Social Influences, and Attitudes and Beliefs Associated With Smoking Among Border Latino Youth
Bibliographic record
Abstract
BACKGROUND: Adolescent smoking rates have declined among all ethnic groups since the late 1990s. However, despite the recent declines and intervention efforts, today smoking remains a serious problem among youth, with a quarter of adolescents being current smokers by the time they complete 12th grade. This problem is particularly prevalent among Latino youth, who have among the highest rates of lifetime and past-30-day use. The purpose of this study was to examine the association between psychosocial factors and the smoking behavior of Latino youth living along the Mexico-US border. METHODS: A convenient sample of 2471 middle and high school Latino students was surveyed in fall 2000. Logistic regression analysis was used to examine the association between study risk factors and youth smoking behavior. RESULTS: The strongest predictor of lifetime and past-30-day smoking was peer influence; however, the strength of the association was greater with recent use. There were also differences in the influence of family and attitudes and beliefs between the 2 groups. CONCLUSIONS: These differences need to be taken into consideration to guide development of tailored prevention and control interventions aimed at this specific group. These efforts should address social influences to smoke, particularly those from peers; promote changes in attitudes and beliefs toward smoking; increase understanding of the addictive nature of nicotine; and provide development of skills young people need to resist social and environmental pressures to smoke. Strict control and enforcement measures are needed to completely eliminate the sale of cigarettes to minors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".