The effect of smoking cessation counselling in pregnant women: a meta‐analysis of randomised controlled trials
Bibliographic record
Abstract
BACKGROUND: Pregnant smokers are often prescribed counselling as part of multicomponent cessation interventions. However, the isolated effect of counselling in this population remains unclear, and individual randomised controlled trials (RCTs) are inconclusive. OBJECTIVE: To conduct a meta-analysis of RCTs examining counselling in pregnant smokers. SEARCH STRATEGY: We searched the CDC Tobacco Information and Prevention, Cochrane Library, EMBASE, Medline and PsycINFO databases for RCTs evaluating smoking cessation counselling. SELECTION CRITERIA: We included RCTs conducted in pregnant women in which the effect of counselling could be isolated and those that reported biochemically validated abstinence at 6 or 12 months after the target quit date. DATA COLLECTION AND ANALYSIS: Overall estimates were derived using random effects meta-analysis models. MAIN RESULTS: Our search identified eight RCTs (n = 3290 women), all of which examined abstinence at 6 months. The proportion of women that remained abstinent at the end of follow up was modest, ranging from 4 to 24% among those randomised to counselling and from 2 to 21% among control women. The absolute difference in abstinence reached a maximum of only 4%. Summary estimates are inconclusive because of wide confidence intervals, albeit with little evidence to suggest that counselling is efficacious at promoting abstinence (odds ratio 1.08, 95% confidence interval 0.84-1.40). There was no evidence to suggest that efficacy differed by counselling type. CONCLUSIONS: Available data from RCTs examining the isolated effect of smoking cessation counselling in pregnant women are limited but sufficient to rule out large treatment effects. Future RCTs should examine pharmacological therapies in this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".