Laypersons’ Priority-Setting Preferences for Allocating a COVID-19 Patient to a Ventilator: Does a Diagnosis of Alzheimer’s Disease Matter?
Bibliographic record
Abstract
PURPOSE: The current study aimed 1) to assess laypersons' priority-setting preferences for allocating ventilators to COVID-19 patients with and without AD while differentiating between a young and an old person with the disease, and 2) to examine the factors associated with these preferences. METHODS: A cross-sectional online survey was conducted among a sample of 309 Israeli Jewish persons aged 40 and above. RESULTS: Overall, almost three quarters (71%) of the participants chose the 80-year-old patient with a diagnosis of AD to be the last to be provided with a ventilator. The preferences of the remaining quarter were divided between the 80-year-old person who was cognitively intact and the 55-year-old person with AD. Education and subjective knowledge about AD were significantly associated with participants' preferences. CONCLUSION: Our results suggest that cognitive status might not be a strong discriminating factor for laypersons' preferences for allocating ventilators during the COVID-19 pandemic.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".