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

Journal: Cyberpsychology, behavior and social networking
PMID:

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.

Authors

  • Xing Zhang
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
  • Mingyue Yin
    School of Athletic performance, Shanghai University of Sport, Shanghai, China.
  • Mingyang Zhang
    School of Quality and Technical Supervision, Hebei University, Baoding, Hebei 071002, P.R.China.
  • Zhaoqian Li
    Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, Granada, Spain.
  • Hansen Li
    School of Physical Education, Sichuan Agricultural University, Ya'an, China.