The educational needs of nursing staff when working with hospitalised older people
Bibliographic record
Abstract
OBJECTIVES: To examine nursing staffs' geriatric knowledge, perceptions about interprofessional collaboration and patient-centred care, and perceived learning needs related to working with hospitalised older people. METHOD: A triangulation mixed methods design was used. A survey was administered to nursing staff that contained the Knowledge About Older Patients Quiz, the patient-centered Care measure and the Modified Index of Interdisciplinary Collaboration measure. Interviews were conducted to understand nursing staffs' learning needs. Survey data were analysed using descriptive statistics. Interview data were analysed using content analysis. Survey and interview data were then compared and contrasted. RESULTS: Twenty-two nursing staff (response rate 26%) completed surveys and 14 participated in interviews. The mean knowledge about older patients score was 22.95, indicating moderately high gerontological knowledge. The mean scores on the patient-centered Care measure and Modified Index of Interdisciplinary Collaboration were moderately high at 3.75 and 3.86, respectively. Themes developed from analysis of the interview data were as follows: complex vulnerable population, clinical care concerns and working as a team. In spite of scores on knowledge surveys, nursing staff identified learning needs related to managing the responsive behaviours of older patients with cognitive impairment, chemical and physical restraints, mobility and continence. CONCLUSIONS: There was an incongruence between survey and interview data as nursing staff reported gaps in their knowledge despite moderately high scores on the Knowledge about Older People Quiz. Further research is needed to understand additional factors that influence nurses' educational needs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".