Developing a Service Quality Index System for AI Health Care Chatbots: Mixed Methods Study

This study pioneers the development of a service quality index system for AI health care chatbots adapted from the SERVQUAL framework. The results provide a validated tool for evaluating the performance of chatbots and offer valuable insights for health service managers and developers to enhance AI-driven medical consultation services.

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Publication Details

Journal
Journal of Medical Internet Research
Published
2026-02-18
DOI
https://doi.org/10.2196/83051
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

Developing a Service Quality Index System for AI Health Care Chatbots: Mixed Methods Study

Yu Gu, Xinyi Wang
Journal of Medical Internet Research
Artificial Intelligence in Healthcare and Education
article

Developing a Service Quality Index System for AI Health Care Chatbots: Mixed Methods Study

Yu Gu, Xinyi Wang
article en

Abstract

This study pioneers the development of a service quality index system for AI health care chatbots adapted from the SERVQUAL framework. The results provide a validated tool for evaluating the performance of chatbots and offer valuable insights for health service managers and developers to enhance AI-driven medical consultation services.

Journal of Medical Internet ResearchVol. 28
Capital Medical University (CN)
Openalex Percentile: Top 53%
Artificial Intelligence in Healthcare and Education
DOIOpen Access PDFOpenAlex
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Developing a Service Quality Index System for AI Health Care Chatbots: Mixed Methods Study — Yu Gu, Xinyi Wang · Journal of Medical Internet Research (2026) | TGRS Research Map | TGRS