Environmental factors selectively impact co‐occurrence of problem/pathological gambling with specific drug‐use disorders in male twins
Bibliographic record
Abstract
AIMS: Multiple forms of drug abuse/dependence frequently co-occur with problem/pathological gambling (PPG). The current study examines the extent to which genetic and environmental factors contribute to their co-occurrence. DESIGN: Bivariate models investigated the magnitude and correlation of genetic and environmental contributions to problem/pathological gambling and its co-occurrence with nicotine dependence, cannabis abuse/dependence and stimulant abuse/dependence. SETTING: Computer-assisted telephone interviews in the community. PARTICIPANTS: Participants were 7869 male twins in the Vietnam Era Twin Registry, a USA-based national twin registry. MEASUREMENTS: Life-time DSM-III-R diagnoses for problem/pathological gambling, nicotine dependence, cannabis abuse/dependence and stimulant abuse/dependence were determined using the Diagnostic Interview Schedule. FINDINGS: All drug-use disorders displayed additive genetic and non-shared environmental contributions, with cannabis abuse/dependence also displaying shared environmental contributions. Both genetic [genetic correlation rA = 0.22; 95% confidence interval (CI) = 0.10-0.34] and non-shared environmental components (environmental correlation rE = 0.24; 95% CI = 0.10-0.37) contributed to the co-occurrence of problem/pathological gambling and nicotine dependence. This pattern was shared by cannabis abuse/dependence (rA = 0.32; 95% CI = 0.05-1.0; rE = 0.36; 95% CI = 0.16-0.55) but not stimulant abuse/dependence (SAD), which showed only genetic contributions to the co-occurrence with problem/pathological gambling (rA = 0.58; 95% CI = 0.45-0.73). CONCLUSIONS: Strong links between gambling and stimulant-use disorders may relate to the neurochemical properties of stimulants or the illicit nature of using 'hard' drugs such as cocaine. The greater contribution of environmental factors to the co-occurrence between problem/pathological gambling and 'softer' forms of drug abuse/dependence (cannabis, tobacco) suggest that environmental interventions (perhaps relating to availability and legality) may help to diminish the relationship between problem/pathological gambling and tobacco- and cannabis-use disorders.
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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) | 0.000 | 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) | 0.002 | 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 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".