Social-Ecological Factors Associated with AI Chatbot Use and Dependence
Abstract
With the rapid rise of artificial intelligence (AI) chatbots like ChatGPT, concerns about their overuse and potential psychological impacts are growing. This study investigates social-ecological factors associated with the use and dependence on AI chatbots. A cross-sectional online survey was conducted with 981 participants in China. Variables across four dimensions – individual characteristics, individual behaviors, interpersonal networks, and regional factors – were analyzed using generalized linear models. Results showed that AI chatbot use was positively associated with urban residence, regular exercise, solitary leisure preferences, younger age, higher education, and longer sleep duration. Usage frequency was linked to regular sleep patterns, efficient work habits, younger age, higher family income, larger social networks, and fewer family members. Problematic use and dependence were more likely among males, science majors, individuals with regular exercise and sleep patterns, and those from regions with lower employment rates. These findings offer theoretical and practical insights for future research, including variable selection, stratified sampling, and targeted interventions.
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LLM-CB dependence is associated with living in regions with lower employment rates.
“Finally, Li et al. found that LLM-CB dependence was associated with male sex, science majors, regular exercise and sleep patterns, and living in regions with lower employment rates117.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [117]
LLM-CB dependence is associated with regular exercise and sleep patterns.
“Finally, Li et al. found that LLM-CB dependence was associated with male sex, science majors, regular exercise and sleep patterns, and living in regions with lower employment rates117.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [117]
LLM-CB dependence is associated with science majors.
“Finally, Li et al. found that LLM-CB dependence was associated with male sex, science majors, regular exercise and sleep patterns, and living in regions with lower employment rates117.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [117]
LLM-CB dependence is associated with male sex.
“Finally, Li et al. found that LLM-CB dependence was associated with male sex, science majors, regular exercise and sleep patterns, and living in regions with lower employment rates117.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [117]
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“Recent empirical studies further reveal that men report higher levels of PGAIU and are more likely to engage in problematic patterns of GAI use than women (Li et al., 2025; Yu et al., 2024).”
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“Finally, Li et al. found that LLM-CB dependence was associated with male sex, science majors, regular exercise and sleep patterns, and living in regions with lower employment rates 117 .”
Kırcaburun, K. (2026) · BMC Psychology · doi:10.1186/s40359-026-05012-4 · Cited by 2
“Consistent with these differences, men also report higher levels of PGAIU and are more likely to engage in maladaptive patterns of GAI use than women [4, 49].”
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“Consistent with this framework, prior research has identified numerous individual-level factors associated with AI dependence, including anxiety (Hu et al., 2023; Huang et al., 2024), perceived usefulness (Liu, 2025; Samant et al., 2024), and self-control (Li et al., 2025; Ye et al., 2025).”
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“This possibility also supports examining chronotype-PGAIU associations separately by gender, as men and women may differ in their motivations for using GAI tools (Li et al. 2025).”
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- Authors
- Li, H., Tian, J., Yin, M., & Zhang, X.
- Affiliations
- Sichuan Agricultural University (CN)
- Sichuan University (CN)
- Shanghai University of Sport (CN)
- Universidad de Granada (ES)
- Corresponding author
- Li, Hansen
- Venue
- International Journal of Human–Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2025-09-24
- Volume
- 42
- Issue
- 11
- Pages
- 7776-7790
- ISSN
- 1044-7318 (ISSN-L)
- 1532-7590
- OpenAlex
- W4414480153
- Cited by
- 9
- References
- 0
- Citations by year
- 2026: 9
- FWCI
- 15.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Human-Computer Interaction (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Psychology › Social Psychology › Technostress in Professional Settings
- Keywords
- AI chatbots, ChatGPT, AI dependency, social-ecological factors, sleep patterns, physical activity, social networks, urban residence, household income, age and education
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