Efficacy of smokeless tobacco for smoking cessation: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Smoking remains prevalent in many countries despite rigorous tobacco control strategies. The use of Swedish snus, a type of low-nitrosamine smokeless tobacco, has been promoted as a tobacco harm reduction strategy. DATA SOURCES AND STUDY SELECTION: Three databases were searched for studies that assessed the effectiveness of snus in promoting smoking abstinence. A total of 28 studies were reviewed (5 randomised controlled trials (RCTs), 7 longitudinal and 16 cross-sectional studies). DATA EXTRACTION: Separate meta-analyses were conducted by study type, pooling effect estimates where outcome measures and design were sufficiently comparable. Study details and quality assessment (Risk of Bias 2 for RCTs, Newcastle-Ottawa Scale for observational studies) are provided for each study. DATA SYNTHESIS: While the meta-analysis of RCTs did not show a significant association between snus use and smoking cessation (risk ratio (RR)=1.33, 95% CI 0.71 to 2.47 and RR=0.62, 95% CI 0.27 to 1.41), the results of the meta-analysis of longitudinal cohort studies (RR=1.38, 95% CI 1.05 to 1.82, p=0.022) and cross-sectional studies (OR=1.87, 95% CI 1.29 to 2.72, p=0.001) indicated that use of snus was associated with an increased likelihood of quitting or having quit smoking. There was significant heterogeneity in the cross-sectional studies, and leave-one-out analysis indicated that the longitudinal cohort results were driven by one study. Most studies examined were subject to an elevated risk of bias. CONCLUSION: There is weak evidence for the use of snus for smoking cessation. Better RCTs and longitudinal studies are needed; meanwhile, existing cessation aids may be better placed than snus to promote abstinence.
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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 | 0.017 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.046 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".