Smoking during the night: Prevalence and smoker characteristics
Bibliographic record
Abstract
We report on the smoking patterns and characteristics of individuals who smoke at night. We also explore the relationship between night smoking, nicotine dependence, and cessation outcomes. Participants (N = 691) were heavy smokers enrolled in cessation research clinics. Data were from three studies. Using ecological momentary assessment, participants monitored their smoking (ad libitum, day and night) on electronic diaries (EDs) during a 2-week baseline period and for 4 weeks following a target quit day. A total of 41% of smokers recorded at least one episode of night smoking. Within this group, night smoking occurred on 26% of nights, averaging two episodes per night. ED data correlated with a single self-report item assessing the frequency of night smoking. Night smoking was associated with greater nicotine dependence and daily caffeine consumption. It also predicted risk for lapsing beyond traditional measures of nicotine dependence. Night smoking is common, is associated with nicotine dependence, and it represents additional risk for cessation failure. People who smoke at night may need nicotine replacement therapy overnight. Future research should determine whether treatments that improve sleep quality also improve cessation outcomes in night smokers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".