Patterns of Use of e-Cigarettes and Their Respiratory Effects: Protocol for an Umbrella Review
Bibliographic record
Abstract
BACKGROUND: Electronic nicotine delivery systems (ENDS)-e-cigarettes or vapes-have been shown to substantially reduce or eliminate many toxins compared with cigarette smoke, but simultaneously ENDS use also produces their own unique toxins. Yet the patterns of use among people who use ENDS are not homogeneous. Some people who use ENDS also smoke cigarettes (dual use). Other people who formerly smoked cigarettes are completely substituting ENDS (exclusive use). A small number of people who have never smoked cigarettes are using ENDS (naïve use of nicotine). Each of these patterns of use results in different exposures to toxins. Unfortunately, epidemiological studies routinely group together any ENDS use regardless of other tobacco use. OBJECTIVE: This umbrella review primarily aims to present all the evidence available on the respiratory effects of ENDS use by adults based on their pattern of use: dual use, exclusive use, and naïve use. With each of these patterns of use, are there benefits, no changes, or harmful effects on respiratory functioning? Our objective is to provide clinicians with a detailed analysis of how different patterns of ENDS use impact respiratory functioning and to point to the best sources of evidence. METHODS: This umbrella review follows the Methods for Overviews of Reviews framework and the PRIOR (Preferred Reporting Items for Overviews of Reviews) statement. Systematic reviews published since 2019 will be searched across 4 databases and 3 gray literature sources. Additional searches will include citation chasing, references lists, and referrals from respiratory specialists. The quality of included reviews will be evaluated using the AMSTAR2 (A Measurement Tool to Assess Systematic Reviews) checklist. We will document biases in 3 areas: protocol deviations, biases from the Oxford Catalogue of Bias, and internal data discrepancies. Two reviewers will independently conduct the search and quality assessments. Our analysis will focus on reviews rated as moderate or high confidence by AMSTAR2. We will use the Vote Counting Direction of Effect method to manage expected data heterogeneity, assessing whether ENDS use is beneficial or detrimental, or has no effect on respiratory functions based on the pattern of use. RESULTS: The review is expected to be completed by December 2024. The database search was concluded in April 2024, and data extraction and bias assessment were completed in June 2024. The analysis phase is planned to be completed by October 2024. CONCLUSIONS: A thorough and comprehensive assessment of the evidence will better inform the contentious debate over the respiratory effects of ENDS providing much needed clarity by linking their effects to specific usage patterns. This analysis is particularly crucial in understanding the risks associated with continued cigarette smoking. TRIAL REGISTRATION: PROSPERO CRD42024540034; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=540034. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/60325.
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 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 | 0.052 | 0.067 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.011 | 0.016 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.099 | 0.017 |
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".