Affiliation:
1. Guilin University of Electronic Technology, China
2. CSIRO's Data61, Australia
Abstract
Artificial Intelligence has found applications in a wide range of fields, including conversational agents designed for healthcare services. The quality of healthcare services greatly depends on the quality of the information provided by the agents. Achieving quality-assured information from conversational agents to support effective decision-making remains as a significant challenge in healthcare. Although prior review studies have shown an interest in investigating the information quality (IQ) of conversational agents in healthcare, no systematic review has been performed to present IQ definitions, factors influencing IQ, and IQ impacts. We conducted a systematic review of 45 articles published up to 2021 to investigate IQ definitions, factors influencing IQ, and IQ impacts in the context of conversational agents applied in healthcare. The findings of this review are integrated into a conceptual framework for the IQ research program in the context of conversational agents in healthcare, which has not been received attention in the literature, guiding future research directions. The present study also discusses implications for both researchers and practitioners to enhance the agents’ IQ and improve the quality of health-related services.
Funder
The Humanities and Social Sciences Youth Foundation, Ministry of Education of the People’s Republic of China
Subject
Library and Information Sciences
Cited by
3 articles.
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