Home care nursing practice for older persons with heart failure living at home
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To enhance knowledge of how older people with heart failure, living at home, manage their illness with the support of their family caregivers and home care nursing services. BACKGROUND: Heart failure monitoring and self-care have been important means of reducing the serious impact of heart failure. Drawing on theories of practice as enacted and conceptualising service users and their family caregivers as active, the idea of attunement was used to explore how home care nurses work in supporting them. DESIGN: Ethnographic case study. METHOD: Data collection involved home visits and interviews (10 home care users, 10 caregivers, five home care team leaders). Data were field-notes and transcribed interviews. Themes were deductively developed from the findings, informed by the theoretical background, using content analysis. The COREQ checklist was used. FINDINGS: Three themes were developed from the data: (1) Practices of attunement in relations, (2) Becoming among difficulties and (3) Off track-difficult to attune around self-care. CONCLUSIONS: The findings reflect the complexity of heart failure monitoring at home, showing how, in addition to self-care measures, users are supported by an array of informal and formal care. The caregiving situation is shaped by relations among participants and involves making oneself available to the situation. We suggest a stance of attunement for home care nurses, which demands tact and calls for interest, engagement and openness. RELEVANCE TO CLINICAL PRACTICE: Study findings caution against limiting heart failure monitoring to circumscribed tasks, instead calling for a holistic understanding of what may be helpful for users. Home care nurses need time to attune with users living with heart failure and their caregivers to prevent exacerbations and promote well-being. NO PATIENT OR PUBLIC CONTRIBUTION: Although patients were not formally involved in study design ethnography favours their voice.
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".