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中国大学生对话式人工智能依赖量表的编制与验证

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

作者信息

Chen Yuanyuan, Wang Mengyun, Yuan Shujuan, Zhao Yan

机构信息

Department of Psychology, Shaanxi University of Technology, Hanzhong, China.

Department of Psychology, Anhui University of Chinese Medicine, Hefei, China.

出版信息

Front Psychol. 2025 Jul 31;16:1621540. doi: 10.3389/fpsyg.2025.1621540. eCollection 2025.


DOI:10.3389/fpsyg.2025.1621540
PMID:40823402
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12350385/
Abstract

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.

摘要

过度依赖对话式人工智能(CAI)会对个体的适应和发展产生重大影响。鉴于实证评估的需求不断增加,本研究介绍了CAI依赖量表(CAIDS)的编制及心理测量学验证,这是一种旨在评估中国大学生CAI依赖程度的新工具。在研究1中,借鉴网络使用问题(PIU)理论并进行定性访谈,我们确定了CAI依赖的心理内涵和维度。项目分析和探索性因素分析促成了包含20个条目的CAIDS的编制,该量表由四个维度组成:不可控性、戒断症状、情绪调节和负面影响。在研究2中,对一个新样本进行的验证性因素分析验证了四维结构,并显示出良好的信效度。在研究3中,一项现状调查显示,大学生CAI依赖的总体水平相对较高,在性别、年龄、年级、收入和地区方面存在显著差异。CAI依赖是负面心理结果的显著正向预测因子,也是主观幸福感的显著负向预测因子。戒断症状和负面影响与适应不良指标的关系更为密切。CAIDS为评估CAI依赖提供了一种可靠且有效的心理测量工具;此外,还需要在更多样化的样本和跨文化背景下进行进一步验证。

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本文引用的文献

[1]
The longitudinal association between family functioning and problematic social media use among Chinese university students: Mediation via loneliness and a subgroup analysis by sex.

Addict Behav. 2025-7

[2]
Social media addiction, escapism and coping strategies are associated with the problematic internet use of adolescents in Türkiye: a multi-center study.

Front Psychiatry. 2024-2-8

[3]
Potential cognitive risks of generative transformer-based AI chatbots on higher order executive functions.

Neuropsychology. 2024-5

[4]
Six addiction components of problematic social media use in relation to depression, anxiety, and stress symptoms: a latent profile analysis and network analysis.

BMC Psychiatry. 2023-5-8

[5]
The associations between screen time and mental health in adolescents: a systematic review.

BMC Psychol. 2023-4-20

[6]
Social Media Addiction and Poor Mental Health: Examining the Mediating Roles of Internet Addiction and Phubbing.

Psychol Rep. 2025-4

[7]
Deconstructing the components model of addiction: an illustration through "addictive" use of social media.

Addict Behav. 2023-8

[8]
Association between screen time and developmental and behavioral problems among children in the United States: evidence from 2018 to 2020 NSCH.

J Psychiatr Res. 2023-5

[9]
Advances in problematic usage of the internet research - A narrative review by experts from the European network for problematic usage of the internet.

Compr Psychiatry. 2022-10

[10]
Can internet use become addictive?

Science. 2022-5-20

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