Qualitative research on sun protection can reveal why people understand environmental risks but still struggle to act on that knowledge. The audience for this kind of evidence includes public health researchers, healthcare teams, UX researchers, and policy analysts who need to turn interview data into practical interventions. A 2026 study in PLOS One examined how pilgrims and nurses understood UV exposure, sunscreen, umbrellas, and ultraviolet protection factor (UPF) products during Hajj. The study provides a useful model for AI-enabled qualitative research because it combines semi-structured interviews, multilingual transcripts, thematic analysis, participant perspectives, and implementation recommendations. This article summarizes the study’s findings and shows how AI-assisted analysis can help research teams compare segments, identify barriers, and preserve participant language without replacing methodological judgment.
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- qualitative research on sun protection
- AI qualitative research
- Hajj sun protection study
- thematic analysis of interviews
- UV protection 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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