Public Awareness of Artificial Intelligence (AI) Utilisation in Healthcare Institutions in Anambra State
Given the growing adoption of AI-driven diagnostic and treatment tools across health systems, understanding community awareness is crucial for effective integration and health communication. Applying the survey design, data were collected from 384 adult residents selected from across six Local Government Areas of Anambra State, Nigeria, using multistage and proportionate sampling techniques. Findings revealed a moderately high level of awareness of AI utilisation, with respondents expressing the strongest familiarity with AI-powered tools such as automated diagnostics and virtual assistants. Social media emerged as the dominant source of AI information, followed by traditional media, while healthcare providers contributed minimally to public knowledge. Respondents also recognised significant benefits of AI, including improved diagnostic accuracy, enhanced service delivery, and overall healthcare quality. However, concerns were evident regarding potential medical errors, privacy concerns, and job displacement of healthcare workers. These findings align with national and international studies showing high exposure but limited depth of understanding among the public and health workers. Guided by the Diffusion of Innovations and Agenda-Setting theories, the study concludes that public awareness is largely media-driven and remains at an early diffusion stage, underscoring the need for deliberate institutional communication, ethical safeguards, and structured public sensitisation. The study recommends strengthening health communication strategies, promoting data protection frameworks, and enhancing healthcare worker involvement in public AI education.
Authors
- C. Ashong, Ashong, Ph.D
Institutions
- University of Uyo (NG)
Publication Details
- Journal
- RESEARCH JOURNAL OF MASS COMMUNICATION AND INFORMATION TECHNOLOGY
- Published
- 2026-11-02
- DOI
- https://doi.org/10.56201/rjmcit.vol.11.no9.2025.pg40.54
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00