Sun Exposure and Behaviours in Saudi Arabia: A National Study of over Eleven Thousand Participants Utilising the Arabic Sun Exposure and Behaviour Inventory
Bibliographic record
Abstract
Background: Excessive sun exposure is a major modifiable risk factor for skin cancer, with ultraviolet (UV) radiation identified as a key contributor. Saudi Arabia’s high UV index and hot climate increase the risk of photo-induced skin damage among residents. Although awareness of sun protection is growing, inconsistent use of preventive measures persists, often due to misconceptions and limited knowledge. This study aimed to assess patterns of current and prior sun exposure across demographic groups in Saudi Arabia using the validated Arabic version of the Sun Exposure and Behaviour Inventory (Ar-SEBI). Methods: An analytical cross-sectional study was conducted between August 2024 and January 2025 across all five Saudi regions using non-probability quota sampling to ensure geographic representation. Sun-exposure practices and protective behaviours were measured using the Ar-SEBI. Data were collected via an online questionnaire and analysed using IBM SPSS Statistics 26. Normality was assessed via Shapiro–Wilk and Levene’s tests. Depending on the distribution, data were analysed using the Mann–Whitney U test, the Kruskal–Wallis H test, unpaired t-tests, or ANOVA. A p-value < 0.05 was considered statistically significant. Results: A total of 11,491 adults participated. Significant demographic and regional differences in sun-related behaviours were observed. Overall, 72.7% of participants were unaware of the SPF level of their sunscreen. Males and individuals under 30 years of age had significantly higher sun exposure scores than females and older adults, respectively (p < 0.001). Residents of the Southern region had the highest exposure and behaviour scores (p < 0.001), despite also reporting higher engagement in some protective measures. Additionally, sun exposure scores increased progressively with darker Fitzpatrick skin types (IV–VI) (p < 0.001), suggesting a common belief that darker skin confers adequate protection. Conclusions: This study reveals notable disparities in sun-protection practices across Saudi Arabia. Younger adults, males, and individuals with darker skin types reported greater sun exposure and indicators of lower protective awareness. These findings support the need for targeted, culturally tailored public health campaigns and policy measures to enhance sun safety and reduce long-term dermatological risks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".