Accepted for/Published in: JMIR Formative Research
Date Submitted: Aug 19, 2025
Date Accepted: Mar 6, 2026
Anxiety and depression associated with the dependent use of generative artificial intelligence in medical students: A cross-sectional study
ABSTRACT
Background:
The increasing use of artificial intelligence (AI) -based tools in academic contexts has raised concerns about their impact on mental health, especially in vulnerable populations such as medical students.
Objective:
This study aimed to evaluate the association between AI dependence and levels of stress, anxiety, and depression in medical students.
Methods:
A cross-sectional study was carried out on 187 Human Medicine students from a Peruvian university, during the first academic semester of 2025. The AI Dependency Scale (DIA) and the DASS-21 scale were applied to measure mental health. Negative binomial regression models adjusted for sex, age, and economic income were used, reporting B coefficients, 95% confidence intervals, and índices of significance (p).
Results:
In the adjusted model, dependence on AI was significantly associated with higher levels of anxiety (B = 0.05; 95% CI: 0.01–0.09; p = 0.01) and depression (B = 0.04; 95% CI: 0.01–0.08; p = 0.03). The association with stress was marginally significant (B = 0.03; 95% CI: -0.00 – 0.07; p = 0.08). In addition, fifth-year students showed a higher likelihood of anxiety than sixth-year students.
Conclusions:
Dependence on artificial intelligence is related to a greater impact on the mental health of medical students, especially in the domains of anxiety and depression. Preventive interventions are required to encourage conscious use of AI in educational settings.
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