The Interaction of Depressive Symptoms and Hazardous Drinking in Relation to Tobacco Craving Among Treatment Seeking Depressed Smokers: Sex Differences
Bibliographic record
Abstract
OBJECTIVES: The present study sought to address whether there is sex effect in the interactive effect between depressive symptoms and hazardous drinking in the prediction of smoking craving after cognitive-behavioral smoking cessation treatment among those with at least mild depression. METHODS: Participants (n = 114, mean age 42.0, SD = 9.73, 64% women) were treatment-seeking smokers who attended 6 weekly 1-hour sessions involving psychological treatment for cessation. Participants reported depressive symptoms and alcohol use at baseline and reported craving at baseline and after treatment. RESULTS: Results indicated that there was a statistically significant 3-way interaction (depression by alcohol use by sex) for smoking craving (B = -0.30, standard error [SE] = 0.14, P = 0.042) and appetitive craving (B = -.21, SE = 0.09, P = 0.031), but not negative reinforcement craving. The form of the significant interactions indicted that higher levels of depressive symptoms and alcohol use were related to greater levels of craving at the end of treatment only among men. CONCLUSIONS: The current findings provide novel empirical evidence suggesting that there is a clinically relevant interplay between depressive symptoms and alcohol use regarding general craving and appetitive craving among male treatment-seeking smokers. Although the present results should be replicated in larger samples, this type of research can inform the development of sex-specific interventions for smoking cessation.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".