Exploring user acceptance of medical e-appointment systems for mental healthcare: A systematic literature review

Clinical Neurosciences and Mental Health Laboratory, Faculty of Medicine and Pharmacy, Hassan II University, Casablanca, Morocco

Abstract

Currently, various digital platforms are available to facilitate medical appointment-making; their use supports a value proposition to optimize patient-physician transactions and reduce the workload associated with traditional medical appointment-making. Studies on online medical appointment systems focus on their effectiveness, their contribution to improving healthcare services, the causes and effects of missed appointments, and user satisfaction with these systems. Unfortunately, there is very little earlier research that addresses the user acceptance of medical e-appointment systems. Hence, this study aims to synthesize research that has assessed the acceptance and use of MEAS in a mental healthcare setting. The literature search was conducted using four databases: Web of Science, Science Direct, PubMed, and Google Scholar. Of the 805 studies collected, 11 empirical studies with a focus on applying theories and models of technology acceptance and use with publication dates ranging from 2012 to 2023 were analyzed in depth. The main results confirmed that no studies have been conducted to assess the acceptance of medical e-appointment scheduling systems for mental healthcare in a Moroccan context. There is a lack of research analyzing the acceptance mechanism from a healthcare provider’s perspective. The technology acceptance model (TAM) and its extensions and the continuance intention of use model are the most common models to explain what sustains the adoption of these systems. The results allowed us to also identify 35 determinants of the adoption of these tools: the quality of the relationship quality with the healthcare service, the quality of the system, effective communication about these systems, perceived usefulness, ease of use, satisfaction, and trust were the most influential factors in the adoption of MEAS.