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Record W4408460421 · doi:10.1186/s12912-025-02867-7

The effectiveness of nursing interventions to improve self-care for patients with heart failure at home: a systematic review and meta-analysis

2025· review· en· W4408460421 on OpenAlexaff
Jessica Longhini, Kayla Gauthier, Hanne Konradsen, Alvisa Palese, Zarina Nahar Kabir, Nana Waldréus

Bibliographic record

VenueBMC Nursing · 2025
Typereview
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsWestern University
FundersKarolinska Institutet
KeywordsMedicineNursing researchPsychological interventionNursing managementNursing Interventions ClassificationNursingHeart failureMeta-analysisIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

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.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.029
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.043
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0290.047
Bibliometrics0.0100.008
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.041
GPT teacher head0.378
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations20
Published2025
Admission routes1
Has abstractyes

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