement as well as evaluating ceiling and floor effect in these outcomes. Criteria for success were preset to be able to evaluate whether the app was feasible to use in a potential future RCT. RESULTS: In total, 71% (17/24) of the patients who completed CR were eligible for a potential RCT as well as for this study. All 14 patients included in the study used the app to promote preventive activities throughout the study. Satisfaction with the technology was high, and the patients found the technology-based follow-up intervention both useful and motivational. Ceiling effect was present in more than 20% of the patients in several domains of the questionnaires evaluating quality of life (36-Item Short Form Health Survey and COOP/WONCA functional health assessments) and health status (EQ-5D). Overall self-rated health status (EuroQol Visual Analog Scale) and perceived goal achievement were found to be outcomes able to detect a change. CONCLUSIONS: Individual follow-up through an app after attendance in CR is feasible. All patients used the app for preventive activities and found the app both useful and motivating. Several points of guidance from the patients in the study have been adopted and incorporated into the final design of the RCT now in the field.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".