Psychosocial Factors At Work, Smoking, Sedentary Behavior, and Body Mass Index:
Bibliographic record
Abstract
This cross-sectional study examined whether psychosocial factors at work were associated with smoking, sedentary behavior, and body mass index. The study population was composed of 3531 men and 3464 women employed as white collar workers in 21 organizations. Data were collected at worksites. Psychological demands and decision latitude at work were measured with the Karasek 18-item questionnaire. Smoking, sedentary behavior, and mean body mass index were compared by quartiles of decision latitude and psychological demands and by job strain categories. Prevalence of smoking, mean number of cigarettes smoked per day, prevalence of sedentary behavior, and mean body mass index were not consistently associated with decision latitude, psychological demands, or high job strain. However, prevalence of smoking was elevated in women belonging to the highest quartile of psychological demands (odds ratio [OR], 1.2; 95% confidence interval [CI], 1.0 to 1.6) and in the active job strain groups in both men (OR, 1.6; 95% CI, 1.2 to 2.1) and women (OR, 1.4; 95% CI, 1.0 to 2.0). Prevalence of sedentary behavior was elevated in men in the lowest quartile of decision latitude (OR, 1.3; 95% CI, 1.0 to 1.7), in the passive group (OR, 1.3; 95% CI, 1.0 to 1.5), and in the high strain group (OR, 1.2; 95% CI, 1.0 to 1.6). In women, this prevalence was elevated in the third quartile of psychological demand (OR, 1.3; 95% CI, 1.1 to 1.6). These results provide only partial support for an association between some psychosocial factors at work and the prevalence of smoking and sedentary behavior.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".