Parental use of sun protection for their children—does skin color matter?
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Excessive sun exposure during childhood is a risk factor for skin cancer. This study aimed to compare the frequency of ideal sun protection use between parents with lighter- and darker-skinned children and explore their attitudes and beliefs on sun safety and their choice of sun protection. METHODS: Parents of children aged 6 months to 6 years completed self-administered questionnaires about sun protection practices for their children. Parents assessed their child's Fitzpatrick phototype and were divided into lighter- (Fitzpatrick phototype I-III) and darker-skinned (Fitzpatrick phototype IV-VI) groups. Sun safety guidelines from the Canadian Dermatology Association were used to qualify ideal sun protection. RESULTS: A total of 183 parents were included. Overall, 31 parents (17%) used ideal sun protection for their children. As their children grew older, parents were less likely to use ideal sun protection (odds ratio = 0.69, 95% confidence interval = 0.53-0.90). Parents in the lighter-skinned group were more likely to use ideal sun protection for their children (odds ratio = 7.4, 95% confidence interval = 2.7-20.1), believe that sun exposure was harmful (odds ratio = 17.2, 95% confidence interval = 4.0-74.9), and perceive value in sun protection (odds ratio = 11.4, 95% confidence interval = 3.3-39.0); the darker-skinned group believed that darker skin tones provided more sun protection (odds ratio = 12.4, 95% confidence interval = 6.1-25.4). CONCLUSION: Ideal parental sun protection efforts are overall low, particularly in parents of darker-skinned children. The identified attitudes toward and beliefs about sun safety may aid in delivery of future sun protection interventions, especially in multiracial populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".