Qualitative research on sun protection can reveal why people do not consistently adopt protective behaviors, even when they understand that environmental risks exist. Public health researchers, healthcare teams, and UX researchers need to distinguish knowledge gaps from cultural, practical, and communication barriers. A November 11, 2026 study in PLOS One examined these issues among Hajj pilgrims and nurses, using post-Hajj interviews to explore awareness of ultraviolet radiation, sunscreen, umbrellas, and ultraviolet protection factor products. This article explains the study's findings and shows how AI-enabled qualitative analysis can help research teams move from interview transcripts to defensible themes more efficiently. Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and health research documents. Researchers can use Evidano to organize multilingual transcripts, compare participant groups, and identify recurring themes while keeping human interpretation and methodological review central.
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- qualitative research on sun protection
- Hajj sun protection awareness
- AI qualitative interview analysis
- thematic analysis of health interviews
- UPF awareness research
Run this analysis on your own data
Evidano codes documents, interviews, survey responses and spreadsheets with AI, with your judgment in control at every step.
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