Depressive Symptoms and Cigarette Smoking in Adolescents and Young Adults: Mediating Role of Friends Smoking
Bibliographic record
Abstract
INTRODUCTION: We examined the mediating role of friends smoking in the association between depressive symptoms and daily/weekly cigarette smoking from adolescence into adulthood. METHODS: Data were drawn from the Nicotine Dependence In Teens study (NDIT, Canada) and the Avon Longitudinal Study of Parents and Children (ALSPAC, UK) studies. Three age groups were investigated in NDIT: age 13-14 (n = 1189), 15-16 (n = 1107), and 17-18 (n = 1075), and one in ALSPAC (n = 4482, age 18-21). Multivariable mediation models decomposed the total effect (TE) of depressive symptoms on smoking into a natural direct effect (NDE) and natural indirect effect (NIE) through friends smoking. RESULTS: The odds ratios (ORs) for the TE were relatively constant over time with estimates ranging from 1.12 to 1.35. Friends smoking mediated the association between depressive symptoms and smoking in the two youngest samples (OR [95% confidence interval [CI] 1.09 [1.01,1.17] in 13- to 14-year-olds; 1.10 [1.03,1.18] in 15- to 16-year-olds). In the two older samples, NDE of depressive symptoms was close to the TE, suggestive that mediation was absent or too small to detect. CONCLUSION: Friends smoking mediates the association between depressive symptoms and daily/weekly cigarette smoking in young adolescents. IMPLICATIONS: If young adolescents use cigarettes to self-medicate depressive symptoms, then interventions targeting smoking that ignore depressive symptoms may be ineffective. Our results also underscore the importance of the influence of friends in younger adolescents, suggestive that preventive intervention should target the social environment, including social relationships.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".