Self-care Practices of Patients With Heart Failure Using Wearable Electronic Devices
Bibliographic record
Abstract
BACKGROUND: Heart failure (HF) is the fastest growing cardiovascular condition globally; associated management costs and hospitalizations place an immense burden on healthcare systems. Wearable electronic devices (WEDs) may be useful tools to enhance HF management and mitigate negative health outcomes. OBJECTIVE: We aimed to perform a systematic review to examine the potential of WEDs to support HF self-care in ambulatory patients at home. METHODS: Five databases were searched for studies published between 2007 and May 2022, including OVID MEDLINE, EMBASE (OVID), APA PsycINFO (OVID), Cochrane Central Register of Controlled Trials (OVID), and CINAHL Plus with Full Text (Ebsco). After 6210 duplicates were removed, 4045 records were screened and 6 were included for review (2 conference abstracts and 4 full-text citations). All studies used WEDs as 1 component of a larger intervention. RESULTS: Outcome measures included quality of life, physical activity, self-efficacy, self-care, functional status, time to readmission, social isolation, and mood. Studies were of moderate to high quality and mixed findings were reported. Enhanced exercise habits and motivational behavior to exercise, as well as decreased adverse symptoms of fatigue and dyspnea, were identified in 2 studies. However, improvements in exercise capacity and increased motivational behavior did not lead to exercise adherence in another 2 studies. CONCLUSIONS: The findings from this review suggest that WEDs may be a viable health behavior improvement strategy for patients with HF. However, studies of higher quality, with the primary intervention being a WED, and consistent outcome measures are needed to replicate the positive findings of studies identified in this review.
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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) | 0.000 | 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".