Gambling-Related completed suicides: a scoping review
Bibliographic record
Abstract
Gambling disorder is a behavioral addiction with various consequences for those who suffer from it, such as lower quality of life, financial difficulties, psychiatric comorbidities, and increased suicide risk. The objective of this scoping review is to describe the available literature regarding gambling activities and completed suicides and underline future avenues of research on this important subject. We conducted an electronic literature search at the end of July 2021 in the following databases: Academic search complete, CINAHL +, APA Psyc Articles, APA Psyc Extra, Psychology and Behavioral Sciences Collection, Psyc Info, SOC Index, and SCOPUS. The search yielded a total of 1108 articles, of which 613 remained after the removal of duplicates. Upon title and abstract review, 51 articles remained. After full-text reading, a total of 18 articles were included in this review. To be selected, articles had to meet the following criteria: be published in a peer-reviewed journal, be available in English or French, and discuss gambling-related suicides as the main subject. The available literature shows distinct risk factors among suicide decedents with a history of problem gambling and that this population presents an elevated suicide risk. Recognizing and understanding the increased suicide risk in patients with gambling disorder will allow primary care professionals to provide better-adapted care to this population. To better comprehend this phenomenon further studies are required, with larger samples, qualitative or mixed-method designs, and a focus on diverse populations.
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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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".