Kenya Sickle Cell Disease Public Health Literacy & Expert Insights Dataset (De-Identified FGDs, KIIs & Surveys)

This dataset contains de-identified qualitative and quantitative data collected in Kenya as part of a mixed-methods research initiative examining public health literacy, patient and caregiver experiences, and expert perspectives on Sickle Cell Disease (SCD) management. The dataset supports two companion manuscripts: “AI-Driven Public Health Literacy for Sickle Cell Disease Management in Kenya” and “Lessons from Experts”. Data were gathered through Focus Group Discussions (FGDs), Key Informant Interviews (KIIs), and structured surveys with diverse stakeholders across the SCD care ecosystem, including caregivers, community health promoters (CHPs/CHVs), Ministry of Health (MoH) officials, health provider officers (HPOs), community representatives, and national-level SCD technical experts. Survey components include pre- and post-test assessments administered via KoboToolbox. All transcripts have been professionally de-identified to remove personal identifiers while preserving contextual richness for research, replication, and secondary analysis. The dataset provides an integrated view of how families understand and navigate SCD, how frontline and community health actors communicate risk and care pathways, and how national and technical experts conceptualize system-level barriers and opportunities for improving SCD awareness, early engagement, and continuity of care. This dataset is intended to facilitate further research on digital health, AI-enhanced health literacy, community-led monitoring, and health systems strengthening in low- and middle-income settings. It also serves as an evidence base for designing behaviorally intelligent, AI-powered communication tools that can support households, frontline workers, and ministries of health in improving outcomes for individuals living with SCD.