REVIEW article
Front. Psychiatry
Sec. Digital Mental Health
Volume 16 - 2025 | doi: 10.3389/fpsyt.2025.1621768
This article is part of the Research TopicApplication of chatbot Natural Language Processing models to psychotherapy and behavioral mood healthView all 14 articles
Effectiveness of Artificial Intelligence Chatbots on Mental Health & Well-being in College Students: A Rapid Systematic Review
Provisionally accepted
- University of Florida, Gainesville, United States
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Background: Mental health disorders among college students have surged in recent years, exacerbated by barriers such as stigma, cost associated with treatment, and limited access to mental health providers. Artificial intelligence (AI)-driven chatbots have emerged as scalable, stigma-free tools to deliver evidence-based mental health support, yet their efficacy specifically for college populations remains underexplored. Objective: This systematic rapid review evaluates the effectiveness of chatbots in improving mental health outcomes (e.g., anxiety, depression) and well-being among college students while identifying key design features and implementation barriers. Methods: Four databases (PubMed, PsycInfo, Applied Science & Technology Source, ACM Digital Library) were searched for studies published between 2014 and 2024. Two reviewers independently screened articles using predefined PICO criteria, extracted data and assessed quality via the PEDro scale. Included studies focused on chatbot interventions targeting DSM-5-defined mental health conditions or well-being in college students. Results: Nine studies (n=1,082 participants) were included, with eight reported statistically significant improvements in anxiety (e.g., GAD-7 reductions), depression (e.g., PHQ-9 scores), or well-being. Effective chatbots frequently incorporated cognitive-behavioral therapy (CBT), daily interactions, and cultural personalization (e.g., 22% depression reduction with Woebot; p<0.05). However, heterogeneity in study quality (PEDro scores: 1–7), high attrition rates (up to 61%), and reliance on self-reported outcomes limited generalizability. Conclusion: Though the use of chatbots for the improvement of mental health and well-being is promising based on the review’s results, future research should prioritize rigorous RCTs, standardized outcome measures (e.g., PHQ-9, GAD-7), and strategies to improve attrition.
Keywords: Mental Health, artificial intelligence, Chatbot, conversational agent, college students
Received: 01 May 2025; Accepted: 11 Aug 2025.
Copyright: © 2025 Nyakhar and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Shahzadhi Nyakhar, University of Florida, Gainesville, United States
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