Smoking Cessation Programs Targeted to Women: A Systematic Review
Bibliographic record
Abstract
The authors of this systematic review aimed to examine tobacco interventions developed to meet the needs of women, to identify sex- and gender-specific components, and to evaluate their effects on smoking cessation in women. The authors searched electronic databases in the Cochrane Central Register of Controlled Trials, MEDLINE, PubMed, EBSCO, PsychINFO, CINHAL, and EMBASE; the search was not restricted by publication date. Data was extracted from published peer-reviewed articles on participants, setting, treatment models, interventions, length of follow-up, and outcomes. The main outcome variable was abstinence from smoking. A total of 39 studies were identified. In efficacy studies, therapists addressed weight concerns and non-pharmacological aspects of smoking, taught mood/stress management strategies, and scheduled the quit date to be timed to the menstrual cycle. In effectiveness studies, therapists were peer counselors, provided telephone counseling, and/or distributed gendered booklets, videos, and posters. Among efficacy studies, interventions addressing weight gain/concerns showed the most promising results. If medication can support smoking cessation in women and how it interacts with non-pharmacological treatment also warrant further research. For effectiveness studies, the available evidence suggests that smoking should be addressed in low-income women accessing public health clinics. Further attention should be devoted to identifying new settings for providing smoking cessation interventions to women from disadvantaged groups. Women-specific tobacco programs help women stop smoking, although they appear to produce similar abstinence rates as non-sex/gender specific programs. Offering interventions for women specifically may reduce barriers to treatment entry and better meet individual preferences of smokers. Developing approaches that fully account for the multiple challenges treatment-seeking women face is still an area of research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".