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Currently accepted at: JMIR Mental Health

Date Submitted: Jun 19, 2026
Date Accepted: Oct 29, 2026

This paper has been accepted and is currently in production.

It will appear shortly on 10.2196/104812

The final accepted version (not copyedited yet) is in this tab.

AI Chatbot Use for Emotional Support Among Young Adults in Japan: Psychosocial Correlates and Dependence Tendencies in a Cross-Sectional Study

  • Tamaki Hosoda-Urban; 
  • Ben E. Urban

ABSTRACT

Background:

Generative artificial intelligence (AI) chatbots are increasingly used for mental health–related purposes, yet little is known about factors associated with such use or AI chatbot dependence.

Objective:

This study examined factors associated with young adults’ use of AI chatbots for emotional self-disclosure and mental health–related support, as well as associations between AI chatbot use and dependence.

Methods:

Participants were 820 individuals aged 18 to 29 years recruited through a Japanese online survey panel. Self-report measures assessed psychosocial factors (self-esteem and loneliness), mental health symptoms (anxiety and depression), AI chatbot use (emotional self-disclosure and mental health–related support), and AI chatbot dependence (emotional dependence and social anxiety–related dependence).

Results:

Overall, 46.5% of participants reported using AI chatbots for emotional self-disclosure at least once in the past month, including 7.9% who reported doing so almost daily. In addition, 41.0% reported using AI chatbots for mental health–related support, including 6.5% who reported almost daily use. Anxiety and depressive symptoms were combined into a mental health symptoms composite because of their high correlation. Multivariable logistic regression showed that mental health symptoms, but not self-esteem or loneliness, were associated with both emotional self-disclosure and mental health–related support. Among emotional self-disclosure users, emotional self-disclosure frequency was positively associated with both dependence dimensions. Path analyses indicated that a model specifying psychosocial factors and mental health symptoms as antecedent variables to AI chatbot use and dependence fit the data better than an AI-initiated alternative. In this model, lower self-esteem and greater loneliness were associated with higher mental health symptoms, which were associated with greater AI chatbot dependence largely through direct pathways, with a smaller additional pathway through more frequent emotional self-disclosure. Among emotional self-disclosure users, loneliness was the only significant psychosocial correlate of emotional dependence.

Conclusions:

Findings suggest that young adults experiencing mental health symptoms may be more likely to use AI chatbots for emotional self-disclosure and mental health–related support, while loneliness may be particularly relevant to emotional dependence among users. These findings highlight the need to understand AI chatbot use not only as a technological behavior, but also as part of young adults’ broader emotional and help-seeking landscape.


 Citation

Please cite as:

Hosoda-Urban T, Urban BE

AI Chatbot Use for Emotional Support Among Young Adults in Japan: Psychosocial Correlates and Dependence Tendencies in a Cross-Sectional Study

JMIR Mental Health. 29/10/2026:104812 (forthcoming/in press)

DOI: 10.2196/104812

URL: https://preprints.jmir.org/preprint/104812

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