Scoping review protocol: personalising verbal communication in socially assistive technologies (SATs) to better meet the needs and preferences of older adults

Introduction Socially Assistive Technologies (SATs) have gained attention for their potential to enhance social health and improve the quality of life for individuals, particularly in healthcare for older adults. These technologies, which include robots, virtual avatars, and AI-based systems, are designed to offer social, emotional, and cognitive support, aiming to address the growing social and emotional needs of vulnerable populations. Despite their potential benefits, the adoption rates of SATs in healthcare remain low, primarily due to barriers related to workload, costs, stigma, and user acceptance. The objective of this scoping review is to identify personalization strategies and assess their impact on the user experience and technology acceptance in healthcare settings. Methods and Analysis A scoping review methodology will be conducted, focusing on studies related to the personalization of verbal communication in SATs for older adults, with an emphasis on Human-Computer Interaction (HCI) and Human-Robot Interaction (HRI). A comprehensive search will be conducted using the databases ACM, Scopus, Web of Science, Medline, Embase, APA PsycINFO and Google Scholar. Only full-length research articles will be included. Studies that consider personalization techniques for verbal communication in SATs, and those that evaluate the effectiveness of these techniques, will be selected. Data extraction will include information on the publication year, country of origin, type of interaction (HRI or HCI), sample size, and personalization strategies. The data will be reviewed to identify key strategies for personalizing verbal communication in SATs, and, if applicable, to explore their potential impact on user acceptance. The review process will involve independent screening and extraction of relevant datapoints with support from AI-based software. Ethics and Dissemination As this study involves the review of existing literature, ethical approval is not required. The findings of this review will be disseminated through academic journals, conferences, and relevant healthcare and technology forums. The review aims to contribute to the development of more effective, personalized SATs that can enhance user acceptance and improve healthcare outcomes for older adults. Key Words Human-Robot Interaction, Socially Assistive Technologies, Personalisation, Communication, Verbal Interaction