Crowdsourcing a Training Dataset of Question-and-Answer Pairs for AI-Enabled Health Information Tools on Sexually Transmitted Infections: Protocol for a Cross-Sectional Exploratory Survey Study

Comprehensive Summary

This protocol outlines an ongoing study examining the effectiveness of using AI chatbots in improving health literacy on sexually transmitted infections (STIs) in sub-Saharan Africa (SSA). The primary focus of Oseku et al. is to address the limitations of existing AI databases, which often lack contextualized and culturally relevant data, and to explore how these gaps can be addressed through the integration of community-informed perspectives. Oseku et al. are conducting a cross-sectional exploratory survey on Slido to collect data from participants in Uganda and provide evidence-based answers from health professionals. Currently, over 5620 question and answer (Q&A) pairs have been collected, as the study is still being carried out.

Outcomes and Implications

With sexually transmitted infections accounting for over 40% of the reproductive health burden in sub-Saharan Africa, this research demonstrates how AI chatbots could help close gaps in health literacy. By generating context-specific and evidence-backed information, such tools could reduce stigma, increase accessibility, and improve community-level education. The curated Q&A dataset also provides a foundation for tailoring AI systems to local populations, positioning chatbots as a potential public health tool for STI prevention and management.