Recommendations From a Chinese-Language Survey of Knowledge and Prevention of Skin Cancer Among Chinese Populations Internationally: Cross-sectional Questionnaire Study
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».