Recommendations From a Chinese-Language Survey of Knowledge and Prevention of Skin Cancer Among Chinese Populations Internationally: Cross-sectional Questionnaire Study
Bibliographic record
Abstract
BACKGROUND: There is a paucity of studies assessing awareness and prevention of skin cancer among Chinese populations. OBJECTIVE: The aim of the study is to compare attitudes and practices regarding skin cancer risks and prevention between Chinese Asian and North American Chinese populations and between Fitzpatrick scores. METHODS: A cross-sectional, internet-based, 74-question survey in Chinese was conducted focusing on Han Chinese participants internationally. The survey included Likert-type scales and multiple-choice questions. All participants were required to read Chinese and self-identify as being 18 years or older and Chinese by ethnicity, nationality, or descent. Participants were recruited on the internet over a 6-month period from July 2017 through January 2018 via advertisements in Chinese on popular social media platforms: WeChat, QQ, Weibo, Facebook, and Twitter. RESULTS: Of the 113 completed responses collected (participation rate of 65.7%), 95 (84.1%) were ethnically Han Chinese, of which 93 (96.9%) were born in China and 59 (62.1%) were female. The mean age of these 95 participants was 35.8 (SD 13.3) years; 72 (75.8%) participants were born after 1975. Few but more North American Chinese reported that Chinese Asian populations received annual skin checks (4/30, 4.2% vs 0/65, 0%; P=.009) and believed that their clinician provided adequate sun safety education (13/30, 43.3% vs 15/65, 23.1%; P=.04). Participants with higher Fitzpatrick scores less frequently received sun safety education from a clinician (4/34, 11.8% vs 22/61, 36.1%; P=.02). More participants with lower Fitzpatrick scores used sunscreen (41/61, 67.2% vs 16/34, 47.1%; P=.05), but alternative sun protection use rates are similar across groups. CONCLUSIONS: Cultural differences and Fitzpatrick scores can affect knowledge and practices with respect to sun protection and skin cancer among social media-using Chinese Asian and North American Chinese communities based on respondent demographics. Most participants in all groups understood that people of color have some risk of skin cancer, but >30% of all groups across regions and Fitzpatrick scores are unaware of current skin protection recommendations, receive insufficient sun safety education, and do not use sunscreen. Outreach efforts may begin broadly with concerted public and private efforts to train and fund dermatologists to perform annual total body skin exams and provide more patient education. They should spark community interest through mass media and empower Chinese people to perform self-examinations and recognize risks and risk mitigation methods.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".