Use of Sun-Protective Clothing at Outdoor Leisure Settings from 1992 to 2002: Serial Cross-sectional Observation Survey
Bibliographic record
Abstract
BACKGROUND: Previous population-based surveys to monitor sun protection behavior over time have relied on self-report, which can be subject to recall and misclassification bias and social desirability bias. The present study aimed to describe the prevalence and determinants of teenagers' and adults' observed sun protection behavior while engaged in outdoor leisure activities on summer weekends, over a decade of the SunSmart skin cancer prevention program, which involved public education and advocacy. METHOD: Serial cross-sectional observational field surveys of teenagers and adults at leisure were undertaken during summer weekends between 11 a.m. and 3 p.m., from 1992 to 2002 (N = 46,810). The four types of setting for observation were parks and gardens, golf courses, tennis courts, and pools and beaches, located within a 25-km radius of Melbourne city center, Australia. The main outcome measure was a binary clothes cover index representing persons above or below the median level of body cover for each type of leisure setting. The index was based on the proportion of body surface covered by the type of hat, shirt, and leg cover garments worn. RESULTS: Body cover varied by environmental factors and the activity demands and demographic characteristics of individuals. After adjusting for covariates, significant improvements in the extent of body cover occurred over the decade, such that the odds of the proportion of people wearing clothes cover above the median level increased by 3% per year (95% confidence interval, 2-4%). CONCLUSION: Results suggest that significant gains in sun-protective behavior have occurred, coincident with the conduct of an ongoing comprehensive skin cancer prevention program.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".