Effects of Unfiltered Cigarettes on Smoking Behavior and Toxicant Exposure: Protocol for a Randomized Crossover Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Plastic filters on cigarette butts are a widespread source of nonbiodegradable, toxic environmental waste. State and local legislation to ban the sale of single-use cigarettes may be considered to prevent this waste, but scientific evidence on the impact of switching smokers to unfiltered cigarettes on smoking behavior and toxicant exposures is needed to inform this policy. We have designed an open-label, randomized, 9-week, crossover clinical trial of adult filtered-cigarette smokers who switch to unfiltered cigarettes. OBJECTIVE: Our objective is to understand the impact of switching smokers of filtered cigarettes to unfiltered cigarettes on smoking behavior and toxic exposures. METHODS: This trial involves a 1-week baseline period; a 2-week period of smoking filtered or unfiltered cigarettes, where groups are randomly assigned; a 3-week washout period; another 1-week baseline period; and a 2-week crossover period of smoking the opposite condition (ie, filtered or unfiltered cigarettes) for a sufficient sample size of 40 participants. We will determine changes in (1) observed topography (ie, puff count, interpuff interval, and puff volume) and cigarettes smoked per day, via butt counts and self-report, (2) expired carbon monoxide and excretion of urinary cotinine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol, and volatile organic compounds, and (3) participants' knowledge and attitudes toward unfiltered cigarettes, satisfaction with smoking, and intention to quit if they were not able to smoke filtered cigarettes. RESULTS: This study was funded in June 2018 and approved by the relevant Institutional Review Boards in July 2018. This study has enrolled 37 participants as of October 2020. Data analysis is currently underway, and trial results are expected to be published in spring 2021. CONCLUSIONS: This pilot proof-of-principle study will inform the design of a larger, future research project that can provide robust scientific evidence on our research question. Such a large study could inform possible state or local legislation to ban the sale of single-use filtered cigarettes in order to mitigate the environmental impact of discarded single-use plastic filters. TRIAL REGISTRATION: ClinicalTrials.gov NCT03749876; https://clinicaltrials.gov/ct2/show/NCT03749876. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/19603.
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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 | 0.026 | 0.024 |
| Meta-epidemiology (narrow) | 0.008 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.052 | 0.011 |
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".