Perception of skin cancer risk and sun protective practices in individuals with vitiligo: a prospective international cross-sectional survey
Bibliographic record
Abstract
Many individuals with vitiligo are uncertain about their skin cancer risk, phototherapy risks, and recommended sun protective practices. This study examined the perceived skin cancer risk and sun protective practices among individuals living with vitiligo. A secondary objective was to understand where participants obtain this information. This was a prospective cross-sectional study. An online survey was distributed to vitiligo support group leaders globally who shared the survey with their members. Individuals over the age of 18 and with vitiligo were included. There were 209 survey respondents, the majority were between the ages 35-54 (45.5%, n = 95), female (70.8%, n = 148), White (66.0%, n = 138). Nearly half of respondents believed they were at increased risk of skin cancer because of their vitiligo (45.5%, n = 95) and nearly a quarter (22.5%, n = 47) believed that phototherapy increased their risk of skin cancer. Having vitiligo affected sun protective practices with less than a quarter (24.4%, n = 51) of respondents using sunscreen daily or often prior to their vitiligo diagnosis in comparison to the majority of respondents (60.3%, n = 126) using it after their vitiligo diagnosis. The three most common sources where patients obtained information were the internet and social media (46.4%, n = 97), vitiligo support groups (23.4%, n = 49), and dermatologists (20.6%, n = 43). Despite evidence indicating a decreased risk of skin cancer in individuals with vitiligo and supporting the safety of narrowband ultraviolet B phototherapy, many participants believed they were at an increased risk of skin cancer. Findings were sub-stratified and showed differences in sunscreen usage based on gender, skin color, and percent depigmentation. This study also found nearly half of respondents obtained information related to vitiligo from the internet and social media. The number of participants may limit the generalizability of the findings. Survey questionnaires are also subject to response bias. The findings from this study highlight demographic variations in sunscreen usage which may help guide the development of targeted interventions to improve sun protective behaviors among diverse populations with vitiligo. In addition, this study suggests certain sun protective practices and skin cancer risk perceptions may vary based on extent of depigmentation. Lastly, this study also demonstrates the internet and social media as a popular source for obtaining information, emphasizing the need for dermatologists to leverage various online communication channels to help disseminate accurate information.
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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 | 0.001 |
| 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".