Learning needs and perceived barriers and facilitators to end-of-life care: a survey of front-line nurses on acute medical wards
Bibliographic record
Abstract
OBJECTIVES: Caring for dying hospitalised patients is a healthcare priority. Our objective was to understand the learning needs of front-line nurses on the general internal medicine (GIM) hospital wards, and perceived barriers to, and facilitators of, optimal end-of-life care. METHODS: We developed an 85-item survey informed by the Theoretical Domains Framework and Capability-Opportunity-Motivation-Behaviour system. We included demographics and two main domains (knowledge and practice; delivering end-of-life care) with seven subsections. Nurses from four GIM wards and the nursing resource team completed this survey. We analysed and compared results overall, by Capability, Opportunity, and Motivation, and by survey domain. We considered items with median scores <4/7 barriers. We conducted an a priori subgroup analysis based on duration of practice (≤5 and >5 years). RESULTS: Our response rate was 60.5% (144/238). 51% had been practising for >5 years; most respondents were female (93.1%). Nurses had similar scores on the knowledge (mean 76.0%; SD 11.6%) and delivering care (mean 74.5% (8.6%)) domains. Scores for items associated with Capability were higher than those associated with Opportunity (median (first, third quartiles) 78.6% (67.9%, 87.5%) vs 73.9% (66.0%, 81.8%); p=0.04). Nurses practising >5 years had significantly higher scores on all analyses. Barriers included engaging with families having strong emotional reactions, managing goals of care conflicts between patients and families, and staffing challenges on the ward. Additional requested resources included formal training, information binders and more staff. Opportunities for consideration include formalised on-the-job training, access to comprehensive information, including symptom management at the end of life, and debriefing sessions. CONCLUSIONS: Front-line nurses reported an interest in learning more about end-of-life care and identified important barriers that are feasible to address. These results will inform specific knowledge translation strategies to build capacity among bedside nurses to enhance end-of-life care practices for dying patients on GIM wards.
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 | 0.003 | 0.017 |
| 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".