A Pilot Study Evaluating the Effectiveness of a Training Module Designed to Improve Hospice Palliative Care Volunteers’ Ability to Deal With Unusual End-of-Life Phenomena
Bibliographic record
Abstract
The need for training to help healthcare professionals and hospice palliative care volunteers deal with unusual experiences at or around the end of a person's life is an oft-repeated theme in the scientific literature. A pilot study was conducted to examine the effectiveness of a training module designed to improve volunteers' ability to recognize, understand, and respond to unusual end-of-life phenomena (EOLP) in their work with dying patients and their families. Twenty-four volunteers from two community-based hospice palliative care programs completed the 25-item Coping with Unusual End-of-Life Experiences Scale (CUEES) prior to and immediately after attending a lecture and PowerPoint training module. A series of paired samples t tests revealed significant pre- and post-training differences on 14 items, suggesting that volunteers felt more knowledgeable about EOLP, better prepared to deal with EOLP, and more comfortable talking about EOLP with others following the training. The need for additional data is discussed.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".