Artificial Intelligence–Assisted Mental Health Screening, Healthcare Accessibility, and Early Intervention Outcomes: A Comparative Public Health Analysis of University-Based Digital Mental Health Systems in the United Kingdom and South Korea

Abstract

The global rise of anxiety, depression, psychological distress, and suicide risk among university students has intensified demand for scalable and accessible mental health systems. This study examines how artificial intelligence–assisted digital mental health screening influences early detection, healthcare accessibility, treatment engagement, and institutional mental health governance through a comparative public health analysis of university-based digital mental health systems in the United Kingdom and South Korea. The article argues that AI-assisted mental health systems are effective only when algorithmic screening is integrated with clinical referral pathways, institutional governance, behavioral support, and ethical safeguards. Using comparative health systems analysis, epidemiological interpretation, digital mental health evaluation, and interdisciplinary public health synthesis, the study compares two higher-education mental health environments characterized by different healthcare structures, social stigma patterns, digital adoption cultures, and institutional support systems. The findings indicate that AI-assisted screening may improve early identification of psychological distress and reduce barriers to help-seeking, particularly among digitally engaged populations. However, algorithmic systems may reproduce inequities when language bias, cultural 

stigma, privacy concerns, and unequal access to mental healthcare remain unresolved. The comparative evidence demonstrates that digital mental health technologies cannot substitute for comprehensive clinical care but may strengthen population-level prevention and early intervention when embedded within accountable healthcare governance frameworks. This article contributes to medical and health sciences scholarship by integrating epidemiology, behavioral health, digital psychiatry, healthcare governance, and institutional mental health systems into a comparative analytical framework.