The effectiveness of nursing interventions to improve self-care for patients with heart failure at home: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Self-care plays an important role in the treatment of patients with heart failure (HF) and adequately performed self-care at home can contribute to fewer hospitalizations, lower mortality risk and require less emergency care. The aim of this systematic review and meta-analysis was to synthesise evidence on the effectiveness of nursing interventions on HF-related self-care at home. Methods Medline, Scopus, Cumulative Index to Nursing and Allied Health Literature, Cochrane database, Web of Science, PsycInfo, and trial registers were searched up to 31st December 2022. We aimed to include experimental and observational studies with a control group investigating nursing interventions including transitional care, home care programs, phone calls, digital interventions, or a combination thereof on self-care of patients with HF. Outcomes were self-care maintenance, self-care management, and self-care behaviours, measured with various instruments. The screening and data extraction were performed independently by two reviewers, and disagreements were solved by a third reviewer. Cochrane risk of bias tool for randomised trials and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach were used. Results Twenty-seven studies were included (2176 participants), of which 24 were randomised controlled trials. Three categories of interventions emerged, called “transitional care”, “home care”, and “remote interventions”. Transitional care aimed at caring for patients at their homes after discharge through phone calls, digital interventions, and home visits may result in little to no difference in self-care maintenance (MD 7.26, 95% CI 5.20, 9.33) and self-care management (MD 5.02, 95% CI 1.34, 8.69) while contrasting results emerged in self-care behaviours since two out of six studies reported no improvements in self-care. Home care combined with phone calls or digital interventions likely increase self-management and self-care behaviours (MD -7.91, 95% CI -9.29, -6.54). Remote care could improve self-care behaviours when delivered as phone call programs, but they are ineffective on all outcomes when delivered as digital interventions alone. Conclusion Transitional care and home care combined with phone calls and digital interventions, and phone calls caring for patients at their home could slightly improve self-care in patients with HF. However, more research is needed to study the effects across different domains of self-care and of interventions delivered through digital interventions alone.
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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 | 0.018 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.029 | 0.046 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".