Currently accepted at: JMIR Medical Education
Date Submitted: Oct 6, 2025
Date Accepted: Mar 30, 2026
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/85373
The final accepted version (not copyedited yet) is in this tab.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Scenario Analysis Reveals How Generative AI Will Impact The Mental Health of Medical Students
ABSTRACT
Background:
Introduction: Generative artificial intelligence (AI) is rapidly transforming medical education, while medical students continue to face high levels of stress, anxiety, and burnout. This dual pressure stemming from technological disruption and psychological vulnerability raises urgent questions about the future of training physicians.
Objective:
Introduction: Generative artificial intelligence (AI) is rapidly transforming medical education, while medical students continue to face high levels of stress, anxiety, and burnout. This dual pressure stemming from technological disruption and psychological vulnerability raises urgent questions about the future of training physicians.
Methods:
Methods:
We used scenario analysis, a foresight methodology, to explore possible futures at the intersection of generative AI and medical students’ mental health. The exploratory scanning identified weak signals and emerging trends, which were clustered using a macro-meso-micro framework and interpreted through a multi-level perspective of socio-technical change. Scenarios were analyzed along two key dimensions: the extent of generative AI integration into medical curricula and the availability of mental health support.
Results:
Results:
Four distinct scenarios emerged: Analogue Happiness (high support, low AI integration), Gen AI Paradise (high support, high integration), Disconnected Struggles (low support, low integration), and Gen AI Takeover (low support, high integration). Each illustrates different risks and opportunities for students’ digital readiness and psychological well-being. Discussion: The findings suggest that technological innovation and mental health support must co-evolve in medical education. Prioritizing one without the other risks producing either digitally unprepared or emotionally fragile physicians. Faculty readiness, ethical frameworks, and participatory curriculum design are critical to ensuring balanced integration. We formulated practical recommendations tailored to students, educators, and other stakeholders to guide balanced adaptation.
Conclusions:
Conclusions:
Generative AI is not an optional add-on but a transformative force, while mental health support is a prerequisite for competence. Institutions must rise to the dual responsibility of preparing students to become both digitally fluent and emotionally resilient. Failing to integrate these pillars constitutes not only a missed opportunity but an ethical failure with consequences for students, educators, healthcare professionals, and ultimately, patients.
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Copyright
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