Nurses’ perspectives on how operational leaders influence function-focused care for hospitalised older people
Bibliographic record
Abstract
AIMS: To explore nurses' perspectives on how leaders influence function-focused care, defined as care that preserves and restores older people's functional abilities. BACKGROUND: Hospitalised older people are at risk of functional decline. Although leaders have the potential to influence function-focused care, few studies have explored nurses' perspectives on how leaders influence function-focused care. METHODS: Thirteen focus groups were held with 57 acute care nurses. Semi-structured questions prompted discussion on nurses' perspectives, needs and strategies to meet their needs. Data were thematically analysed. RESULTS: Three themes were identified: (1) the emphasis in hospitals is on moving older people quickly through the system, not supporting their functioning; (2) leaders are generally seen as too disconnected from practice to design system efficiency initiatives that support older people's functioning and nurses' provisioning of function-focused care; and (3) leadership strategies to better support nurses in providing function-focused care to older people in the context of system efficiency. CONCLUSIONS: Leaders should connect with practice to devise age-sensitive efficiency initiatives that support function-focused care. Nurses need support from leaders in four areas to provide function-focused care to older people in the current hospital context. IMPLICATIONS: The findings provide direction on how leaders can facilitate function-focused care in the current health-care environment emphasising system efficiency.
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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 | 0.000 | 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".