Monitoring Cigarette Smoking and Relapse in Young Adults With and Without Remote Biochemical Verification: Randomized Brief Cessation Study
Bibliographic record
Abstract
BACKGROUND: Technological advancements to study young adult smoking, relapse, and to deliver interventions remotely offer conceptual appeal, but the incorporation of technological enhancement must demonstrate benefit over traditional methods without adversely affecting outcomes. Further, integrating remote biochemical verification of smoking and abstinence may yield value in the confirmation of self-reported smoking, in addition to ecologically valid, real-time assessments. OBJECTIVE: The goal of this study was to evaluate the impact of remote biochemical verification on 24-hour self-reported smoking and biochemical verification agreement, retention, compliance with remote sessions, and abstinence during a brief, 5-week cessation attempt and relapse monitoring phase. METHODS: Participants (N=39; aged 18-25 years; mean age 21.6, SD 2.1 years; n=22, 56% male; n=29, 74% White) who smoked cigarettes daily engaged in a 5-week cessation and monitoring study (including a 48-hour quit attempt and provision of tobacco treatment in the form of nicotine replacement therapy, brief cessation counseling, and financial incentives for abstinence during the 2-day quit attempt only). Smoking (cigarettes per day) was self-reported through ecological momentary assessment (EMA) procedures, and participants were randomized to either (1) the inclusion of remote biochemical verification (EMA + remote carbon monoxide [rCO]) 2× per day or (2) in-person, weekly CO (wCO). Groups were compared on the following outcomes: (1) agreement in self-reported smoking and breath carbon monoxide (CO) at common study time points, (2) EMA session compliance, (3) retention in study procedures, and (4) abstinence from smoking during the 2-day quit attempt and at the end of the 5-week study. RESULTS: No significant differences were demonstrated between the rCO group and the wCO (weekly in-person study visit) group on agreement between 24-hour self-reported smoking and breath CO (moderate to poor), compliance with remote sessions, or retention, though these outcomes numerically favored the wCO group. Abstinence was numerically higher in the wCO group after the 2-day quit attempt and significantly different at the end of treatment (day 35), favoring the wCO group. CONCLUSIONS: Though study results should be interpreted with caution given the small sample size, findings suggest that the inclusion of rCO breath added to EMA compared to EMA with weekly, in-person CO collection in young adults did not yield benefit and may have even adversely affected outcomes. Our results suggest that technological advancements may improve data accuracy through objective measurement but may also introduce barriers and burdens and could result in higher rates of missing data. The inclusion of technology to inform smoking cessation research and intervention delivery among young adults should consider (1) the research question and necessity of biochemical verification and then (2) how to seamlessly incorporate monitoring into personalized and dynamic systems to avoid the added burden and detrimental effects to compliance and honesty in self-report.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".