The Development and Validation of an Artificial Intelligence Chatbot Dependence Scale
Xing Zhang, Mingyue Yin, Mingyang Zhang, Zhaoqian Li, H. Li
Universidad de Granada Shanghai University of Sport Jishou University Sichuan Agricultural University
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
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.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
计算机 / AIEducation and Learning Interventions
Mental Health via Writing · Technology Use by Older Adults
参考文献 36
此处列出前 3 条
引用本文 35
按被引量排序,此处列出前 3 条