Duty to provide care to Ebola patients: the perspectives of Guinean lay people and healthcare providers
Bibliographic record
Abstract
AIM: To examine the views of Guinean lay people and healthcare providers (HCPs) regarding the acceptability of HCPs' refusal to provide care to Ebola patients. METHOD: From October to December 2015, lay people (n=252) and HCPs (n=220) in Conakry, Guinea, were presented with 54 sample case scenarios depicting a HCP who refuses to provide care to Ebola patients and were instructed to rate the extent to which this HCP's decision is morally acceptable. The scenarios were composed by systematically varying the levels of four factors: (1) the risk of getting infected, (2) the HCP's working conditions, (3) the HCP's family responsibilities and (4) the HCP's professional status. RESULTS: Five clusters were identified: (1) 18% of the participants expressed the view that HCPs have an unlimited obligation to provide care to Ebola patients; (2) 38% held that HCPs' duty to care is a function of HCPs' working conditions; (3) 9% based their judgments on a combination of risk level, family responsibilities and working conditions; (4) 23% considered that HCPs do not have an obligation to provide care and (5) 12% did not take a position. CONCLUSION: Only a small minority of Guinean lay people and HCPs consider that HCPs' refusal to provide care to Ebola patients is always unacceptable. The most commonly endorsed position is that HCPs' duty to provide care to Ebola patients is linked to society's reciprocal duty to provide them with the working conditions needed to fulfil their professional duty.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".