Effects of reduced nicotine content cigarettes on individual withdrawal symptoms over time and during abstinence.
Bibliographic record
Abstract
In the United States, the Food and Drug Administration (FDA) has initiated a public dialogue about reducing the nicotine content of cigarettes. A reduced-nicotine standard could increase withdrawal symptoms among current smokers. We examined the impact of switching smokers to cigarettes that varied in nicotine content on withdrawal symptoms over 6 weeks. A secondary analysis (N = 839) of a 10-site, double-blind clinical trial of nontreatment-seeking smokers was completed. Participants were instructed to smoke study cigarettes, containing 0.4 to 15.8 mg of nicotine/g of tobacco, for 6 weeks and were then abstinent overnight. Using latent growth curves, trajectories of individual withdrawal symptoms were compared between the reduced nicotine content (RNC) conditions and a normal nicotine content (NNC) condition. Path analyses compared symptoms after overnight abstinence. Relative to NNC cigarettes, participants smoking RNC cigarettes had increased anger/irritability/frustration and increased appetite/weight gain during the initial weeks, but the symptoms resolved by Week 6. Individuals who were biochemically verified as adherent with using only the 0.4 mg/g cigarettes had higher sadness levels (Cohen's d = .40) at Week 6 compared with the NNC condition, although symptoms were mild. After a post-Week 6 overnight abstinence challenge, some RNC conditions relative to NNC condition exhibited reduced withdrawal. Individuals who were biochemically confirmed as adherent to the lowest nicotine condition experienced only mild and transient symptom elevations. Thus, a reduced-nicotine standard for cigarettes produced a relatively mild and temporary increase in withdrawal among nontreatment-seeking smokers (ClinicalTrials.gov No. NCT01681875). (PsycINFO Database Record
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".