Aim

Develop an AI-generated Global Surgery podcast series tailored to healthcare professionals’ needs in specific countries, focussing on Uganda as a pilot. This precision education model addresses disparities in global surgical education, historically driven by high-income countries (HICs). Podcasts were chosen for their scalability, accessibility, and self-directed learning.

Methods

Building on prior data from our international trainee-based needs assessment (145 survey respondents from 18 countries; 94 from Low-and-Middle-Income-Countries, LMICs; 51 from High-Income-Countries, HICs). Generative AI (ChatGPT 4.0, OpenAI) and prompt engineering were used to develop a global surgery curriculum from survey data from Ugandan respondents (selected because Uganda had one of the highest response rates, n=31). The resultant curriculum was then adapted into a podcast format featuring country-specific themes using NotebookLM (Google), using a format of exercises, case studies, and expert interviews.

Results

The preliminary outputs of the survey and podcasts highlight diverse country-specific priorities; for HICs these include access to resources, research opportunities, and infrastructure development; for LMICs they emphasise the burden of surgical disease, use of local case studies, and foundational concepts in global surgery.

Conclusions

By tailoring content to regional needs and leveraging storytelling to foster engagement, podcasts can complement traditional curricula to address gaps in access and relevance. Limitations include current AI-generative software offering only US accents, which may not suit learners elsewhere, reflecting concerns about HICs bias in AI-generated content. Future research will validate the podcasts through focus groups with Ugandan surgical trainees, and explore speech-processing for regional accents, or blending human voice with AI-generated transcripts.