Euthanasia in Belgium: trends in reported cases between 2003 and 2013
Bibliographic record
Abstract
BACKGROUND: In 2002, the Belgian Act on Euthanasia came into effect, regulating the intentional ending of life by a physician at the patient's explicit request. We undertook this study to describe trends in officially reported euthanasia cases in Belgium with regard to patients' sociodemographic and clinical profiles, as well as decision-making and performance characteristics. METHODS: technique. We also compared and analyzed trends for cases reported in Dutch and in French. RESULTS: The number of reported euthanasia cases increased every year, from 235 (0.2% of all deaths) in 2003 to 1807 (1.7% of all deaths) in 2013. The rate of euthanasia increased significantly among those aged 80 years or older, those who died in a nursing home, those with a disease other than cancer and those not expected to die in the near future (p < 0.001 for all increases). Reported cases in 2013 most often concerned those with cancer (68.7%) and those under 80 years (65.0%). Palliative care teams were increasingly often consulted about euthanasia requests, beyond the legal requirements to do so (p < 0.001). Among cases reported in Dutch, the proportion in which the person was expected to die in the foreseeable future decreased from 93.9% in 2003 to 84.1% in 2013, and palliative care teams were increasingly consulted about the euthanasia request (from 34.0% in 2003 to 42.6% in 2013). These trends were not significant for cases reported in French. INTERPRETATION: Since legalization of euthanasia in Belgium, the number of reported cases has increased each year. Most of those receiving euthanasia were younger than 80 years and were dying of cancer. Given the increases observed among non-terminally ill and older patients, this analysis shows the importance of detailed monitoring of developments in euthanasia practice.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".