Deathbed Visions: Hospice Palliative Care Volunteers’ Experiences, Perspectives, and Responses
Bibliographic record
Abstract
11 female hospice palliative care volunteers who had either witnessed and/or had patients or patients' family members tell them about deathbed visions (DBVs) were interviewed about their experiences, perspectives, and responses. The volunteers responded to a series of guiding questions and shared stories about their patients' DBVs. During the interviews, the volunteers talked about, among other things, the impact of DBVs on their patients and themselves, how they responded to their patients' DBVs, and their explanations for them. The most common visitors appearing in the deathbed vision stories shared by the volunteers were their patients' deceased family members (parents, siblings). The volunteers described their patients' visions as having largely positive (e.g., comforting) effects on the patients as well as having a positive impact on themselves (e.g., lessening their own fear of death). The volunteers did not initiate conversations about DBVs with their patients, but responded appropriately by listening, asking questions, and not being dismissive if the patient brought it up first. All volunteers provided spiritual as opposed to medical or scientific explanations for DBVs. The implications and limitations of the findings are 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".