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.本数据集包含在肯尼亚收集的去标识化定性与定量数据，该数据作为混合方法研究项目的组成部分，围绕镰状细胞病（Sickle Cell Disease, SCD）管理相关的公共卫生素养、患者与照护者体验及专家观点展开调研。本数据集支撑两篇配套学术论文：《肯尼亚镰状细胞病管理的AI驱动公共卫生素养》与《专家经验》。 数据通过焦点小组讨论（Focus Group Discussions, FGDs）、关键知情人访谈（Key Informant Interviews, KIIs）以及结构化问卷完成采集，调研对象覆盖镰状细胞病照护生态系统中的多元利益相关方，包括照护者、社区健康宣传员（Community Health Promoters, CHPs/CHVs）、卫生部（Ministry of Health, MoH）官员、健康服务提供者专员（Health Provider Officers, HPOs）、社区代表以及国家级镰状细胞病技术专家。问卷模块包含通过KoboToolbox实施的前测与后测评估。 所有转录文本均已完成专业去标识化处理，在移除个人识别信息的同时，保留了支撑研究复现与二次分析所需的语境丰富性。本数据集提供了整合视角，涵盖家庭如何理解并应对镰状细胞病、一线与社区健康工作者如何传递风险信息与照护路径，以及国家级与技术专家如何认知系统层面的障碍与机遇，以提升镰状细胞病的知晓率、早期参与度及照护连续性。 本数据集旨在推动低收入与中等收入地区在数字健康、AI增强型健康素养、社区主导监测以及卫生系统强化领域的后续研究。同时，其可作为设计行为智能型AI驱动沟通工具的证据基础，此类工具能够助力家庭、一线健康工作者及卫生部，改善镰状细胞病患者的健康结局。