Information quality of conversational agents in healthcare

被引:2
|
作者
Liu, Caihua [1 ]
Zowghi, Didar [2 ]
Peng, Guochao [3 ,5 ]
Kong, Shufeng [4 ]
机构
[1] Guilin Univ Elect Technol, Sch Artificial Intelligence, Guilin, Peoples R China
[2] CSIRO, Australias Natl Sci Agcy, Data61, Canberra, Australia
[3] Sun Yat Sen Univ, Sch Informat Management, Guangzhou, Peoples R China
[4] Sun Yat Sen Univ, Software Engn, Guangzhou, Peoples R China
[5] Sun Yat Sen Univ, Guangzhou, Peoples R China
关键词
information quality; conversational agents; artificial intelligence; healthcare; systematic review; MANAGEMENT; IMPACT;
D O I
10.1177/02666669231172434
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
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.
引用
收藏
页数:23
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