History of Suicide Attempts in Adults With Asperger Syndrome
Bibliographic record
Abstract
BACKGROUND: Individuals with Asperger syndrome (AS) may be at higher risk for attempting suicide compared to the general population. AIMS: This study examines the issue of suicidality in adults with AS. METHOD: An online survey was completed by 50 adults from across Ontario. The sample was dichotomized into individuals who had attempted suicide (n = 18) and those who had not (n = 32). We examined the relationship between predictor variables and previous attempts, and compared the services that both groups are currently receiving. RESULTS: Over 35% of individuals with AS reported that they had attempted suicide in the past. Individuals who attempted suicide were more likely to have a history of depression and self-reported more severe autism symptomatology. Those with and without a suicidal history did not differ in terms of the services they were currently receiving. This study looks at predictors retrospectively and cannot ascertain how long ago the attempt was made. Although efforts were made to obtain a representative sample, there is the possibility that the individuals surveyed may be more or less distressed than the general population with AS. CONCLUSION: The suicide attempt rate in our sample is much higher than the 4.6% lifetime prevalence seen in the general population. These findings highlight a need for more specialized services to help prevent future attempts and to support this vulnerable group.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".