What are the differences among occupational groups related to their palliative care-specific educational needs and intensity of interprofessional collaboration in long-term care homes?
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to compare the differences across occupational groups related to their end-of-life care-specific educational needs and reported intensity of interprofessional collaboration in long-term care (LTC) homes. METHODS: A cross-sectional survey, based on two questionnaires, was administered at four LTC homes in Ontario, Canada using a modified Dilman's approach. The first questionnaire, End of Life Professional Caregiver Survey, included three domains: patients and family-centered communication, cultural and ethical values, effective care delivery. The Intensity of Interprofessional Collaboration Scale included two subscales: care sharing activities, and interprofessional coordination. In total, 697 LTC staff were given surveys, including personal support workers, support staff (housekeeping, kitchen, recreation, laundry, dietician aids, office staff), and registered staff (licensed nurses, physiotherapists, social workers, pharmacists, physicians). RESULTS: A total of 317 participants completed the survey (126 personal support workers, 109 support staff, 82 registered staff) for a response rate of 45%. Significant differences emerged among occupational groups across all scales and subscales. Specifically, support staff rated their comfort of working with dying patients significantly lower than both nurses and PSWs. Support staff also reported significantly lower ratings of care sharing activities and interprofessional coordination compared to both registered staff and personal support workers. CONCLUSIONS: These study findings suggest there are differing educational needs and sense of interprofessional collaboration among LTC staff, specific to discipline group. Both the personal support workers and support staff groups appeared to have higher needs for education; support staff also reported higher needs related to integration on the interdisciplinary team. Efforts to build capacity within support staff related to working with dying residents and their families are needed. Optimal palliative care may require resources to increase the availability of support for all staff involved in the care of patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".