Association between e-cigarette use, physical activity and cardiorespiratory fitness: protocol for a systematic review
Bibliographic record
Abstract
Introduction Despite the rise in popularity of e-cigarette smoking or ‘vaping’, its long-term health consequences are still being investigated. In particular, it is unclear what impact e-cigarette use has on aerobic performance and exercise capacity. This information has important implications both for tobacco smokers as a harm reduction approach, and youth and young adults who are increasingly turning to e-cigarettes recreationally. Thus, this review aims to systematically evaluate the literature surrounding the effects of regular e-cigarette use on markers of cardiorespiratory fitness and physical activity. Methods and analysis This protocol follows the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guidelines. A systematic search was undertaken in October 2024, using the defined population, intervention, comparison, outcomes, study time framework to identify all relevant articles. Studies will be eligible if they include individuals who use e-cigarette products, assess regular e-cigarette use as an exposure, compare to a group of non-users and report outcomes related to measures of cardiorespiratory fitness (eg, VO2max, 6 min walk test) or physical activity (eg, sport participation, meeting weekly physical activity guidelines), regardless of study duration. Searched databases will include PubMed/Medline, Cochrane Library and Embase, with no restriction to date or language of publication. Two reviewers will carry out the title and abstract screening, full text review and data extraction. Risk of bias will be assessed using the Newcastle-Ottawa Scale for non-randomised studies and the Cochrane Risk of Bias Tool (v2) for randomised studies. Study heterogeneity will be assessed using the Q and I 2 statistic tests. Efforts will be made to conduct a meta-analysis if sufficient data and homogeneity are present. Otherwise, a narrative synthesis will be conducted, focusing on common themes, subgroups and sources of variability. Ethics and dissemination Ethics approval is not required for this review of previously published or presented data. The results of the review will be disseminated via conference presentations and peer-reviewed publication. Moreover, results of this review may inform public health recommendations and identify areas in the field where further research is needed. PROSPERO registration number CRD420250589685.
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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 | 0.064 | 0.086 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.023 | 0.020 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.072 | 0.009 |
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".