Educational intervention among farmers in a community health care setting
Bibliographic record
Abstract
BACKGROUND: Farmers are at increased risk of developing work-related respiratory diseases including asthma, but little is known about their occupational health and safety (OHS) knowledge and exposure prevention practices. Educational interventions may improve knowledge and practice related to prevention. AIMS: To determine the feasibility of an educational intervention for farmers in a community health centre setting. METHODS: This was a pilot study. Farmers were recruited by the community health centre and completed a questionnaire on symptoms, OHS knowledge and exposure prevention practices. The intervention group received education on work-related asthma and exposure control strategies, and was offered spirometry and respirator fit testing. All subjects were asked to repeat the questionnaire 6 months later. RESULTS: There were 68 study participants of whom 38 formed the intervention group. At baseline, almost 60% of farmers reported having received OHS training and were familiar with material safety data sheets (MSDSs); fewer (approximately 40%) reported knowledge of OHS legislation and availability of MSDSs. Approximately, two-thirds of subjects reported using respiratory protection. The response rate for repeating the questionnaire was 76% in the intervention group and 77% in the controls. Among the intervention subjects, statistically significant increases were observed in reported safety training, familiarity and availability of MSDSs and knowledge of OHS legislation. CONCLUSIONS: Gaps in OHS knowledge were observed. The educational intervention on OHS knowledge and exposure prevention practices in the community health centre setting was feasible. Larger, more-controlled studies should be undertaken as this study suggests a positive effect on OHS knowledge and prevention practices.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".