The acute effects of physical activity on cigarette cravings: systematic review and meta‐analysis with individual participant data
Bibliographic record
Abstract
AIMS: To conduct an updated systematic review and the first meta-analysis of experimental trials investigating the acute effects of short bouts of physical activity (PA) on strength of desire (SoD) and desire to smoke (DtS) using individual participant data (IPD). METHODS: A systematic review of literature and IPD meta-analyses included trials assessing the acute effects of shorts bouts of PA on SoD and DtS among temporarily abstaining smokers not using pharmaceutical aids for smoking cessation. Authors of eligible studies were contacted and raw IPD were obtained. Two-stage and one-stage IPD random-effects meta-analyses were conducted. Participants engaging in PA were compared against control participants, using post-intervention SoD and DtS with baseline adjustments. RESULTS: A two-stage IPD meta-analysis assessing effects of PA on SoD yielded an average standardized mean difference (SMD) between PA and control conditions (across 15 primary studies) of -1.91 [95% confidence interval (CI): -2.59 to -1.22]. A two-stage IPD meta-analysis assessing effects of PA on DtS yielded an average SMD between PA and control conditions (across 17 primary studies) of -2.03 (95% CI: -2.60 to -1.46). Additional meta-analyses, including those using a one-stage model, those including only parallel arm studies and meta-analyses comparing only moderate exercise against a control condition, showed significant craving reduction following PA. Despite a high degree of between-study heterogeneity, effects sizes of all primary studies were in the same direction, with PA showing a greater reduction in cravings compared with controls. CONCLUSIONS: There is strong evidence that physical activity acutely reduces cigarette craving.
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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 | 0.037 | 0.087 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.052 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".