Author
Dr. Jitendra Singh, Vaibhav, Dr. Nitin Kumar
Keywords
Depression Assessment; Anxiety Disorders; Psychometric Models; Tripartite Model; Digital Mental Health Diagnostics; Computational Psychiatry.
Abstract
Depression and anxiety disorders represent two of the most prevalent mental health conditions worldwide and contribute significantly to the global burden of disease. Accurate clinical assessment plays a crucial role in identifying these disorders, guiding treatment planning, and monitoring therapeutic outcomes. This cross-sectional analytical study examines clinical assessment models used in the diagnosis and evaluation of depression and anxiety disorders and explores the integration of traditional psychometric methods with emerging computational and AI-based approaches among 226 individuals. Integrated assessment models combining psychometric screening tools, cognitive frameworks, and digital mental health analytics provide more comprehensive diagnostic insights compared with single-method approaches. Network-based models demonstrated the highest predictive accuracy in identifying symptom severity (F=6.14, p=0.002). Continued research into digital mental health diagnostics and computational psychiatry may further enhance the accuracy and accessibility of mental health assessments.
References
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[51] Vettriselvan, R., & Rajan FSA, A. J. (2019). Occupational Health Issues Faced by Women in Spinners. Indian Journal of Public Health Research & Development, 10(1).
[52] Vettriselvan, R., Deepan, A., Jaiswani, G., Balakrishnan, A., & Sakthivel, R. (2025). Health Consequences of Early Marriage: Examining Morbidity and Long-Term Wellbeing. In Social, Political, and Health Implications of Early Marriage (pp. 189-212). IGI Global Scientific Publishing.
[53] Vettriselvan, R., Ramya, R., Selvalakshmi, V., Jyothi, P., & Velmurugan, P. R. (2026). Empowering Patients through Knowledge: Educational Strategies in Rehabilitation. In Holistic Approaches to Health Recovery (pp. 263-290). IGI Global Scientific Publishing.
[54] Vijayalakshmi, M., Subramani, A. K., Vettriselvan, R., Catherin, T. C., & Deepika, R. (2025). Sustainability and Responsibility in the Digital Era: Leveraging Green Marketing in Healthcare. In Digital Citizenship and Building a Responsible Online Presence (pp. 285-306). IGI Global Scientific Publishing.
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[56] Zahoor, H., Mustafa, N., Ashifa, K. M., Safaei, M., & El Gamil, R. (2025). Unlocking resilience: Emotional intelligence and self-leadership shape stress perception among health students. International Journal of Innovation and Learning, 38(4), 395–419.
[2] Beck, R., Benedict, B., & Winkler, A. (2003). Depression and anxiety: integrating the tripartite and cognitive content-specificity assessment models. Journal of Psychopathology and Behavioral Assessment, 25(4), 251–256.
[3] Belzung, C., & Lemoine, M. (2011). Criteria of validity for animal models of psychiatric disorders. Biology of Mood & Anxiety Disorders, 1(1), 9.
[4] Belzer, K., & Schneier, F. R. (2004). Comorbidity of anxiety and depressive disorders. Journal of Psychiatric Practice, 10(5), 296–306.
[5] Burns, D. D., & Eidelson, R. J. (1998). Why are depression and anxiety correlated? A test of the tripartite model. Journal of Consulting and Clinical Psychology, 66(3), 461.
[6] Cai, H., et al. (2024). A network model of depressive and anxiety symptoms. Molecular Psychiatry, 29(3), 767–781.
[7] Castanheira, L., et al. (2018). Anxiety assessment in pre-clinical tests and in clinical trials. Current Topics in Medicinal Chemistry, 18(19), 1656–1676.
[8] Chow, P. I., et al. (2017). Using mobile sensing to test clinical models of depression, social anxiety, state affect, and social isolation among college students. Journal of Medical Internet Research, 19(3), e62.
[9] Clark, L. A., & Watson, D. (1991). Tripartite model of anxiety and depression. Journal of Abnormal Psychology, 100(3), 316.
[10] Ferreira, M. F., et al. (2018). Depression assessment in clinical trials and pre-clinical tests. Current Topics in Medicinal Chemistry, 18(19), 1677–1703.
[11] Fuchs, E., & Flugge, G. (2006). Experimental animal models for the simulation of depression and anxiety. Dialogues in Clinical Neuroscience, 8(3), 323–333.
[12] Lam, R. W., Michalaak, E. E., & Swinson, R. P. (2006). Assessment scales in depression and anxiety. CRC Press.
[13] Naragon-Gainey, K., et al. (2016). A comparison and integration of structural models of depression and anxiety in a clinical sample. Journal of Abnormal Psychology, 125(7), 853.
[14] Nemesure, M. D., et al. (2021). Predictive modeling of depression and anxiety using electronic health records and a novel machine learning approach. Scientific Reports, 11(1), 1980.
[15] Nordin, K., et al. (2001). Predicting anxiety and depression among cancer patients: a clinical model. European Journal of Cancer, 37(3), 376–384.
[16] Obbarius, A., et al. (2017). Standardization of health outcomes assessment for depression and anxiety. Quality of Life Research, 26(12), 3211–3225.
[17] Rekha R, A S Aneeshkumar, (2026). Machine Learning Approaches for social media Based Depression Detection: A Review, Telematique, 25(1), pp. 373-383.
[18] Orner, R. J., et al. (2004). Anxiety and depression: a model for assessment and therapy in primary care. Primary Care Mental Health, 2(1), 55–65.
[19] Rose, M., & Devine, J. (2014). Assessment of patient-reported symptoms of anxiety. Dialogues in Clinical Neuroscience, 16(2), 197–211.
[20] Shankman, S. A., & Klein, D. N. (2003). The relation between depression and anxiety. Clinical Psychology Review, 23(4), 605–637.
[21] Zhiguo, W. U., & Yiru, F. A. N. G. (2014). Comorbidity of depressive and anxiety disorders: challenges in diagnosis and assessment. Shanghai Archives of Psychiatry, 26(4), 227.
[22] Arockia, V. J., Vettriselvan, R., Rajesh, D., Velmurugan, P. R. R., & Cheelo, C. (2025). Leveraging AI and Learning analytics for enhanced distance learning: transformation in education. In AI and learning analytics in distance learning (pp. 179-206). IGI Global Scientific Publishing.
[23] Ashifa, K. M. (2019). Developmental initiatives for persons with disabilities: Appraisal on village-based rehabilitation of Amar Seva Sangam. Indian Journal of Public Health Research & Development, 10(12), 1257–1261.
[24] Rasi, R. A., & Ashifa, K. M. (2019). Role of community-based programmes for active ageing: Elders self-help group in Kerala. Indian Journal of Public Health Research & Development, 10(12).
[25] Ashifa, K. M. (2020). Effect of substance abuse on physical health of adolescents. European Journal of Molecular & Clinical Medicine, 7(2), 3155–3160.
[26] Ashifa, K. M. (2020). Physical health hazards of schizophrenia patients. Systematic Reviews in Pharmacy, 11(12), 1848–1850.
[27] Ashifa, K. M. (2021). Analysis on the determinants of health status among tribal communities. Journal of Cardiovascular Disease Research, 12(3), 531–534.
[28] Ashifa, K. M. (2021). Health status of primitive tribal women in India. Journal of Cardiovascular Disease Research, 12(5), 772.
[29] Ashifa, K. M. (2022). A situation analysis of the social well-being of elderly during the COVID-19 pandemic. International Journal of Health Sciences, 6(3), 10156–10163.
[30] Ashifa, K. M., & Ramya, P. (2019). Health afflictions and quality of work life among women working in fireworks industry. International Journal of Engineering and Advanced Technology, 8(6S3), 1723–1725.
[31] Basha, R., Pathak, P., Sudha, M., Soumya, K. V., & Arockia Venice, J. (2025). Optimization of quantum dilated convolutional neural networks: Image recognition with quantum computing. Internet Technology Letters, 8(3), e70027.
[32] Catherine, S., Gupta, N., Gopi, E., & Swadhi, R. (2025). Enhancing Patient Engagement and Outcomes Through Digital Transformation: Machine Learning in Medical Marketing. In Impact of Digital Transformation on Business Growth and Performance (pp. 285-312). IGI Global Scientific Publishing.
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[34] Elkin, N., Mohammed, A. K., Kilincel, S., Soydan, A. M., Tanriver, S. C., Celik, S., & Ranganathan, M. (2025). Mental health literacy and happiness among university students: A social work perspective to promoting well-being. Frontiers in Psychiatry, 16, 1541316.
[35] Gayathri, R. K., Vettriselvan, R., Rajesh, D., Balakrishnan, R., Kumar, R., & Kavitha, J. (2025). Striking a Balance: Mental Health Challenges and Work-Life Integration among Women Faculty in Indian B-Schools. Texila International Journal of Public Health, 13(2).
[36] Gayathri, R. K., Vettriselvan, R., Rajesh, D., Balakrishnan, R., Kumar, R., & Kavitha, J. (2025). Strategic Role of Human Resource Management in Enhancing Occupational Health and Safety Practices in Business Schools in India. Texila International Journal of Public Health, 13(2).
[37] Jenifer, R. D., Vettriselvan, R., Saxena, D., Velmurugan, P. R., & Balakrishnan, A. (2025). Green Marketing in Healthcare Advertising: A Global Perspective. In AI Impacts on Branded Entertainment and Advertising (pp. 303-326). IGI Global Scientific Publishing.
[38] Kariveliparambil, A., Rasi, R. A., Ahmad, M. S., Oztas, N., & Ayan, F. S. (2026). Evolving Social Capital in Indigenous Communities: Perspectives on Trust, Reciprocity, and Cultural Preservation Among Irula Elders. Journal of Social Service Research, 52(1), 147–166.
[39] Mustafa, N., Zahoor, H., Gamil, R. E., Ashifa, K. M., & Safaei, M. (2026). Empowering future caregivers: the role of self-leadership in reducing stress among nursing students. International Journal of Innovation and Learning, 39(1), 74-103.
[40] Natraj, N. A., Abirami, T., Ananthi, K., Venice, J. A., Chandru, R., & Rathish, C. R. (2024). The Impact of 5G Technology on the Digital Supply Chain and Operations Management Landscape. In Applications of New Technology in Operations and Supply Chain Management (pp. 289-311). IGI Global Scientific Publishing.
[41] Ranganathan, M., Jacob, A., Ashifa, K. M., Kumar, G. J., Anthony, M., Vijay, M., & Kumari, R. B. (2024). An investigation of the effects of chronic stress on attention in parents of children with neurodevelopmental disorders. Universal Journal of Public Health, 12(1), 37–50.
[42] Shanthi, H. J., Gokulakrishnan, A., Sharma, S., Deepika, R., & Swadhi, R. (2025). Leveraging Artificial Intelligence for Enhancing Urban Health: Applications, Challenges, and Innovations. In Nexus of AI, Climatology, and Urbanism for Smart Cities (pp. 275-306). IGI Global Scientific Publishing.
[43] Swadhi, R., Gayathri, K., Suresh, N. V., Catherine, S., & Velmurugan, P. R. (2025). Leveraging Machine Learning for Enhanced Patient Engagement and Outcomes: Revolutionizing Healthcare Marketing. In Impact of Digital Transformation on Business Growth and Performance (pp. 313-340). IGI Global Scientific Publishing.
[44] Swadhi, R., Velmurugan, P. R., Mahalingam, U., Keerthana, R., & Padmavathy, N. (2026). Embedding Fairness and Resilience: Human-Centered Leadership in AI-Driven Workplaces. In Centering Positive Organizational Cultures Through Human-Centered Leadership (pp. 139-162). IGI Global Scientific Publishing.
[45] Venice, J. A., Arivazhagan, D., Suman, N., Shanthi, H. J., & Swadhi, R. (2025). Recommendation systems and content personalization: algorithms, applications, and adaptive learning. In AI for Large Scale Communication Networks (pp. 323-348). IGI Global Scientific Publishing.
[46] Venice, J. A., Vettriselvan, R., Rajesh, D., Suresh, N. V., & Abirami, P. (2025). Enabling personalized learning and adaptive systems through strategic management: cloud integration in education. In Bridging Academia and Industry Through Cloud Integration in Education (pp. 49-72). IGI Global Scientific Publishing.
[47] Venice, J. A., Vettriselvan, R., Jain, S., Madusudanan, K., & Aarthy, C. C. J. (2025). Performance Evaluation and Metrics in Blockchain Powered AI/ML: Data Analytics for Cognitive Internet of Things (CIoT). In Transforming Education With AI-Powered Personalized Learning (pp. 143-178). IGI Global Scientific Publishing.
[48] Venice, A., Swadhi, R., Gayathri, K., Chandra, P., & Sajana, K. P. (2026). Rehabilitation Robotics and Adaptive Motion Planning for Patient-Centric Care. In Intelligent Motion Control for Human-Centered Systems (pp. 51-76). IGI Global Scientific Publishing.
[49] Vettriselvan, R. (2025). Harnessing innovation and digital marketing in the era of industry 5.0: resilient healthcare SMEs. In The Future of Small Business in Industry 5.0 (pp. 163-186). IGI Global Scientific Publishing.
[50] Vettriselvan, R., & Anto, M. R. (2018). Pathetic health status and working condition of Zambian women. Indian Journal of Public Health Research & Development, 9(9), 259-264.
[51] Vettriselvan, R., & Rajan FSA, A. J. (2019). Occupational Health Issues Faced by Women in Spinners. Indian Journal of Public Health Research & Development, 10(1).
[52] Vettriselvan, R., Deepan, A., Jaiswani, G., Balakrishnan, A., & Sakthivel, R. (2025). Health Consequences of Early Marriage: Examining Morbidity and Long-Term Wellbeing. In Social, Political, and Health Implications of Early Marriage (pp. 189-212). IGI Global Scientific Publishing.
[53] Vettriselvan, R., Ramya, R., Selvalakshmi, V., Jyothi, P., & Velmurugan, P. R. (2026). Empowering Patients through Knowledge: Educational Strategies in Rehabilitation. In Holistic Approaches to Health Recovery (pp. 263-290). IGI Global Scientific Publishing.
[54] Vijayalakshmi, M., Subramani, A. K., Vettriselvan, R., Catherin, T. C., & Deepika, R. (2025). Sustainability and Responsibility in the Digital Era: Leveraging Green Marketing in Healthcare. In Digital Citizenship and Building a Responsible Online Presence (pp. 285-306). IGI Global Scientific Publishing.
[55] Vijayalakshmi, M., Subramani, A. K., Vettriselvan, R., Velmurugan, P. R., & Hasine, J. (2025). Strategic Collaborations in Medical Innovation and AI-Driven Globalization: Advancing Healthcare Startups. In Navigating Strategic Partnerships for Sustainable Startup Growth (pp. 85-110). IGI Global Scientific Publishing.
[56] Zahoor, H., Mustafa, N., Ashifa, K. M., Safaei, M., & El Gamil, R. (2025). Unlocking resilience: Emotional intelligence and self-leadership shape stress perception among health students. International Journal of Innovation and Learning, 38(4), 395–419.
Received : 28 February 2026
Accepted : 30 April 2026
Published : 03 May 2026
DOI: 10.30726/esij/v13.i2.2026.1320024