article · BMC Medical Education
Medical students face a significant burden of depressive symptoms and social isolation, particularly in conflict-affected regions like Sudan, where access to formal mental health services is severely restricted. While AI chatbots are increasingly adopted for academic and emotional assistance, their relationship with psychological outcomes in such unstable, resource-constrained environments remains poorly characterized. This study aimed to evaluate the association between conversational AI utilization, depressive symptoms, and social isolation among Sudanese medical students to guide evidence-based policy and the responsible development of digital support tools. A large-scale, cross-sectional survey was conducted between November 2025 and March 2026. Data were collected from 2,507 medical students using validated instruments, including the Patient Health Questionnaire-9 (PHQ-9) for depressive symptoms and the Revised UCLA Loneliness Scale-6 (RULS-6) for social isolation. Structured questionnaires assessed sociodemographic characteristics, chatbot usage patterns, and perceived psychological benefits. Chatbot adoption was nearly universal, with 41.9% of participants reporting daily use. Although academic perceived support was the primary driver of engagement (88.8%), significant subsets also used AI for companionship (22.2%) and to cope with stress or loneliness (23.1%). High prevalence rates were observed for both mild-to-severe depressive symptoms (70.6%) and moderate-to-high loneliness (65.0%). Students exhibiting higher levels of psychological distress were significantly more likely to report emotional connectivity, perceived companionship, and subjective well-being benefits from AI interactions, although these correlations remained statistically weak. Conversational AI chatbots have become a ubiquitous tool among Sudanese medical students, fulfilling both pedagogical and relational roles. In a conflict-affected context with restricted access to formal mental health services, AI provides a scalable, low-barrier support mechanism. However, the potential for digital reliance to exacerbate social withdrawal warrants caution. These findings emphasize the need for responsible AI integration and longitudinal research to delineate the long-term effects of AI-mediated support on student well-being.
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DOI: 10.1186/s12909-026-10326-3
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