Differences between intermittent and light daily smokers in a population of U.S. military recruits
Bibliographic record
Abstract
INTRODUCTION: Few studies have assessed differences between intermittent and light smokers, particularly among young adults. Exploring these differences promotes a systematic approach to research and treatment in low-level smokers. This study explored demographic, tobacco-related, and psychosocial predictors of intermittent nondaily smoking relative to light smoking among basic military training (BMT) recruits. The impact of smoking status on abstinence rates at follow-up was also assessed. METHODS: Participants were 5,603 U.S. Air Force BMT intermittent nondaily (n = 3,134) or light daily (n = 2,469) smoking recruits participating in a population-based group randomized trial targeting tobacco use prevention and cessation (Klesges et al., 2006, Efficacy of a tailored tobacco control program on long-term use in a population of U.S. military troops. Journal of Consulting and Clinical Psychology, 74, 295-306.). Participants completed baseline measures assessing demographics; tobacco use and history; and common social, attitudinal, and behavioral risk factors for tobacco use. Flights of recruits were randomly assigned to a tobacco use intervention or health education control intervention. At the 1-year follow-up, participants reported 7-day point prevalence and continuous abstinence. RESULTS: Intermittent nondaily smoking relative to light daily smoking was associated with lesser perceived addiction, intermittent and daily use of smokeless tobacco, nonsmoking male and female heads of household, lesser likelihood of smoking while stressed or while bored, and higher likelihood of intentions to quit smoking. Intermittent smokers were significantly more likely than light daily smokers to report abstinence at follow-up. DISCUSSION: Intermittent and daily light smokers differ on several tobacco-related and psychosocial variables. Attending to these factors in prevention and cessation programs may enhance abstinence in both groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".