The Development and Validation of an Artificial Intelligence Chatbot Dependence Scale.

IF 4.2 2区心理学 Q1 PSYCHOLOGY, SOCIAL Cyberpsychology, behavior and social networking Pub Date : 2024-11-26 DOI:10.1089/cyber.2024.0240

Xing Zhang, Mingyue Yin, Mingyang Zhang, Zhaoqian Li, Hansen Li

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Abstract

In recent years, a plethora of artificial intelligence (AI) chatbots have been developed and made available to the public. Consequently, an increasing number of individuals are integrating AI chatbots into their daily lives for various purposes. This trend has also raised concerns regarding AI chatbot dependence. However, a valid and reliable scale to assess AI chatbot dependence is yet to be developed. Therefore, this study was designed to develop and validate an AI chatbot dependence scale. We obtained initial items from previous publications and in-depth interviews. Subsequently, item analysis, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), reliability, and validity analyses were performed to validate the AI chatbot dependence scale. Seventeen items underwent item analysis and EFA, resulting in a single-factor model with eight items explaining 58.42% of the total variance. The CFA indicated that our AI chatbot dependence scale had acceptable model fitting indices, with standardized loadings ranging between 0.50 and 0.76. In addition, this scale exhibited good reliability and validity. Thus, the current AI chatbot dependence scale can effectively evaluate individuals' dependence on AI chatbots in their daily lives.

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人工智能聊天机器人依赖性量表的开发与验证。

近年来，大量人工智能（AI）聊天机器人被开发出来并向公众开放。因此，越来越多的人出于各种目的将人工智能聊天机器人融入日常生活。这一趋势也引发了人们对人工智能聊天机器人依赖性的担忧。然而，评估人工智能聊天机器人依赖性的有效而可靠的量表尚未开发出来。因此，本研究旨在开发并验证人工智能聊天机器人依赖量表。我们从以前的出版物和深度访谈中获得了初始项目。随后，我们进行了项目分析、探索性因子分析（EFA）、确证性因子分析（CFA）、信度和效度分析，以验证人工智能聊天机器人依赖量表。对 17 个项目进行了项目分析和探索性因子分析，得出了一个单因素模型，其中 8 个项目解释了 58.42% 的总方差。CFA表明，我们的人工智能聊天机器人依赖量表具有可接受的模型拟合指数，标准化载荷介于0.50和0.76之间。此外，该量表还表现出良好的信度和效度。因此，本人工智能聊天机器人依赖量表可以有效评估个人在日常生活中对人工智能聊天机器人的依赖程度。

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来源期刊

Cyberpsychology, behavior and social networking PSYCHOLOGY, SOCIAL-

CiteScore

9.60

自引率

3.00%

发文量

123

期刊介绍： Cyberpsychology, Behavior, and Social Networking is a leading peer-reviewed journal that is recognized for its authoritative research on the social, behavioral, and psychological impacts of contemporary social networking practices. The journal covers a wide range of platforms, including Twitter, Facebook, internet gaming, and e-commerce, and examines how these digital environments shape human interaction and societal norms. For over two decades, this journal has been a pioneering voice in the exploration of social networking and virtual reality, establishing itself as an indispensable resource for professionals and academics in the field. It is particularly celebrated for its swift dissemination of findings through rapid communication articles, alongside comprehensive, in-depth studies that delve into the multifaceted effects of interactive technologies on both individual behavior and broader societal trends. The journal's scope encompasses the full spectrum of impacts—highlighting not only the potential benefits but also the challenges that arise as a result of these technologies. By providing a platform for rigorous research and critical discussions, it fosters a deeper understanding of the complex interplay between technology and human behavior.