Clinical and behavioral correlates in adult methamphetamine users with childhood exposure to household drug and alcohol use
Bibliographic record
Abstract
Aims: To describe and compare methamphetamine (MA) users with and without a family history of alcohol or drug () use in the household. Design: A total of 1144 Thai-speaking MA users in Thailand were recruited for a cohort study. Cross-sectional baseline data were analyzed according to their exposure to FAOD use (FAOD+/FAOD-). The Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA) was utilized to collect baseline socio-demographic information and variables known to be associated with the impact of FAOD use. Findings: FAOD+ participants had lower average years of education (p<0.01), fewer average months of employment in the past year (p<0.01) and reported higher rates of self-harm experience (p<0.001), gambling (p=0.018) and antisocial personality disorder (p=0.015). FAOD+ participants had more severe clinical, adverse consequences. FAOD+ significantly predicted episodes of lifetime MA use (R2 =0.004, p=0.032), the largest number of drinks ever had in a 24-hour period (R2 =0.01, p=0.001), paranoid experiences ([OR]=1.090, p=0.004), alcohol dependence ([OR]=1.112, p=0.001) and antisocial personality disorder ([OR]=1.139, p=0.015). FAOD+ participants who were exposed to alcohol only were more likely to report a significantly higher number of drinks ever had in a 24-hour periods (p<0.005). Similarly, FAOD+ participants who were exposed to MA use only were significantly more likely to report more frequent use of MA (p<0.005). Conclusions: FAOD+ participants were characterized by a generally more severe clinical presentation than FAOD- participants. Moreover, we show the specificity of drug type mattered, with family exposure of alcohol and MA associated with greater subsequent use of the respective drugs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".