Suicide and gambling: Psychopathology and treatment-seeking.
Bibliographic record
Abstract
The aim of this study was to evaluate suicides with a history of problem gambling (PG) and others with no such history (NPG) and to compare the two on mental health problems and service utilization. Data on a sample of 49 PG suicides and 73 NPG suicides were obtained from informants and hospital records. Psychopathology was prevalent in both groups, but problem gamblers were twice as likely to have a personality disorder. Moreover, PG suicides were less in contact with mental health services in their last month, their last year, and their lifetime. NPG suicides consulted specialized services from 3 (last month and last year) to 13 times (lifetime) as often as their PG counterparts. Lower service utilization associated with PG suicides argues in favor of stepping up detection, engagement in care and treatment with respect to problem gambling, especially when comorbidity is present.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".