Factors associated with crack-cocaine early initiation: a Brazilian multicenter study
Bibliographic record
Abstract
BACKGROUND: Crack-cocaine dependence is a serious public health issue, related to several psychiatric and psychosocial problems. Crack-cocaine users are usually embedded in a context of great social vulnerability, often associated with violence, poverty, family conflict and easy and early access to alcohol, tobacco and other drugs. METHODS: This cross-sectional study enrolled a consecutive sample of 577 patients admitted to 20 therapeutic communities located in Southern Brazil, between September 2012 and September 2013. A structured interview assessed life-time exposure to risk and protective factors for drug use, such as parental monitoring in childhood, deviant behaviors and peer pressure. RESULTS: Presence of family conflict (p = 0.002), maltreatment (p = 0.016), and deviant behavior prior to age 15 in a bivariate analysis predicted an earlier age of crack-cocaine initiation, whereas adolescents experiencing parental monitoring during adolescence started use later (p < 0.001). In the multivariate model, perceptions related to ease of access of illicit drugs (marijuana: p = 0.028, 95% CI = - 3.81, - 0.22; crack-cocaine: p < 0.001, 95% CI = - 7.40, - 4.90), and deviant behavior (threatening someone with a gun: p = 0.028, 95% CI = - 2.57, - 0.14) remained independent predictors of early age of crack-cocaine initiation. CONCLUSIONS: Early onset of crack-cocaine use seems to be associated with exposure to family conflict, easy access to drugs and deviant behavior. Treatment and preventive programs should take these factors into account when designing and implementing community interventions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".