Digital Mental Health Screening Among Indian University Students: Psychometric Validation of the Mental Health Assessment Scale for Students

Abstract Background: Early identification of psychological distress among university students is a public health priority, particularly in low-resource settings. International evidence indicates substantial prevalence of anxiety, depressive symptoms, and functional impairment among college populations. In India, treatment gaps remain high, especially among young adults. Most existing screening tools focus primarily on symptom detection and do not integrate vulnerability, resilience, and functional impact within a unified framework. The Mental Health Assessment Scale for Students (MASS) was developed as a multidimensional screening instrument to address this gap. The study aimed to evaluate the reliability, structural validity, discriminative performance, and clinical utility of MASS in distinguishing nonclinical students from psychiatric patients. Methodology: A cross-sectional known-group validation study was conducted with 456 participants (304 students and 152 psychiatric patients). Participants completed MASS, the General Health Questionnaire, and the World Health Organization disability framework-based functioning measure. Internal consistency was assessed using Cronbach’s alpha and McDonald’s omega. Exploratory factor analysis evaluated structural validity. Known-group validity was examined using independent-sample comparisons and effect sizes. Receiver operating characteristic analysis determined optimal cutoffs. Logistic regression examined predictors of moderate-to-severe risk. Concordance with psychiatrist referral decisions was assessed using Cohen’s kappa. Results: MASS demonstrated strong internal consistency (α = 0.82–0.91; composite α = 0.91). A four-factor solution explained 63% of variance (Kaiser–Meyer–Olkin = 0.89). All domains significantly differentiated students and patients ( P < 0.001; Cohen’s d = 1.33–2.21). The composite score showed good discrimination (area under the curve = 0.88; 95% confidence interval: 0.84–0.92). At cutoff ≥ 294, sensitivity was 83% and specificity was 79% (positive predictive value = 65%; negative predictive value = 90%). Logistic regression identified stress, functional impairment, and low resilience as significant predictors (Nagelkerke R ² = 0.32). Concordance with psychiatrist decisions was moderate (κ =0.49). Conclusion: MASS demonstrates good reliability and discriminative validity as a multidimensional screening instrument suitable for institutional triage and stratification. Further longitudinal and multisite validation is warranted.