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Record W2886868192 · doi:10.1177/0269216318794091

How do expatriate health workers cope with needs to provide palliative care in humanitarian emergency assistance? A qualitative study with in-depth interviews

2018· article· en· W2886868192 on OpenAlexfundno aff
Martin Schneider, François Chappuis, Sophie Pautex

Bibliographic record

VenuePalliative Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsnot available
FundersUniversité de FribourgMcGill University
KeywordsExpatriatePalliative careThematic analysisMedicineNursingQualitative researchHealth careDilemmaSociology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.076
GPT teacher head0.413
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2018
Admission routes1
Has abstractyes

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