Could Depression and Loss of Dignity Correlate with Requesting Euthanasia and Physician-Assisted Suicide? A Look at the Research from the United States, Canada, and the Netherlands
Bibliographic record
Abstract
Euthanasia and physician-assisted suicide are legal in the Netherlands, Belgium, Luxembourg, Colombia, and Canada. Physician-assisted suicide alone is legal in Switzerland and within the U.S. in Oregon, Washington, Montana, California, and Vermont. Public support in the United States and the Netherlands for the “right to die” has steadily increased since 1950. This research seeks to uncover the underlying reasons that patients request euthanasia and physician-assisted suicide. Signs of psychological depression and loss of dignity appear to be the main reasons for considering euthanasia and physician-assisted suicide. In the United States, requests for euthanasia and physician-assisted suicide correlated most strongly with loss of autonomy, not being able to enjoy everyday life activities, and loss of dignity. In the Netherlands, more than half of euthanasia/physician-assisted suicide cases contained loss of dignity as one of the reasons. In Canada, the desire for death in the terminally ill was higher for people who had higher ratings of pain, lower family support, and depressive symptoms. Of these, depression is the best predictor of the desire to die. Palliative care that respects individual differences and psychological treatment that emphasizes the therapeutic alliance would provide people with more years of meaningful living.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".