Accepted for/Published in: JMIR Research Protocols
Date Submitted: Jul 3, 2024
Date Accepted: Dec 24, 2024
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Healthcare Social Robots in the Age of Generative AI: Protocol for a Scoping Review
ABSTRACT
Background:
Social Robots (SR), sensorimotor machines designed to interact with humans, can help to respond to the increasing demands in the health care sector (HCS). To ensure a successful use of this technology, acceptance is paramount. Generative Artificial Intelligence (Generative AI) is an emerging technology with the potential to enhance the functionality of SR and promote user acceptance by further improving Human-Robot Interaction.
Objective:
We present a protocol for a Scoping Review of literature on the implementation of Generative AI in SR in the HCS. The aim of this Scoping Review is to map out the intersection of SR and Generative AI in the HCS; to explore if Generative AI is applied in SR in the HCS; to outline which models of Generative AI and SR are used for these implementations; and to explore whether user acceptance is reported as an outcome following these implementations. This Scoping Review supports future research by providing an overview of the state of connectedness of two emerging technologies, SR and Generative AI, and by mapping out potential research gaps
Methods:
For this review, we follow the methodological framework developed by Arksey and O'Malley and the recommendations by the Joanna Briggs Institute. Our protocol was drafted using the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews (PRISMA-ScR). We will conduct a systematic literature search of the online databases Medline, Embase, CINAHL, Web of Science, and IEEE Xplore, aiming to retrieve relevant data items via tabular data charting from references meeting specific inclusion criteria. Results will be collated, categorized, summarized by clustering similar publications by classifying the collected data items. The findings will be presented through a series of adequate tables, graphs, visual representations, and corresponding narrative summaries.
Results:
After conducting a preliminary search and de-duplication, we retrieved 3176 preliminary results. This Scoping Review will be supplemented with the next methodological steps, including retrieving the results in a reference management tool as well as screening titles, abstracts, and full text regarding specific inclusion criteria.
Conclusions:
The conducted preliminary search implies that there is a sufficient number of heterogenous references to complete this Scoping Review. To our knowledge, this is the first Scoping Review on the implementation of Generative AI in Healthcare SR.
Citation
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