Wish to Die and Physical Illness in Older Adults
Bibliographic record
Abstract
The Scientific Committee of the ESA StudyThe wish to die is the first step into the suicidal process.While depression is a major risk factor for the wish to die in old age, it seems that chronic physical illness could also be an important associated factor.Therefore, it would be interesting to look at the relations between 15 specific illnesses and the wish to die in old age.A representative probabilistic sample of community-dwelling older adults aged over 65 (M = 73.9)took part in a large survey on the prevalence of mental disorders, that also gathered information on chronic illness.Results indicated that 5.2% of the 2,811 respondents believed that they would be better dead, and that nine types of chronic illnesses were found significantly more often in elderly persons with the wish to die compared to those without.A logistic regression, including these nine diseases, revealed that, when gender was controlled for, three types of chronic illnesses were significantly associated with increased odds of wish to die: arthritis/rheumatism (OR = 1.72), respiratory problems (OR = 1.85), and urinary/prostate disorders (OR = 1.76).Although many chronic illnesses were found significantly more often in persons with a wish to die, painful diseases causing functional limitations (arthritis) and illnesses that affect basic physiological needs (breathing, eliminating) were particularly important associated factors.New research should look at the possible mediating effects of helplessness, hopelessness, perceived burdensomeness, and reduced quality of life on the relation between chronic illness and the wish to die.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".