Evaluation of the effectiveness of a WHO-5A model based comprehensive tobacco control program among migrant workers in Guangdong, China: a pilot study
Bibliographic record
Abstract
BACKGROUND: As a vulnerable population in China, migrant workers have a higher smoking rate than the general population. This study aims to assess the effectiveness of a WHO-5A based comprehensive tobacco control program in workplaces aggregated with migrants. METHODS: Using a controlled before and after design, four purposely selected manufacturing factories were assigned to either intervention or control groups. Participants in the intervention arm received adapted 5A group counseling regularly supported by social-media and traditional health education approaches. The primary outcome was the change of smoking rate based on salivary cotinine concentration at three-month follow-up as compared to the control arm. Secondary outcomes were changes in smoking-related knowledge and attitudes assessed using questionnaires. Difference-in-differences approach (DID) and generalized estimating equations (GEE) models were used to conduct the effectiveness analysis. RESULTS: 149 and 166 workers were enrolled in the intervention and control arm respectively. The multiple imputed and adjusted GEE models demonstrated that, compared to those in the control arm, participants in the intervention arm had nearly 2.4 times odds of improving smoking-related knowledge (OR = 2.40, 95% CI = 1.32-4.36, P = 0.02) and three times the odds of improving smoking-related attitude (OR = 3.07, 95% CI = 1.28-7.41, P = 0.03). However, no significant difference was found regarding the change of smoking rate between the two arms (P > 0.05). The regression analysis showed that attendance at the 5A group counseling sections was an important determinant of stopping smoking or improving smoking-related knowledge and attitudes in the intervention group. CONCLUSIONS: This WHO-5A comprehensive intervention was effective in improving migrant workers' knowledge of smoking and anti-smoking attitudes. A large-scale, long-term trial is recommended to determine the effectiveness of this intervention. TRIAL REGISTRATION: ChiCTR-OPC-17011637 at Chinese Clinical Trial Registry. Retrospectively registered on 12th June 2017.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".