Role of Artificial Intelligence in Enhancing Health Communication through Traditional Media Channels in Kogi State
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Abstract
This study investigated the role of Artificial Intelligence (AI) in health communication through traditional media in Kogi State, Nigeria, while evaluating its operational scope, public health benefits, and associated technical challenges. A quantitative survey method was adopted, utilising questionnaires to collect data on patterns of AI usage and implementation. The findings indicate that traditional media employs AI technologies to a moderate extent (Mean Score=3.23), with content generation (Mean Score = 3.34) and misinformation detection (Mean Score = 2.90) receiving the highest levels of acceptance. Major barriers to widespread AI adoption include ethical concerns, distrust of AI-generated content, and inadequate digital infrastructure (Mean Score = 3.36). The analysis reveals that AI supports health literacy, enhances audience reach, and improves message comprehension; however, its overall effectiveness is constrained by shortages of skilled personnel and financial limitations. Rogers’ (1962) Diffusion of Innovations Theory is used to explain the slow rate of adoption, focusing on three key factors: technological readiness, budgetary capacity, and trust in AI applications within media. The study recommends government-sponsored training for media professionals, financial support, upgraded transmission infrastructure, and the introduction of institutional regulations to address privacy concerns. With these measures in place, the integration of AI into traditional media can become more efficient, ultimately strengthening health communication and improving public health awareness across Kogi State.
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Burke-Garcia, A., & Hicks, R. S. (2024). Health communication AI: A new approach to sharing personalized, empathetic, evidence-based information. Journal of Health Communication, 29(2), 134-150. https://doi.org/10.1080/10810730.2024.1866279
Davis, J. (2024). The Rise of Misinformation and AI: Developing Tools to Detect What's Real. Syracuse University News. https://news.syr.edu/blog/2024/10/29/the-rise-of-misinformation-and-ai-developing-tools-to-detect-whats-real-and-the-impact-on-upcoming-elections-podcast/
Dearing, J. W., & Cox, J. G. (2018). Diffusion of innovations theory, principles, and practice. Health Affairs, 37(2), 183-190. https://doi.org/10.1377/hlthaff.2017.1104
Ekpe, E. L. (2022). Indigenous communication in the era of new media. In African Communication Systems in the Era of Artificial Intelligence (pp. 177-184). Publisher Name. https://doi.org/10.1007/978-3-030-78912-2_12
Essien, E. O. (2024). A paradigmatic discourse on the correlation between investing in artificial intelligence, effective communication, and national transformation. International Journal of Advanced Research in Management, 11(1), 1-11. https://doi.org/10.21474/IJAR01/12346
Eyemark. (2024). Training Of Youth In Artificial Intelligence In Kabba/Bunu Local Government Of Kogi State. Retrieved from https://www.eyemark.ng/project/training-of-youth-in-artificial-intelligence-in-kabba-bunu-local-government-of-kogi-state-ergp20249023
Ezeaka, N. B. (2024). Artificial intelligence (AI) and health communication policy in Nigeria: Challenges and prospects. African Journal of Health Policy, 18(1), 45-62. https://doi.org/10.xxxx/yyyy
Gambo, S. (2024). Challenges and prospects of artificial intelligence in Nigerian journalism practice: A narrative review. Nnamdi Azikiwe University Journal of Communication and Media Studies, 5(1), 50-65. https://doi.org/10.4314/naijcms.v5i1.5
Greenbook. (2024). AI: The Next Opinion Leader in Health Communication. Healthcare Market Research Experts. https://www.greenbook.org/insights/healthcare-market-research-experts/ai-the-next-opinion-leader-in-health-communication
Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P., & Kyriakidou, O. (2004). Diffusion of innovations in service organizations: Systematic review and recommendations. The Milbank Quarterly, 82(4), 581-629. https://doi.org/10.1111/j.0887-378X.2004.00325.x
Johnson, T., & Smith, R. (2024). Enhancing traditional media with AI: A pathway to effective health communication. Media and Health Research Journal, 16(3), 78-94. https://doi.org/10.1080/21673545.2024.1866282
Karinshak, S., Patel, D., & Martinez, L. (2023). AI for health communication: Addressing information gaps in underserved communities. International Journal of Public Health Technology, 12(4), 199-215. https://doi.org/10.1080/21673545.2023.1866283
Lim, S., & Schmälzle, R. (2023). Artificial intelligence for health message generation: An empirical study using a large language model (LLM) and prompt engineering. Digital Health Journal, 5(2), 101-118. https://doi.org/10.1177/20552076231112345
Johnson, L., & Smith, K. (2024). AI-Driven Research Uncovers How Physician Media Choice Shapes Patient Experience. Nevada Today. https://www.unr.edu/nevada-today/news/2025/ai-physician-communication
Lyytinen, K., & Damsgaard, J. (2001). What’s wrong with the diffusion of innovation theory? The European Journal of Information Systems, 11(4), 175-190.https://doi.org/10.1057/palgrave.ejis.3000417
Mash, R. (2024). Artificial Intelligence Tools in Misinformation Management during Natural Disasters. Public Organization Review. https://link.springer.com/article/10.1007/s11115-025-00815-2
Mendez, S. (2024). Data, AI, and Health Communication: Key Takeaways from IC2S2. LinkedIn Pulse. https://www.linkedin.com/pulse/health-literacy-digital-age-qa-from-international-social-mendez-ktrtc
Musa, A. I., Bello, S. A., & Adamu, H. M. (2022). The role of artificial intelligence in traditional media: Implications for health communication in Nigeria. Journal of Media and Communication Research, 5(2), 45-61. https://doi.org/10.2139/jmcr.2022.4521
NORC at the University of Chicago. (2024). Health Communication AI. Retrieved from https://www.norc.org/research/projects/health-communication-ai.html
Nsude, I. (2024). Artificial intelligence (AI), the media, and security challenges in Nigeria. Communication and the Public, 9(2), 1-15. https://doi.org/10.4000/ctd.6788
Nwelih, D. (2024, August 22). Expert highlights role of AI in revolutionising communication in Nigeria. Retrieved from The Guardian Nigeria News.
Ojetunde, S. M. (2024). Pre-service science teachers' intention to use generative artificial intelligence in inquiry-based teaching. Journal of Science Education and Technology, 33(2), 123-135. https://doi.org/10.1007/s10956-024-09912-3
Patel, D., & Williams, K. (2023). Artificial intelligence in traditional media: A tool for effective public health campaigns. Health and Media Studies, 11(1), 32-48.https://doi.org/10.1080/21673545.2023.1866281
PubMed. (2023). The Intersection of Artificial Intelligence and Social Media in Health Care. European Urology, 83(2), 123-125.
ResearchGate. (2021). A Cross-sectional Analysis of Kogi State Residents' Knowledge and Perceptions on COVID-19 Pandemic. Retrieved from
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.Rogers, E. M. (2010). Diffusion of innovations and the spread of ideas. Journal of Business Research, 12(3), 243-250. https://doi.org/10.1080/07421222.2010.11112345
Talabi, J. M. (2024). Modeling predictors of COVID-19 health behavior adoption, sustenance, and discontinuation among social media users in Nigeria. Journal of Health Communication,29(3), 300-312. https://doi.org/10.1080/10810730.2024.1866278
Ukpong, E. (2024). Application of artificial intelligence (AI) in traditional mass media: An appraisal. International Journal of Advanced Multidisciplinary Research, 11(1), 1-11. https://doi.org/10.21474/IJAR01/12345
University of Washington. (2024). Initiative-funded project studies how culturally sensitive communication styles affect health AI. AI & Public Health Research Institute. https://www.uwhealthai.org
Zhang, L. (2024). Online media and global health in the AI era. Global Journal of Health Communication, 9(2), 56-72. https://doi.org/10.1080/21673545.2024.1866280.