Association between dimensions of the psychosocial and physical work environment and latent smoking trajectories: a 16-year cohort study of the Canadian workforce
Bibliographic record
Abstract
BACKGROUND: This study aimed to determine the number of latent smoking trajectories among Canadians employed in the workforce over a 16-year period, and if latent trajectories in dimensions of the physical and psychosocial work environment were associated with specific smoking trajectories. METHODS: We studied 5461 employed adults from the longitudinal Canadian National Population Health Survey. Daily cigarette consumption was measured biannually from 1994 to 2010. Work environment factors (skill discretion, decision authority, psychological demands, job insecurity, physical exertion and workplace social support) were measured in 1994 and then from 2000 to 2010 using an abbreviated form of the Job Content Questionnaire. Smoking and work environment trajectories were derived using group-based trajectory modelling. Associations between work environment trajectory classes and smoking trajectory classes were estimated using multinomial logistic regression. RESULTS: Four latent smoking trajectories were seen: non-smokers; ceasing smokers (consuming ~14 cigarettes/day in 1994 and 0 in 2008-2010); smokers (consuming ~7 cigarettes/day between 1994 and 2010); and heavy smokers (consuming ~22 cigarettes/day in 1994 and ~14 in 2010). Lower skill discretion, high psychological demands, high physical exertion and low social support trajectories were associated with membership in the heavy smoking trajectory compared with the non-smoking trajectory. Low decision authority, high psychological demands and high physical exertion trajectories were associated with membership in the ceasing compared with the non-smoking trajectory. CONCLUSIONS: Certain physical and psychosocial work environment trajectories were associated with heavy and ceasing smoking behaviours over a 16-year period. The role of the work environment should be further considered in smoking cessation programmes.
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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 | 0.000 | 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 | 0.000 |
| 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".