Health and Safety Practices and Perceptions of COVID-19 in Long-Haul Truck Drivers
Bibliographic record
Abstract
OBJECTIVE: To examine long-haul truck drivers (LHTD) perceptions of COVID-19 and their use of health and safety practices. METHODS: 146 LHTD completed an online survey to collect data on their experiences with COVID-19. Data were analyzed using descriptive and inferential statistics, and thematic analysis for open-ended responses. RESULTS: LHTD were aged from 22 to 79 years (mean age 48.1 ± 11.8); 82.2% were men. Almost half of the sample were not concerned about COVID-19. Those not concerned were significantly less likely to employ health and safety practices (eg, wearing masks, social distancing), were less educated and healthier. They also perceived COVID-19 to not be real or a serious threat to their health. CONCLUSIONS: Tailored education approaches are needed to provide evidence-based data on COVID-19 risks and complications.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".