The Development and Validation of an Artificial Intelligence Chatbot Dependence Scale

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

Institutions

Publication Details

Journal
Cyberpsychology Behavior and Social Networking
Published
2024-11-26
DOI
https://doi.org/10.1089/cyber.2024.0240
Citations
16
Primary Topic
Education and Learning Interventions
Type
article
Field-Weighted Citation Impact
12.47
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Development and Validation of an Artificial Intelligence Chatbot Dependence Scale

H. Li, Mingyue Yin, Xing Zhang, Zhaoqian Li et al.
16 citations
Cyberpsychology Behavior and Social Networking
Education and Learning Interventions
12.47
article

The Development and Validation of an Artificial Intelligence Chatbot Dependence Scale

H. Li, Mingyue Yin, Xing Zhang, Zhaoqian Li, Mingyang Zhang
article en
16 citations

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.

Cyberpsychology Behavior and Social NetworkingVol. 28(2)
Jishou University (CN), Universidad de Granada (ES), Shanghai University of Sport (CN), Sichuan Agricultural University (CN)
Openalex Percentile: Top 1%
Education and Learning Interventions
12.47
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

The Development and Validation of an Artificial Intelligence Chatbot Dependence Scale — H. Li, Mingyue Yin, et al. · Cyberpsychology Behavior and Social Networking (2024) | TGRS Research Map | TGRS