Smarter AI, Healthier Students? How Perceived AI Assistant Intelligence Shapes Medical Students’ Mental Health Through Learning Goal Progress and Academic Anxiety

As artificial intelligence (AI) adoption grows in medical education, AI assistants have become important learning support tools for medical students. However, existing research has primarily focused on learning performance and technology adoption, while little is known about how perceived AI assistant intelligence influences medical students’ mental health. Drawing on Self-Determination Theory (SDT), this study develops a model linking perceived AI assistant intelligence to mental health through the serial mediating roles of learning goal progress and academic anxiety, while examining the moderating role of AI literacy. A two-study design was employed. Study 1 surveyed 721 Chinese medical students, and Study 2 conducted a real human–AI interaction experiment with 398 medical students. Results showed that perceived AI assistant intelligence positively predicts learning goal progress. Learning goal progress and academic anxiety jointly mediate the relationship between perceived AI assistant intelligence and mental health. In addition, AI literacy strengthens the positive effect of perceived AI assistant intelligence on learning goal progress and enhances its indirect effect on mental health through the serial mediation pathway. The experimental findings further support the robustness of these relationships. This study extends research on AI in education by uncovering the psychological mechanisms through which perceived AI assistant intelligence affects medical students’ mental health. It also enriches the application of SDT in human–AI collaborative learning contexts and provides practical implications for optimizing AI-assisted learning environments, improving AI literacy, and promoting student well-being.

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Publication Details

Journal
Behavioral Sciences
Published
2026-09-22
DOI
https://doi.org/10.3390/bs16101715
Primary Topic
AI in Service Interactions
Type
article
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article

Smarter AI, Healthier Students? How Perceived AI Assistant Intelligence Shapes Medical Students’ Mental Health Through Learning Goal Progress and Academic Anxiety

Shuyue Zhang, Chenchen Xu, Xinru Liu, Miao Si et al.
Behavioral Sciences
AI in Service Interactions
article

Smarter AI, Healthier Students? How Perceived AI Assistant Intelligence Shapes Medical Students’ Mental Health Through Learning Goal Progress and Academic Anxiety

Shuyue Zhang, Chenchen Xu, Xinru Liu, Miao Si, Yue Chen, Liuyiran Li
article en

Abstract

As artificial intelligence (AI) adoption grows in medical education, AI assistants have become important learning support tools for medical students. However, existing research has primarily focused on learning performance and technology adoption, while little is known about how perceived AI assistant intelligence influences medical students’ mental health. Drawing on Self-Determination Theory (SDT), this study develops a model linking perceived AI assistant intelligence to mental health through the serial mediating roles of learning goal progress and academic anxiety, while examining the moderating role of AI literacy. A two-study design was employed. Study 1 surveyed 721 Chinese medical students, and Study 2 conducted a real human–AI interaction experiment with 398 medical students. Results showed that perceived AI assistant intelligence positively predicts learning goal progress. Learning goal progress and academic anxiety jointly mediate the relationship between perceived AI assistant intelligence and mental health. In addition, AI literacy strengthens the positive effect of perceived AI assistant intelligence on learning goal progress and enhances its indirect effect on mental health through the serial mediation pathway. The experimental findings further support the robustness of these relationships. This study extends research on AI in education by uncovering the psychological mechanisms through which perceived AI assistant intelligence affects medical students’ mental health. It also enriches the application of SDT in human–AI collaborative learning contexts and provides practical implications for optimizing AI-assisted learning environments, improving AI literacy, and promoting student well-being.

Behavioral SciencesVol. 16(10)
Second Affiliated Hospital of Nanjing Medical University (CN), Nanjing Medical University (CN)
Quality Education
Openalex Percentile: Top 8%
AI in Service Interactions
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Smarter AI, Healthier Students? How Perceived AI Assistant Intelligence Shapes Medical Students’ Mental Health Through Learning Goal Progress and Academic Anxiety — Shuyue Zhang, Chenchen Xu, et al. · Behavioral Sciences (2026) | TGRS Research Map | TGRS