Perceptions about the Health Effects of Passive Smoking among Bangladeshi Young Adults
Bibliographic record
Abstract
Passive smoking is now firmly established as a significant cause of morbidity and mortality. Assessment of young adults’ perceptions, understanding and knowledge of the health effects of passive smoking may promote educational endeavours to increase awareness of the passive smoking-linked health effects and to facilitate interventions. The study, therefore, assessed the perceptions of young adults in Bangladesh about the health effects of passive smoking. This cross-sectional descriptive study was conducted among 656 young adults in two districts under Dhaka division of Bangladesh. The study used a multistage cluster random sampling approach. Binary logistic regression was used for identifying the predictors of perceptions that passive smoking is harmful. The vast majority of the respondents believed that passive smoking causes illnesses but the knowledge of specific health effects was limited. Most (87.2%) respondents perceived that passive smoking causes ‘some’ or ‘a lot’ of harm to health of both adults and children. However, disparities in perceptions were prevalent across their educational levels. The results of logistic regression analysis showed that, after adjusting other factors, respondents who had nine or more years of education were 6.7 times likelihood of perceiving that passive smoking causes “some” or “lot of harm” compared to those who had no education. The findings suggested that more efforts, including some appropriate measures to address knowledge gaps, are needed to increase better perception about the harmful effects of passive smoking among young adults.
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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 | 0.003 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".