Generative artificial intelligence in public health research and scientific communication: A narrative review of real applications and future directions

Abstract

Introduction: Generative artificial intelligence (GenAI) tools such as ChatGPT-4o and Gemini are rapidly influencing public health research and communication. Their capacity to assist with drafting, summarising, and translating content offers significant potential, particularly in multilingual and resource-limited settings.This narrative review critically explored the adoption of GenAI tools in public health research and communication, focusing on their practical applications and ethical implications. Methods: This narrative review synthesised 18 recent peer-reviewed and grey literature (2023-2025) to explore the role of GenAI in public health research and communication. A hybrid human-AI approach was used, where colour-coded manual coding was combined with AI-supported thematic analysis. All AI-generated outputs were critically reviewed, verified, and refined by the author. Results: Five key themes were identified: (1) Supporting scientific research writing tasks; (2) enhancing language clarity and scientific tone; (3) bridging the gap between science and the public; (4) ethical concerns and quality assurance; and (5) future potential and the need for upskilling. Discussion: GenAI can democratise and accelerate public health research publication and communication, provided it is used transparently and critically. Human oversight and contextual judgement remain essential to ensure responsible use. Conclusion: With thoughtful implementation, GenAI can enhance human expertise in the realm of public health, academia and scientific communication. It offers an emerging opportunity to strengthen public health research and communication, particularly when supported by ethical guidelines, training, and institutional leadership.

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