Hospital Doctors’ Experiences of Caring for Dying Patients
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to examine, by means of a postal questionnaire, the experience of all grades of doctors caring for patients dying in an acute hospital in Scotland. METHOD: A postal questionnaire was sent to 306 doctors working in inpatient medical and surgical specialties, emergency medicine, anaesthetics and intensive care medicine in an acute hospital. RESULTS: There was an overall 41% response rate (127/306). Of responding doctors 55% had cared for 10 or more patients in the previous year. A quarter of respondents had personal experience of bereavement outside of clinical practice within the previous year. A total of 65% of responding doctors agreed that their most memorable patient death had had a strong emotional impact upon them. Responding doctors reported benefit from peer support. There was no association between length of time as a doctor and difficulty rating for talking to patients about death (p-value: 0.203). There was no association between difficulty rating and length of time working as a doctor when talking to relatives about death and dying (p-value: 0.205). We considered the questionnaire responses in relation to Scottish Government policy and initiatives associated with the care of the dying, and the future training and support of doctors caring for this group of patients and their relatives. CONCLUSION: Doctors describe similar experiences in terms of communication difficulties and emotional effects of caring for dying patients irrespective of their length of time working as a doctor.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".