JMIR Publications

ABSTRACT

Background:

Sexually transmitted infections (STIs) are a significant public health concern, particularly in Sub-Saharan Africa, where their prevalence remains high. Promoting awareness and reducing stigma are essential strategies for addressing this challenge, but those affected often have limited access to accurate and culturally appropriate health information. Innovative solutions are therefore essential to enhance sexual health literacy and encourage informed health-seeking behaviors. AI-enabled tools like chatbots have emerged as promising avenues for delivering accurate and accessible health information. However, their potential is constrained by the lack of contextualized datasets, which are crucial for ensuring their effectiveness and relevance to diverse populations.

Objective:

This study therefore aims to develop an open-access, contextualized dataset of question-and-answer pairs on sexual health and STIs to support development and training of digital and AI-enabled health information tools.

Methods:

Using a crowdsourcing approach, questions are being collected from participants aged 15 years and older via online platforms, paper-based submissions, and in-person interactions at public events across Sub-Saharan Africa. Each question will be anonymized and reviewed by medical professionals, who will provide accurate, evidence-based answers. The dataset will then undergo processing, including cleaning and tagging for AI training, ensuring adherence to FAIR principles. The final dataset will be published as open access.

Results:

Data collection began on 12th June 2024 and is ongoing. The data collection process was piloted in Kigali. Data is undergoing cleaning and processing to enhance its utility for AI applications. The final dataset will be published as open access in 2025, contributing

Conclusions:

This study represents a significant step toward developing accessible evidence-based health information tools, with the potential to increase literacy levels on STIs and improve health-seeking behaviours. The Q&A dataset from this study will enable the development of AI tools to address critical gaps in sexual health education thus fostering informed decision-making.