The Acceptability of Humor between Palliative Care Patients and Health Care Providers
Bibliographic record
Abstract
BACKGROUND: Humor frequently occurs in palliative care environments; however, the acceptability of humor, particularly between patients and health care providers has not been previously examined. OBJECTIVES: To explore the importance and acceptability of humor to participants who are patients in a palliative care context, the study determines if demographics are correlated with the degree of acceptability, and examines the acceptance of humor by patients with advanced illness when interacting with nurses or physicians. METHODS: One hundred participants admitted to a palliative care unit or residential hospice were surveyed. Basic demographic data were collected, as well as responses on a five-point Likert scale to a variety of questions regarding the participants' attitudes about humor before and after their illness and the acceptability of humor in a palliative setting. Participants were also given the opportunity to comment freely on the topic of humor and the palliative experience. RESULTS: A large majority of participants valued humor highly both prior to (77%) and during (76%) their illness experience. Despite this valuation, the frequency of laughter in their daily lives diminished significantly as patients' illness progressed. Most participants remembered laughing with a nurse (87%) and a doctor (67%) in the week prior to the survey, and found humor with their doctors (75%) and nurses appropriate (88%). CONCLUSION: The vast majority of participants found humorous interactions with their health care providers acceptable and appropriate, and this may indicate a opportunity for enhanced and more effective end-of-life care in the future.
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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 | 0.005 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".