Patterns of Sun Protection Behaviours among Australian Adolescents and Adults over a Six-Year Period
Bibliographic record
Abstract
The major cause for skin cancer is the excessive and unprotected exposure to ultraviolet radiation (UVR), which can be prevented by engaging in sun protection behaviours. As longitudinal studies on both adolescents' and adults' performances of sun protection behaviours are limited, the current study aimed to investigate changes in sun protection in these population segments in Western Australia, a region with high annual UVR. During six summer seasons (2015/16 to 2020/21), cross-sectional surveys were conducted among 1806 adolescents (14 to 17 years old) and 1808 adults (18-45 years old), investigating the frequency of five sun protection behaviours (wearing clothing, applying sunscreen, wearing a hat, wearing sunglasses, and seeking shade) and sun avoidance (staying indoors). Over the six-year period, staying indoors increased in both groups. Among adolescents, a decrease in wearing clothing and sunglasses and an increase in seeking shade was demonstrated, and hat and sunscreen use remained relatively stable. Among adults, an increase in sunscreen use was shown, whereas all other sun-related behaviours remained consistent over the six-year period. The results from this study can provide directions for health communications focusing on improving sun protection behaviours among both adolescent and adult populations.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".