Exploring equity in global health collaborations: a qualitative study of donor and recipient power dynamics in Liberia.

IntroductionGlobal health collaborations between individuals from high-resource and low-resource settings are complex and often built on hierarchical structures and power differentials that are difficult to change. There have been many calls and frameworks developed to facilitate more equity within these collaborations, yet little is known about the lived experiences of global health donors and recipients working within such collaborations and how those experiences can facilitate more equitable collaboration. Liberia, a postconflict, post-Ebola country, provides an ideal setting to study lived experiences of global health collaborations.MethodsOur qualitative analysis used key informant interviews representing the perspectives of those working on behalf of the Liberian government, Liberian academics, foreign donors and non-governmental organisations and implementing partners. Thematic analysis guided this analysis to explore topics such as financial control, accountability and decision making.ResultsThe first phase of the analysis mapped the existing patterns of priority setting. Priority-setting power was most strongly held by those with financial control (donors), and implementation plans tended to be built on metrics that aim to meet donor expectations. The second phase of the analysis explored the interplay between underlying factors that we identified in our data associated with driving collaborative inequity: history of prior of engagement, level of transparency and patterns of accountability.ConclusionsOur findings highlight that global health collaborations in Liberia are structured to hinder equitable partnerships. The power structure tied to financial ownership offers little space for recipients to have an equitable role in collaborations, which maintains dependence on external aid and ensures that weak systems remain weak. While our study is limited to Liberia, we anticipate that these dynamics are common elsewhere and reinforce the importance of intentional efforts to ensure equitable decision making and power structures in similar settings worldwide.

Leveraging Generative AI Tools to Support the Development of Digital Solutions in Health Care Research: Case Study.

BACKGROUND: Generative artificial intelligence has the potential to revolutionize health technology product development by improving coding quality, efficiency, documentation, quality assessment and review, and troubleshooting. OBJECTIVE: This paper explores the application of a commercially available generative artificial intelligence tool (ChatGPT) to the development of a digital health behavior change intervention designed to support patient engagement in a commercial digital diabetes prevention program. METHODS: We examined the capacity, advantages, and limitations of ChatGPT to support digital product idea conceptualization, intervention content development, and the software engineering process, including software requirement generation, software design, and code production. In total, 11 evaluators, each with at least 10 years of experience in fields of study ranging from medicine and implementation science to computer science, participated in the output review process (ChatGPT vs human-generated output). All had familiarity or prior exposure to the original personalized automatic messaging system intervention. The evaluators rated the ChatGPT-produced outputs in terms of understandability, usability, novelty, relevance, completeness, and efficiency. RESULTS: Most metrics received positive scores. We identified that ChatGPT can (1) support developers to achieve high-quality products faster and (2) facilitate nontechnical communication and system understanding between technical and nontechnical team members around the development goal of rapid and easy-to-build computational solutions for medical technologies. CONCLUSIONS: ChatGPT can serve as a usable facilitator for researchers engaging in the software development life cycle, from product conceptualization to feature identification and user story development to code generation. TRIAL REGISTRATION: ClinicalTrials.gov NCT04049500; https://clinicaltrials.gov/ct2/show/NCT04049500.