Narrative review addresses prevalence and management of depression in medical students, suggesting digital tools improve outcomes.
Medical students experience high rates of depression due to intense academic demands, challenges in identity formation, and limited support networks. Despite growing awareness, early detection and effective management remain insufficient. This narrative review synthesizes current evidence on the prevalence, recognition, and management of depression in medical students, with a focus on digital identification tools and competence-based mental health education. Included studies address prevalence, recognition, digital interventions, educational reforms, and competence development. Evidence indicates that stigma, inadequate training, and inconsistent institutional protocols hinder timely identification. Digital interventions including self-screening applications, remote counseling platforms, and predictive analytics models offer scalable and accessible solutions, though challenges remain in privacy, equitable access, and cultural adaptability. Integrating mental health competence into curricula is increasingly recognized as critical, encompassing self-awareness, help-seeking behavior, peer support, professional boundaries, and digital literacy for mental health tools. Most studies are cross-sectional, limiting understanding of longitudinal outcomes and the sustained impact of interventions. Future efforts should prioritize culturally responsive digital solutions, structured competence-based training, and system-level strategies to foster psychologically safe learning environments. We propose a conceptual framework linking prevalence, digital tools, educational interventions, and institutional policies to guide systemic improvements in depression recognition and management for medical students. This review highlights the need for coordinated strategies to reduce barriers, enhance competence, and promote well-being, ultimately supporting students’ academic success and professional development.
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Ren et al. (2026) studied this question.
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