Actual Use Behavior Assessment of a Novel Puff Recording Electronic Nicotine Delivery System: Observation Study
Bibliographic record
Abstract
BACKGROUND: Compared with combustible cigarettes, electronic cigarettes (e-cigarettes) can deliver a sufficient amount of nicotine with a significantly reduced emission of toxicants, which renders them as potential harm reduction candidates for tobacco and smoking replacement. However, the use of e-cigarettes is not harm free and the long-term health effect of using e-cigarettes is yet to be established. Given the high prevalence of e-cigarette use across the globe and its potential health concerns, it is imperative to conduct actual use behavior assessments to better understand how e-cigarettes are being consumed in real-world conditions. However, with the currently available technologies, there is still a lack of noninvasive, noninterventional, and convenient instruments for the real-time and real-world use behavior monitoring of e-cigarette product use. Novel technology-based systems that do not primarily rely on self-report or intrusive measurements to monitor e-cigarette use behaviors are therefore highly desired. OBJECTIVE: The primary goal of this study is to investigate the e-cigarette actual use behaviors in the real world via a novel puff recording electronic nicotine delivery system (PR-ENDS). Specifically, we aim to analyze and summarize the survey and PR-ENDS use data and to study the relationships and effects of different factors on these variables. METHODS: In real-world conditions, 61 enrolled UK e-cigarette users were instructed to use PR-ENDS as the primary source of nicotine with their selected e-liquids for at least 3 weeks (21 days). A baseline survey was conducted to collect information about participants' demographics and nicotine use history (cigarette and ENDS). The puff data (ie, puff number, puff duration for each puff, device power, e-liquid nicotine concentrations) were directly recorded by PR-ENDS and uploaded to the cloud for further analyses. The nicotine emission and nicotine consumption were estimated based on recorded puff data. RESULTS: Middle-aged adults with a nicotine history represented the major user profile during the PR-ENDS trial. A wide range of device power and e-liquid nicotine concentrations was applied and their combinations during actual use were found to be rather complex. Various puff parameters (ie, puff duration, puff number, nicotine emission) were assessed with contributing factors from device, e-liquid, and user nicotine history in different effect sizes. The real-time observation revealed substantial intra- and interindividual variabilities in PR-ENDS use behaviors. The use pattern of a quick adaptation followed by consistent product use was recognized for at least 3 weeks during actual use. CONCLUSIONS: The actual use behavior assessment of PR-ENDS was conducted as a proof-of-concept application. The complex interactions of product attributes and significant intra- and interindividual variabilities in e-cigarette use behaviors provided new insights of compensatory behavior, which can inspire future studies in the field of nicotine addiction and abuse liability behavior assessment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".