Training Staff in Long-Term Care Facilities-Effects on Residents' Symptoms, Psychological Well-Being, and Proxy Satisfaction
Bibliographic record
Abstract
Abstract Context Long-term care facility (LTCF) residents have unmet needs in end-of-life and symptom care. Objectives This study examines the effects of an end-of-life care staff training intervention on LTCF residents’ pain, symptoms, and psychological well-being and their proxies’ satisfaction with care. Methods We report findings from a single-blind, cluster randomized controlled trial featuring 324 residents with end-of-life care needs in 20 LTCF wards in Helsinki. The training intervention included four 4-hour educational workshops on palliative care principles (advance care planning, adverse effects of hospitalizations, symptom management, communication, supporting proxies, challenging situations). Training was provided to all members of staff in small groups. Education was based on constructive learning methods and included participants’ own resident cases, role-plays, and small-group discussions. During a 12-month follow-up we assessed residents’ symptoms with the Edmonton Symptom Assessment Scale (ESAS), pain with the PAINAD instrument and psychological well-being using a PWB questionnaire. Proxies’ satisfaction with care was assessed using the SWC-EOLD. Results The change in ESAS symptom scores from baseline to 6 months favored the intervention group compared with the control group. However, the finding was diluted at 12 months. PAINAD, PWB, and SWC-EOLD scores remained unaffected by the intervention. All follow-up analyses were adjusted for age, gender, do-not-resuscitate order, need for help, and clustering. Conclusion Our rigorous randomized controlled trial on palliative care training intervention demonstrated mild effects on residents’ symptoms and no robust effects on psychological well-being or on proxies’ satisfaction with care.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".