Bibliographic record
Abstract
AIMS AND OBJECTIVES: To offer an explanation of how registered nurses' are providing care to hospitalised older adults in nursing teams comprised of a variety of roles and educational levels. BACKGROUND: Around the globe economic pressures, nursing shortages and increased patient acuity have resulted in tasks being shifted to healthcare workers with less education and fewer qualifications than registered nurses. In acute care hospitals, this often means reducing the number of registered nurses and adding licensed practical nurses and care aides (also referred to as unregulated healthcare workers) to the nursing care team. The implications of these changes are not well understood especially in the context of hospitalised older adults, who are complex and the most common care recipients. DESIGN: Thematic analysis of data that were collected in a previous grounded theory study to provide an opportunity in-depth analysis of how nurses provided care to hospitalised older adults within nursing teams. METHODS: Data collected in western Canada on two hospital units in two different health authorities were analysed in relation to how nursing teams provide care. Hand coding and thematic analysis were employed. RESULTS: The themes of scrutinised skill mix and working together highlighted how the established nursing value of reciprocity is challenging to enact in teams with a variety of scopes of practice. The value of reciprocity both aided and hindered the nursing team in engaging in team behaviours to effectively manage patient care. CONCLUSION: Educators and leaders could assist the nursing care team in re-thinking how they engage in teamwork by providing education about roles and communication techniques to support teams and ultimately improve nursing care. RELEVANCE TO CLINICAL PRACTICE: The value of reciprocity within nursing teams needs to be re-examined within the context of team members with varying abilities to reciprocate in kind.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".