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Are conversational agents used at scale by companies offering digital health services for the management and prevention of diabetes?

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  • Singapore-ETH Center
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Abstract

Successful interventions to prevent and manage type 2 diabetes rely on long-term, day-today decisions which take place outside of clinical settings. In this context, human resources are difficult to scale up, and leveraging Conversational agents (CAs) could be one way to scale up healthcare to tackle the emerging epidemic of type 2 diabetes. The objective of this paper is to assess the degree to which CAs are employed by top-funded digital health companies that target the prevention and management of type 2 diabetes. Companies were identified via two venture capital databases, i.e. Crunchbase Pro and Pitchbook. Two independent reviewers screened results and the final list of companies was validated and revised by three independent digital health experts. The companies' digital services (usually mobile applications) were accessed and reviewed for the utilisation of CAs. To better understand the purpose of identified CAs, relevant publications were identified via PubMed, Google Scholar, ACM Digital Library and on the companies' website. Nine out of 15 companies' digital services were accessible to the authors and only in one case a CA was employed. The uptake of CAs by top-funded digital health companies targeting type-2 diabetes is still low.

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Preprint
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Artificial intelligence (AI) has transformed the world and the relationships among humans as the learning capabilities of machines have allowed for a new means of communication between humans and machines. In the field of health, there is much interest in new technologies that help to improve and automate services in hospitals. This article aims to explore the literature related to conversational agents applied to health care, searching for definitions, patterns, methods, architectures, and data types. Furthermore, this work identifies an agent application taxonomy, current challenges, and research gaps. In this work, we use a systematic literature review approach. We guide and refine this study and the research questions by applying Population, Intervention, Comparison, Outcome, and Context (PICOC) criteria. The present study investigated approximately 4145 articles involving conversational agents in health published over the last ten years. In this context, we finally selected 40 articles based on their approaches and objectives as related to our main subject. As a result, we developed a taxonomy, identified the main challenges in the field, and defined the main types of dialog and contexts related to conversational agents in health. These results contributed to discussions regarding conversational health agents, and highlighted some research gaps for future study.
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Digital medicine offers the possibility of continuous monitoring, behavior modification and personalized interventions at low cost, potentially easing the burden of chronic disease in cost-constrained healthcare systems.
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Current user interfaces for automated patient and consumer health care systems can be improved by leveraging the results of several decades of research into effective patient-provider communication skills. A research project is presented in which several such "relational" skills - including empathy, social dialogue, nonverbal immediacy behaviors, and other behaviors to build and maintain good working relationships over multiple interactions - are explicitly designed into a computer interface within the context of a longitudinal health behavior change intervention for physical activity adoption. Results of a comparison among 33 subjects interacting near-daily with the relational system and 27 interacting near-daily with an identical system with the relational behaviors ablated, each for 30 days indicate, that the use of relational behaviors by the system significantly increases working alliance and desire to continue working with the system. Comparison of the above groups to another group of 31 subjects interacting with a control system near-daily for 30 days also indicated a significant increase in proactive viewing of health information.
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