Clinical Correlates of Sports Betting: A Systematic Review
Bibliographic record
Abstract
Sports betting is becoming increasingly widespread, and a growing number of individuals, both adolescents and adults, participate in this type of gambling. The main aim of this systematic review was to assess correlates of sports betting (sociodemographic features, gambling-related variables, co-occurring psychopathologies, and personality tendencies) through a systematic review conducted following the PRISMA guidelines. Relevant studies were identified via searches of NCBI/PubMed and APA PsycInfo databases. Individuals from the general population and/or with a clinical diagnosis of gambling disorder (GD) were included, irrespective of gender and age. In addition, the studies needed to have administered at least one clinical interview/psychometric instrument to assess the presence of problematic gambling/GD, contain at least one group of participants with sports betting, and directly analyze the association between sports betting and any of the following features: sociodemographics, gambling-related variables, co-occurring psychopathologies, and/or personality tendencies. Fifty-four articles were included. Multiple sociodemographic variables have been studied in relation to sports betting. In general, males with high impulsivity have greater tendencies for sports betting. The co-occurrence of certain pathologies, especially substance use or other addictive disorders, was also suggested. Most studies were cross-sectional, assessed participants using self-administered instruments, recruited samples using non-probability online panels, included small samples, had unbalanced samples, and included samples from only one country. Impulsive males may be particularly prone to sports gambling and related problems. Future research should examine prevention strategies that may help prevent the development of sport-betting-related GD and other addictive behaviors in vulnerable individuals.
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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 | 0.006 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".