Predictors of Intentions to Learn and Adopt Medical Artificial Intelligence Among Healthcare Professionals in Ghana: A Descriptive Cross-Sectional Study.

INTRODUCTION: Effective integration of medical artificial intelligence (AI) into healthcare delivery requires healthcare professionals to possess the necessary knowledge and skills. This study examined factors associated with healthcare professionals' behavioural intentions to learn about and adopt medical AI in Ghana. METHODS: An analytical cross-sectional study was conducted among 1131 healthcare professionals selected through systematic sampling between 15 October and 30 November 2023. Data were collected using a structured, self-administered questionnaire assessing personal relevance, social norms, self-efficacy, knowledge, behavioural intentions, and learning engagement related to medical AI. Data were entered using EpiData 3.2 and analysed in Stata 18 using descriptive statistics and structural equation modelling to identify significant predictors (p < 0.05). RESULTS: Behavioural intention significantly predicted actual knowledge acquisition in medical AI (β = 0.78, p < 0.001). Major determinants of behavioural intention included self-efficacy (β = 0.29, p < 0.001), basic knowledge (β = 0.34, p < 0.001), subjective norms (β = 0.19, p < 0.001), and personal relevance (β = 0.15, p < 0.001). Behavioural intention is fully associated with the relationships between self-efficacy and social norms on learning outcomes, while personal relevance showed a direct association with learning outcomes. Age moderated the relationship between intention and self-efficacy, and gender moderated key pathways, with the associations between behavioural intention and social norms being more positive among females than males. CONCLUSION: The adoption of medical AI among healthcare professionals is predominantly shaped by behavioural intention, self-efficacy, knowledge, and social influences. Strategic interventions that strengthen self-efficacy, underscore the professional relevance of AI, and capitalise on prevailing social norms may serve as critical enablers in advancing AI integration within Ghana's healthcare sector.