Workplace continuing education for nurses caring for hospitalised older people
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To develop, implement and evaluate a workplace continuing education programme about nursing care of hospitalised older people. BACKGROUND: The healthcare system cannot rely solely upon nurses' prelicensure education to prepare them to meet the evolving needs of hospitalised older patients. Over the past decade, there has been a dramatic rise in the proportion of older people in hospitals, yet many nurses do not have specialised knowledge about the unique care needs of this population. DESIGN: A multimethod pre-to post-design was employed. METHODS: Between September 2013 and April 2014, data were collected via surveys, focus groups and interviews. Thirty-two Registered Nurses initially enrolled in the programme of which 22 completed all data points. Three managers also participated in interviews. One-way repeated-measures ANOVAs were conducted to evaluate the effect of the programme and change over time. Qualitative data were analysed using thematic analysis. RESULTS: Survey results indicated improvements in perceptions about nursing care of older people but no changes in knowledge. Themes generated from the qualitative data focused on participants' experiences of taking part in the programme and included: (i) relevance of content and delivery mode, (ii) value of participating in the programme and (iii) continuing education in the context of acute care. CONCLUSIONS: This study illustrated the potential role of workplace continuing education in improving care for hospitalised older people, particularly the potential to change nurses' perceptions about this population. Nurses prefer learning opportunities that are varied in delivery of educational elder-focused content and accessible at work. Organisational leaders need to consider strategies that minimise potential barriers to workplace continuing education. IMPLICATIONS FOR PRACTICE: Workplace continuing education can play a key role in improving quality of care for hospitalized older adults and ought to be a priority for employers planning education for nurses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".