Attitude of emergency doctors in providing palliative and end-of-life care in Hong Kong and education needs: A prospective cross-sectional analysis based on self-reported surveys.
Bibliographic record
Abstract
Abstract Introduction: In view of the growth of the aging population in Hong Kong, the importance and need of palliative care and end-of-life (EOL) care were brought into the spotlight. The Department of Accident and Emergency (AED) was one of first medical contacts for the public. Despite the urge to investigate this issue, there were no related studies involving emergency physicians in Hong Kong previously. The objectives of this study were to evaluate the attitude of emergency doctors in providing palliative and EOL care in Hong Kong, and to investigate the education needs for emergency doctors in palliative and EOL care. Methods: This research was a questionnaire study. Emergency physicians from 6 AED in Hong Kong were recruited. The questionnaires were designed to cover the attitudes of emergency physicians towards palliative and EOL care in terms of the role of palliative and EOL care in AED, the specific obstacles in providing it and the comfort level with the care; and further education needs.Results: 145 emergency physicians completed the questionnaires, in which 60 respondents from the service-providing hospitals. Significant proportions from both groups recognized palliative and EOL care was an important competence for them, but was uncertain about its role and priority in AED. Lack of time and access to palliative and EOL care specialists/ teams were the major barriers. Group 1 staff was more comfortable to provide the care and discuss it with patients and relatives. Further education needs, apart from the management of physical complaints like pain management, topics including communication skills and EOL care ethics were also emphasized.Conclusions: The study revealed several obstacles which required additional resources and manpower for overcoming them, in order to further promote the palliative and EOL care in Emergency Medicine. Further education, especially communication skills and ethical issues, were necessary as well. With the combination of elements of routine AED practice and the basic palliative medicine skill set, it would promote the development of this emerging field in Emergency Medicine 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".