O-277 Solar UVR exposure among outdoor workers in Alberta: Measurements and protective behaviours
Bibliographic record
Abstract
Introduction Workplace solar UVR exposure has significant health and economic impacts. However, occupational exposure and sun protection behaviour data are scarcely available. Objectives This study aimed to characterize outdoor workers’ full-day solar UVR exposures and their determinants, as well as the prevalence and determinants of sun protection behaviours used at work and leisure. Methods We collected personal dosimetry measurements over one week using calibrated, electronic UVR dosimeters, and outdoor workers’ demographics, skin cancer risk factors, job information, and sun habits at work and leisure using self-completed questionnaires. Workers’ mean daily solar UVR exposure (standard erythemal dose, SED), corrected for repeated measurements, was summarized, and determinants of exposure were assessed using marginal models. The frequency of specific protective behaviours at leisure and work was compared. Sun protection scores were calculated, and the determinants of these scores for both settings were modelled using multiple linear regression. Results We recruited 179 workers and collected 883 full-day measurements. The mean dose among all workers was 1.9 SED (range: 0.03–16.6). Nearly half of all measurements exceeded the recommended international limit (1.3 SED). Landscape and maintenance workers (2.6 SED), and trade and recreation workers (1.8 SED) had the highest mean exposures. Job title, dosimeter placement, forecast, and hours spent outside were predictors of daily SED. At work, wearing a sleeved shirt (81% often/always) and hat (73%) were most prevalent, while seeking shade (12%) and applying sunscreen (36%) were least prevalent. Sun protection scores were higher at work than leisure. Hours spent outdoors was a strong determinant for the work and leisure models. Additional leisure model predictors were eye colour, sex, skin type, and job group. Conclusion Outdoor workers are exposed to high solar UVR levels and use different sun protective behaviours at work and leisure. These findings can inform future monitoring studies and exposure reduction initiatives.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".