Designing a Culturally Relevant Digital Skin Cancer Prevention Intervention for Hispanic Individuals: Qualitative Exploration
Notice bibliographique
Résumé
BACKGROUND: In the past 2 decades, melanoma incidence among Hispanic individuals has risen by 20%. The mortality rate of Hispanic individuals is higher than that for non-Hispanic White individuals. Skin cancer can largely be prevented with regular sun protection, and skin cancer outcomes can be improved through early detection, for example, by skin self-examination. Alarmingly, Hispanic individuals are less aware of the symptoms and harms of skin cancers, tend to have misperceptions regarding the risks and benefits of skin cancer prevention behaviors, and engage in less sun protection behaviors than non-Hispanic White individuals. OBJECTIVE: This study aimed to use a community-engaged approach and conduct both group and individual interviews among Hispanic individuals and relevant key stakeholders to explore the potential design of a mobile-based skin cancer prevention intervention for Hispanic individuals. METHODS: This study used a qualitative design (focus groups and individual interviews). Participants were recruited from local community organizations' social media, local events, and contact lists (eg, email). Zoom interviews were conducted to examine whether Hispanic individuals would be interested in a mobile-based skin cancer intervention and to explore their preferences and suggestions to inform skin cancer prevention intervention design. RESULTS: Five focus groups (2 in Spanish and 3 in English) among self-identified Hispanic individuals (n=34) and 15 semistructured, in-depth individual interviews among key stakeholders (health care providers and community leaders; eg, dermatologist, nurse practitioner, licensed social worker, and church leader) were conducted. The main themes and subthemes emerging from the group discussions and individual interviews were organized into the following categories: intervention platform, delivery frequency and format, message design, engagement plan, and activities. WhatsApp and Facebook were identified as suitable platforms for the intervention. Messages including short videos, visuals (eg, images and photographs), and simple texts messages were preferred. Recommendations for message design included personalized messages, personal stories and narratives, culturally relevant design (eg, incorporating family values), and community-trusted sources. Potential engagement and retention recommendations were also discussed. Additional details and exemplar quotes of each theme and subtheme are described. CONCLUSIONS: This study provides important insights and directions for the design of a mobile, digital skin cancer intervention to modify Hispanic individuals' sun protection and skin self-examination behaviors to help improve skin cancer outcomes. Insights gathered from community leaders and health care providers provided valuable additions to the community-derived data. Leveraging popular digital platforms among Hispanic individuals such as WhatsApp or Facebook could be a promising approach to skin cancer prevention. Recommendations from the community included the use of concise videos, illustrative images, clear text messages, tailored communications, narratives featuring personal experiences, designs that reflect cultural significance, and information from sources that are trusted by the community, which provided useful strategies for future intervention design among Hispanic individuals.
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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 | 0,002 | 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 | 0,002 |
| 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 ».