Decision making and vulnerability to suicidal behaviour in elderly
Bibliographic record
Abstract
Suicide is a major public health concern, especially for older adults, who have higher rates of completed suicide than any other age group in most countries of the world. However, understanding suicidal behaviour remains a challenging task particularly among the elders who have been poorly studied. Decision making has been recently found to be altered in suicide attempters under 65.To test wether decision making would be a neuropsychological trait of vulnerability to suicidal behaviours, the authors used the Iowa Gambling Task to investigate normothymic non demented elders with a history of suicidal behaviour (N = 35) and compared it to decision making in non suicide attempters with a past history of depression (N = 52) and comparison subjects (N = 43). The data also were compared to those of similar groups of younger normothymic subjects. Moreover, the old suicidal patients were assessed according to the age at the onset of suicidal behaviour (before or after 60).Old suicide attempters did not significantly differ from the other aged groups and according to the age of first suicidal behaviour. Old suicide attempters presented better performances than that of younger suicidal patients.Vulnerability to suicidal behaviour in older people may proceed from cognitive processes which are different from the ones involved in suicidal vulnerability of younger subjects. These results are preliminary and further studies are needed to explore vulnerability cognitive patterns to suicide among elders.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".