Chatbot Usability Scale in Chinese Users: Cross-Cultural Adaptation and Validation Study

Read full text
Authors: Haoming Ma, Runyuan Pei, Sijia Li, Aoqi Wang, Xingyi Tang, Meihua Piao
Cited by: 1
References: 32

Abstract

Background: Chatbots are increasingly deployed across various domains; however, systematic evaluation of their usability remains limited, particularly in non-Western contexts. The 11-item Chatbot Usability Scale (BUS-11), a multidimensional instrument grounded in human-computer interaction theory, has demonstrated strong psychometric properties in prior studies; however, a validated Chinese version does not exist, despite China being one of the largest chatbot markets. Objective: This study aimed to translate, culturally adapt, and validate the BUS-11 for Chinese users. Methods: Following established cross-cultural adaptation procedures, the scale was forward- and back-translated, reviewed by an expert committee, and pilot-tested for clarity and feasibility. A main validation study was then conducted with 214 participants, who completed 438 evaluations of the chatbots across 10 widely used systems. Results: Psychometric analyses demonstrated excellent scale-level content validity index (ie, 0.92), strong internal consistency (Cronbach α=0.92), and a clear 3-factor structure (Accessibility, Interaction Process Quality, and Information Quality), explaining 56.1% of the variance. Meanwhile, privacy or security and response time were retained as single-item indicators. The Chinese BUS-11 was concise, user-friendly, and psychometrically robust. Conclusions: This work fills a critical gap by providing the first validated instrument for assessing chatbot usability in Chinese contexts, enabling reliable cross-cultural comparisons and supporting both research and practical design evaluation in human-computer interaction.

Fields of Study & Subjects

AI in Service Interactions Digital Mental Health Interventions Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
JMIR Human Factors
Publisher
JMIR Publications Inc.
Volume
13
Pages
e84971–e84971
Publication date
19 February 2026
Language
EN