Pathways from AI-assisted learning experience to psychological resilience: The role of stress perception in medical students

This study investigated the incidence of stressors and psychological resilience among medical students within the framework of AI-assisted (artificial intelligence-assisted) learning, with the objective of informing evidence-based treatments for the enhancement of resilience. A cross-sectional study utilizing random sampling was performed among 994 medical students from three medical colleges in East China in 2025.The data were analyzed utilizing SPSS version 27.0.The findings indicated that the psychological resilience ratings of medical students were markedly inferior to the national youth average. Resilience had a positive correlation with the utilization of AI applications and a negative correlation with various stressors, demonstrating differing magnitudes and directions of influence. The academic year, academic ranking, family income, only-child status, and gender significantly influenced the outcomes. Path analysis indicated that stress perception partially moderated the association between AI-assisted learning and resilience. These findings offer new empirical data regarding the pathways connecting AI-assisted learning experiences to psychological resilience and underscore the varying impacts of different stressors and individual backgrounds. The study provides practical insights for creating stress-categorization management systems and enhancing intelligent technology applications to promote mental health in medical education.

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Publication Details

Journal
Acta Psychologica
Published
2026-03-16
DOI
https://doi.org/10.1016/j.actpsy.2026.106658
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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0.00
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article

Pathways from AI-assisted learning experience to psychological resilience: The role of stress perception in medical students

Xi Huang, Xuejin Song, Hongxu Pan, Chenchen Xu et al.
Acta Psychologica
Artificial Intelligence in Healthcare and Education
article

Pathways from AI-assisted learning experience to psychological resilience: The role of stress perception in medical students

Xi Huang, Xuejin Song, Hongxu Pan, Chenchen Xu, Yining Bao, Jing Liu, Liang Fang
article en

Abstract

This study investigated the incidence of stressors and psychological resilience among medical students within the framework of AI-assisted (artificial intelligence-assisted) learning, with the objective of informing evidence-based treatments for the enhancement of resilience. A cross-sectional study utilizing random sampling was performed among 994 medical students from three medical colleges in East China in 2025.The data were analyzed utilizing SPSS version 27.0.The findings indicated that the psychological resilience ratings of medical students were markedly inferior to the national youth average. Resilience had a positive correlation with the utilization of AI applications and a negative correlation with various stressors, demonstrating differing magnitudes and directions of influence. The academic year, academic ranking, family income, only-child status, and gender significantly influenced the outcomes. Path analysis indicated that stress perception partially moderated the association between AI-assisted learning and resilience. These findings offer new empirical data regarding the pathways connecting AI-assisted learning experiences to psychological resilience and underscore the varying impacts of different stressors and individual backgrounds. The study provides practical insights for creating stress-categorization management systems and enhancing intelligent technology applications to promote mental health in medical education.

Acta PsychologicaVol. 265
Second Affiliated Hospital of Nanjing Medical University (CN), Southeast University (CN), Nanjing Medical University (CN)
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Openalex Percentile: Top 22%
Artificial Intelligence in Healthcare and Education
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Pathways from AI-assisted learning experience to psychological resilience: The role of stress perception in medical students — Xi Huang, Xuejin Song, et al. · Acta Psychologica (2026) | TGRS Research Map | TGRS