Objective: This study aimed to evaluate the psychological distress, psychopathology, and resilience of university students in Mumbai using a multidimensional, digitalized psychometric assessment battery designed for early identification and triage of mental health concerns. Methods: A cross-sectional study was conducted among 442 engineering students at K.J. Somaiya Institute of Technology. Participants completed six validated digital screening tools assessing stress, psychiatric symptoms, mental health risk, resilience, positivity, and functioning. A digital algorithm classified students into referral pathways: self-help, counseling, or psychiatric intervention. Statistical analysis included K-means clustering, chi-square tests, and Pearson correlation. Results: A high prevalence of psychological stress (76%) was observed, with 14.3% experiencing severe stress. Severe psychiatric symptoms were present in 6.8% of participants, and 5.4% exhibited red-flag indicators requiring immediate psychiatric attention. Notably, 31% showed low resilience, and 36.6% reported impaired functioning. Chi-square analysis showed significant associations between stress and symptoms, resilience, and functioning (p < 0.001). Correlation analysis revealed strong inter-domain relationships, confirming the value of comprehensive assessment. Conclusion: Multidimensional, digital psychometric screening provides a scalable, context-sensitive approach for identifying student mental health needs. Integrating such tools within academic institutions can enhance early intervention, promote mental well-being, and support tailored mental health services in university settings.
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