Ethical implications of shared decision-making in Parkinson’s disease treatment
Bibliographic record
Abstract
Shared decision-making (SDM) involves an active participation of the patient in deciding treatment choice, based on his/her preferences, beliefs, and values. In the context of Parkinson's disease (PD), physicians encounter limitations in applying this model related to cognitive decline and other disease-related complications. Discussing the ethics of this approach on the context of these limitations the PD patient suffers is thus of great importance. This review intends to analyze ethical challenges of SDM in PD related to decision-making capacity, surrogates' role in patient's identity, and patients' and physicians' preferences. Although skepticism could arise when dealing with surrogates' decisions, a key for flourishing the patient's autonomy is acknowledging its relational context, as relatives' beliefs and values are imprinted in the patient's identity. To do so, empathy should be encouraged in physicians, recognizing the different value attribution that patients and their relatives have in the decision process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.015 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".