Tobacco and alcohol use in the context of adolescent pregnancy and postpartum: a scoping review of the literature
Bibliographic record
Abstract
Adolescent girls are more likely than women of other ages to smoke tobacco or drink alcohol during pregnancy. The health impacts of smoking and drinking for girls and the interconnections between alcohol and tobacco use with adolescent pregnancy underscore the urgent need for integrated approaches to prevent and reduce alcohol and tobacco use among pregnant girls/young women. This article reports on the results of a scoping review of the literature focused on adolescents' use of tobacco and alcohol during pregnancy and postpartum. A search of CINAHL, Medline, Social Science Index and Web of Science identified 40 articles published in the two decades between 1990 and 2012 that met our inclusion criteria related to this age group, pregnancy/motherhood status, and use of both alcohol and tobacco. The review points to compelling gaps in our knowledge and our responsiveness to adolescents aged 19 and under who use alcohol and tobacco during pregnancy and the postpartum period. Research has been primarily descriptive, with separate, parallel streams of investigation to identify trends and predictors of alcohol and tobacco use, prior to, during and following pregnancy. There is a marked lack of effective interventions described in the literature that are designed to prevent or reduce alcohol and tobacco use during pregnancy among adolescent girls; and there are few examples of gender-informed prevention or treatment programmes for this population. Research is needed on interventions that attend to the context of adolescent girls' substance use as well as their preferences and developmental needs for support that encourage sustained behaviour change throughout pregnancy and the postpartum period and that effectively address the influence of partners and friends on use.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.014 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".