Preferences for Communication About End‐of‐Life Care in Atypical Parkinsonism
Bibliographic record
Abstract
BACKGROUND: Studies on preferences regarding discussions on end-of-life care (EOLC), advance care planning (ACP), medical assistance in dying (MAiD), and brain donation have not yet been conducted in patients with atypical parkinsonism (AP). OBJECTIVE: The aim of this study was to know the preferences of patients with AP regarding discussions on EOLC, ACP, MAiD, and brain donation. METHODS: This cross-sectional study was conducted in patients clinically diagnosed with AP. An adapted questionnaire that assessed various potential factors that affect patients' preferences regarding EOLC and ACP was sent through postal mail to 278 patients. RESULTS: A total of 90 completed questionnaires were returned. Most patients preferred to discuss at the time of diagnosis information about the disease, its natural course, treatment options, and prognosis. In contrast, they preferred that EOLC and ACP be discussed when the disease has progressed. No demographic or disease-related factors were found to be predictors of the patient's preferences. Notably, most patients (63.3%) had previous actual discussions on these issues. Less than a third of patients were open to discussions about MAiD and brain donation; older age and the importance of spirituality and religion decreased the odds of discussing these. CONCLUSIONS: Our study demonstrates that patients with AP have preferences regarding the timing of the discussion of the different themes surrounding EOLC and ACP. A needs-based approach in initiating and conducting timely discussions on these difficult but essential issues is proposed. A thorough explanation and recognition of a patient's beliefs are recommended when initiating conversations about MAiD and brain donation. © 2021 International Parkinson and Movement Disorder Society.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".