The Quit Experience and Concerns of Smokers With Psychiatric Illness
Bibliographic record
Abstract
INTRODUCTION: The purpose of this study is to better understand the quit experience and concerns of smokers with psychiatric illness (i.e., major depressive, anxiety, psychotic and bipolar disorders) in comparison with those without psychiatric illness. METHODS: Smokers (N=732) with (n=430, 59%) and without psychiatric illness, recruited between June 2010 and March 2013 to participate in the FLEX (Flexible and Extended Dosing of Nicotine Replacement Therapy [NRT] and Varenicline in Comparison to Fixed-Dose NRT for Smoking Cessation) smoking-cessation trial, completed questionnaires assessing previously used cessation aids and reasons for relapse, and motivation and concerns about their upcoming quit attempt. These supplementary data analyses were conducted in May 2015. RESULTS: The most commonly used cessation methods during previous attempts were nicotine replacement therapy (66.4%), cold turkey (59.7%), and bupropion (34.7%); no group differences were identified. Stress was the most common precipitator of relapse during previous attempts in all groups (43.6%), particularly among participants with depression and anxiety. Health was the most common motivation for the upcoming quit attempt (91%), followed by family/social pressures (28.1%) and cost (27.9%, particularly by smokers with psychotic disorders). Common pre-cessation concerns for the complete sample included: cravings (27.6%), stress (26.7%), and fear of failure (26%); participants with psychotic and anxiety disorders were most concerned about cravings, whereas the latter two concerns were more prominent for individuals with anxiety. CONCLUSIONS: Findings reveal differences in the quit histories and concerns of smokers with or without psychiatric illness. Smokers with psychiatric illness are particularly vulnerable to relapse at times of stress and negative affect; interventions that emphasize alternative coping strategies and facilitate mood management are required.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".