Family Factors and Adolescent Problem Drinking in a High-Risk Urban Peruvian Neighborhood
Bibliographic record
Abstract
BACKGROUND: Family relationships are widely recognized as playing a role in adolescent alcohol use. Although family relationships and parenting vary by culture, limited research has explored these relationships in Latin America. OBJECTIVES: We sought to determine which family factors are associated with adolescent alcohol use in Callao, Peru. METHODS: Data come from a cross-sectional survey conducted in a public secondary school in Callao, Peru in 2007. A total of 180 11th grade students are included in the analysis. Our main outcome measure was problem drinking, defined as self-report of having ever consumed beer, wine, spirits, or hard alcohol to a point of drunkenness. Logistic regression was used to determine if odds of problem drinking varied by level of parental monitoring (knowledge of activities and whereabouts), positive family relationships, or family conflict, while controlling for demographic and peer variables. RESULTS: Low levels of parental monitoring and low levels of positive family relationships were each associated with significantly higher odds of lifetime problem drinking in analyses adjusted for deviant peer affiliation along with sociodemographic variables (odds ratio (OR) = 4.2; 95% confidence interval (CI): 1.3-13.5; OR = 4.4; 95% CI: 1.5-13.0, respectively). Although family conflict was associated with elevated odds of lifetime problem drinking, this did not reach significance (adjusted OR = 2.01; 95% CI: 0.8-5.1). Conclusions/Importance: Interventions designed to prevent adolescent alcohol use in urban Peru may benefit from promoting positive family interactions and parental monitoring skills.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".