Development and validation of the conversational AI dependence scale for Chinese college students

Excessive dependence on Conversational artificial intelligence (CAI) can significantly impact individual adaptation and development. Given the growing need for empirical assessment, this study presents the development and psychometric validation of the CAI Dependence Scale (CAIDS), a new instrument...

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Main Authors: Yuanyuan Chen, Mengyun Wang, Shujuan Yuan, Yan Zhao
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Psychology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1621540/full
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author Yuanyuan Chen
Mengyun Wang
Shujuan Yuan
Yan Zhao
author_facet Yuanyuan Chen
Mengyun Wang
Shujuan Yuan
Yan Zhao
author_sort Yuanyuan Chen
collection DOAJ
description Excessive dependence on Conversational artificial intelligence (CAI) can significantly impact individual adaptation and development. Given the growing need for empirical assessment, this study presents the development and psychometric validation of the CAI Dependence Scale (CAIDS), a new instrument designed to assess CAI dependence among Chinese college students. In Study 1, drawing on theories of problematic internet use (PIU) and qualitative interviews, we identified the psychological connotations and dimensions of CAI dependence. Item and exploratory factor analyses led to the development of the 20-item CAIDS, comprising four dimensions: uncontrollability, withdrawal symptoms, mood modification, and negative impacts. In Study 2, confirmatory factor analysis in a new sample validated the four-dimensional structure and demonstrated good reliability and validity. In Study 3, a current status survey revealed that the overall level of CAI dependence among college students was relatively high, with significant differences observed by gender, age, grade, income, and region. CAI dependence was a significant positive predictor of negative psychological outcomes and a significant negative predictor of subjective wellbeing. Withdrawal symptoms and negative impacts were more closely related to maladaptive indicators. The CAIDS provides a reliable and valid psychometric tool for assessing CAI dependence; additionally, further validation is required with more diverse samples and in cross-cultural contexts.
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spelling doaj-art-d243ca1ae2c5425a9a7fe1b91a16ac022025-08-20T03:31:40ZengFrontiers Media S.A.Frontiers in Psychology1664-10782025-07-011610.3389/fpsyg.2025.16215401621540Development and validation of the conversational AI dependence scale for Chinese college studentsYuanyuan Chen0Mengyun Wang1Shujuan Yuan2Yan Zhao3Department of Psychology, Shaanxi University of Technology, Hanzhong, ChinaDepartment of Psychology, Anhui University of Chinese Medicine, Hefei, ChinaDepartment of Psychology, Shaanxi University of Technology, Hanzhong, ChinaDepartment of Psychology, Shaanxi University of Technology, Hanzhong, ChinaExcessive dependence on Conversational artificial intelligence (CAI) can significantly impact individual adaptation and development. Given the growing need for empirical assessment, this study presents the development and psychometric validation of the CAI Dependence Scale (CAIDS), a new instrument designed to assess CAI dependence among Chinese college students. In Study 1, drawing on theories of problematic internet use (PIU) and qualitative interviews, we identified the psychological connotations and dimensions of CAI dependence. Item and exploratory factor analyses led to the development of the 20-item CAIDS, comprising four dimensions: uncontrollability, withdrawal symptoms, mood modification, and negative impacts. In Study 2, confirmatory factor analysis in a new sample validated the four-dimensional structure and demonstrated good reliability and validity. In Study 3, a current status survey revealed that the overall level of CAI dependence among college students was relatively high, with significant differences observed by gender, age, grade, income, and region. CAI dependence was a significant positive predictor of negative psychological outcomes and a significant negative predictor of subjective wellbeing. Withdrawal symptoms and negative impacts were more closely related to maladaptive indicators. The CAIDS provides a reliable and valid psychometric tool for assessing CAI dependence; additionally, further validation is required with more diverse samples and in cross-cultural contexts.https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1621540/fullconversational artificial intelligence dependencevalidationscalepsychometricChinese college students
spellingShingle Yuanyuan Chen
Mengyun Wang
Shujuan Yuan
Yan Zhao
Development and validation of the conversational AI dependence scale for Chinese college students
Frontiers in Psychology
conversational artificial intelligence dependence
validation
scale
psychometric
Chinese college students
title Development and validation of the conversational AI dependence scale for Chinese college students
title_full Development and validation of the conversational AI dependence scale for Chinese college students
title_fullStr Development and validation of the conversational AI dependence scale for Chinese college students
title_full_unstemmed Development and validation of the conversational AI dependence scale for Chinese college students
title_short Development and validation of the conversational AI dependence scale for Chinese college students
title_sort development and validation of the conversational ai dependence scale for chinese college students
topic conversational artificial intelligence dependence
validation
scale
psychometric
Chinese college students
url https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1621540/full
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AT shujuanyuan developmentandvalidationoftheconversationalaidependencescaleforchinesecollegestudents
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