Home care nurses’ decisions about the need for and amount of service at the end of life
Bibliographic record
Abstract
AIMS: We explore home care nurse decision-making about the need for and amount of service by clients and families at the end of life. We identify factors nurses refer to when describing these decisions, situated within contextual features of nursing practice. BACKGROUND: Home care nurses are often responsible for decisions which have an impact on the access of clients and families to services at the end of life. Understanding how these decisions, are made, factors that are considered, and contextual influences is critical for improving access and enhancing care. METHODS: Qualitative data were collected between 2006 and 2008 from two samples of home care nurses: the first group (n = 29) recorded narrative descriptions of decisions made during visits to families. The second group (n = 27) completed in-person interviews focusing on access to care and their interactions with clients and families. Data were analysed with thematic coding and constant comparison. FINDINGS: Participants described assessing client and family needs and capacity. These assessments, at times integrated with considerations about relationships with clients and families, inform predictive judgements about future visits; these judgments are integrated with workload and home health resource considerations. In describing decisions, participants referred to concepts such as expertise, practice ideals and approaches to care. CONCLUSION: Findings highlight the role of considerations of family caregiver capacity, the influence of relationships and the importance of the context of practice, as part of a complete understanding of the complexity of access to care at the end of life.
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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 | 0.004 | 0.014 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".