News Brief: NPs and PAs unsure about participating in medical aid in dying.
Bibliographic record
Abstract
NPs and PAs unsure about participating in medical aid in dying. A significant number of advanced practice professionals (APPs; specifically, NPs and physician assistants) are uncertain about participating in medical aid in dying (MAID), according to a study in the October JAMA Network Open. MAID involves prescribing life-ending medication to terminally ill patients with less than six months of life expectancy. It is an increasingly accepted practice in European countries and Canada and is becoming more common in the United States. Ten states and the District of Columbia have passed laws permitting MAID under a range of conditions. In 2021, New Mexico became the first state to pass legislation giving MAID prescription authority to APPs, and other states with MAID laws are considering doing the same. Yet, in a recent survey of 77 APPs working at a comprehensive cancer center in Washington State, only 51% of respondents reported willingness to prescribe or consult about the medications, while 40% were uncertain, and 9% were not willing to participate. Despite these varied responses, 91% of respondents supported the legalization of MAID.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.048 | 0.019 |
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".