How do expatriate health workers cope with needs to provide palliative care in humanitarian emergency assistance? A qualitative study with in-depth interviews
Bibliographic record
Abstract
BACKGROUND: Given the worldwide increase of chronic diseases, expatriate health workers on assignment with humanitarian emergency organisations can face more clinical situations that require advanced pain control or palliative care. Multiple reasons can prevent the provision of this care. AIM: To better know how health workers react to and cope with this dilemma. DESIGN: A qualitative interview study using inductive thematic analysis was performed. SETTING/PARTICIPANTS: A total of 15 expatriate health workers took part in individual in-depth interviews after their assignment with the organisation 'Médecins sans Frontières'. RESULTS: Clinical situations requiring advanced pain control or palliative care do occur during assignments. Expatriate health workers have different levels of knowledge of pain control and palliative care. Lacking opioids were a main reason for inadequate pain control. The expatriates felt helpless, distressed and frustrated in such situations. Peer support was sometimes helpful. Guidelines for palliative care in emergency settings would have been useful. CONCLUSION: Pain control and palliative care needs occur during clinical practice in emergency humanitarian assistance. Training for expatriate health workers should be improved. Humanitarian organisations should strengthen their capacity to provide pain control and palliative care by developing and applying adapted guidelines.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".