Dr. Anuja Rajoriya, Vaibhav, Manish Samyal

Childhood Obesity; Metabolic Syndrome; Cardiometabolic Risk Factors; Pediatric Obesity; Childhood Nutrition; Pediatric Public Health.

Childhood obesity has emerged as one of the most pressing global public health challenges, contributing significantly to the development of metabolic disorders and long-term chronic diseases. The rising prevalence of childhood obesity is associated with multiple cardiometabolic complications including insulin resistance, dyslipidemia, hypertension, and metabolic syndrome. This cross-sectional analytical study examines the prevalence of childhood obesity and its association with cardiometabolic risk factors among 264 children aged 6–15 years attending pediatric health clinics and school health programs. Elevated BMI levels were strongly associated with increased cardiometabolic risk indicators, including insulin resistance and abnormal lipid profiles. Children with sedentary lifestyles and poor dietary habits demonstrated significantly higher obesity prevalence. BMI level was the strongest predictor of metabolic risk (F=7.41, p=0.001). The study highlights the importance of early preventive interventions, lifestyle modification programs, and community-based health promotion strategies to address childhood obesity.

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[21] Ashifa, K. M. (2020). Effect of substance abuse on physical health of adolescents. European Journal of Molecular & Clinical Medicine, 7(2), 3155–3160.
[22] Ashifa, K. M. (2020). Physical health hazards of schizophrenia patients. Systematic Reviews in Pharmacy, 11(12), 1848–1850.
[23] Ashifa, K. M. (2021). Analysis on the determinants of health status among tribal communities. Journal of Cardiovascular Disease Research, 12(3), 531–534.
[24] Ashifa, K. M. (2021). Health status of primitive tribal women in India. Journal of Cardiovascular Disease Research, 12(5), 772.
[25] 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.
[26] 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.
[27] Catherine, S., et al. (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.
[28] Devi, M., et al. (2025). Precision Medicine, Personalized Treatment, and Network-Driven Innovations: Transforming Healthcare With AI. In AI for Large Scale Communication Networks (pp. 303-322). IGI Global Scientific Publishing.
[29] Elkin, N., et al. (2025). Mental health literacy and happiness among university students. Frontiers in Psychiatry, 16, 1541316.
[30] Gayathri, R. K., Vettriselvan, R., et al. (2025). Striking a Balance: Mental Health Challenges and Work-Life Integration. Texila International Journal of Public Health, 13(2).
[31] Gayathri, R. K., Vettriselvan, R., et al. (2025). Strategic Role of Human Resource Management in Enhancing Occupational Health and Safety Practices. Texila International Journal of Public Health, 13(2).
[32] Jenifer, R. D., Vettriselvan, R., et al. (2025). Green Marketing in Healthcare Advertising: A Global Perspective. In AI Impacts on Branded Entertainment and Advertising (pp. 303-326). IGI Global Scientific Publishing.
[33] Kariveliparambil, A., et al. (2026). Evolving Social Capital in Indigenous Communities. Journal of Social Service Research, 52(1), 147–166.
[34] Mustafa, N., et al. (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.
[35] Ranganathan, M., et al. (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.
[36] Rasi, R. A., & Ashifa, K. M. (2019). Role of community-based programmes for active ageing. Indian Journal of Public Health Research & Development, 10(12).
[37] Shanthi, H. J., et al. (2025). Leveraging Artificial Intelligence for Enhancing Urban Health. In Nexus of AI, Climatology, and Urbanism for Smart Cities (pp. 275-306). IGI Global Scientific Publishing.
[38] Swadhi, R., et al. (2025). Leveraging Machine Learning for Enhanced Patient Engagement and Outcomes. In Impact of Digital Transformation on Business Growth and Performance (pp. 313-340). IGI Global Scientific Publishing.
[39] Venice, A., Swadhi, R., et al. (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.
[40] 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.
[41] 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.
[42] Vettriselvan, R., & Rajan FSA, A. J. (2019). Occupational Health Issues Faced by Women in Spinners. Indian Journal of Public Health Research & Development, 10(1).
[43] Vettriselvan, R., Deepan, A., et al. (2025). Health Consequences of Early Marriage. In Social, Political, and Health Implications of Early Marriage (pp. 189-212). IGI Global Scientific Publishing.
[44] Vettriselvan, R., Ramya, R., et al. (2026). Empowering Patients through Knowledge: Educational Strategies in Rehabilitation. In Holistic Approaches to Health Recovery (pp. 263-290). IGI Global Scientific Publishing.
[45] Vettriselvan, R., Velmurugan, P. R., et al. (2025). Health Impacts of Smartphone and Internet Addictions Across Age Groups. In Impacts of Digital Technologies Across Generations (pp. 187-210). IGI Global Scientific Publishing.
[46] Vijayalakshmi, M., et al. (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.
[47] Vijayalakshmi, M., et al. (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.
[48] Zahoor, H., et al. (2025). Unlocking resilience: Emotional intelligence and self-leadership shape stress perception among health students. International Journal of Innovation and Learning, 38(4), 395–419.
[49] Kumar, A., et al. (2024). Malignant parotid gland tumours: A case series from a tertiary care centre in Western Uttar Pradesh. Journal of Carcinogenesis, 24(2), 157–163. https://doi.org/10.64149/J.Carcinog.24.2.157-163
[50] Avinash, K., Aanieq, M., Kanwar, S., Mansi, S., & Thajana Devi, K. (2025). Reinke’s Edema in A 5-Year-Old Child — A Rare Entity. Ame Journal of Surgery and Clinical Case Reports, 15(1), 1-4.
[51] Patel, A. M., Goel, S., Rai, V., Gopal, A. V., Gupta, V., & Nagpal, S. (2025). Anaesthetic management of 60-year-old female with ankylosing spondylitis undergoing a restorative surgery: A case report. International Journal of Medical and All Body Health Research, 6(2), 152–154. https://doi.org/10.54660/IJMBHR.2025.6.2.152-154
[52] Jain, T., Sahu, R. L., Bhatia, R., & Pratap, H. (2025). A comparative analysis of functional outcome of distal femur fractures treated with locking compression plate fixation and non-locking plate fixation. International Journal of Medical and All Body Health Research, 6(3), 200–207. https://doi.org/10.54660/IJMBHR.2025.6.3.200-207
[53] Kumar, A., Sinha, G., Sharma, M., Srivastava, S., & Acharya, K. (2025). Oncocytic variant of mucoepidermoid carcinoma parotid — a surgical case report. Journal of Contemporary Clinical Practice, 11(10), 291-294.
[54] Kumar, A., Titoria, C., Sinha, G., Sharma, M., & Yadav, E. (2025). Rare Coexistence of Follicular Adenoma Thyroid and Colloid Goitre — A Surgical Case Report. Journal of Contemporary Clinical Practice, 11(7), 391-395.
[55] Mahaveerakannan, R., Anitha, C., Balamanigandan, R., & Saraswathi, S. (2025). Enhanced Public Security: Modified YOLO Network for Unattended Object Detection in Dynamic Environments. In 2025 Global Conference in Emerging Technology (GINOTECH) (pp. 1-8). IEEE..

Dr. Bharat Gupta, Neha Kakran, Anupama Choudhary

Developmental Disorders; Behavioral Disorders; Early Childhood Screening; Developmental Surveillance; Pediatric Mental Health; Early Intervention.

Early identification of developmental and behavioral disorders is essential for ensuring optimal cognitive, emotional, and social development in children. Developmental delays and behavioral disorders often emerge during early childhood and may significantly affect long-term educational achievement, mental health, and social functioning if not detected and addressed at an early stage. Advances in pediatric screening practices and developmental surveillance have improved the ability of healthcare providers to identify children at risk for developmental and behavioral disorders, enabling timely intervention and support. This cross-sectional analytical study examines the effectiveness of early identification strategies among 242 children aged 1–10 years attending pediatric healthcare facilities and developmental clinics. Parental concerns, early developmental screening, and routine pediatric surveillance significantly improve the identification of developmental and behavioral disorders. Children with limited access to healthcare services and those from disadvantaged socioeconomic backgrounds were more likely to experience delayed identification. Early intervention programs demonstrated significant benefits in improving developmental outcomes among affected children. The study highlights the importance of integrating routine developmental screening, caregiver education, and community-based early intervention programs into pediatric healthcare systems.

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[5] Glascoe, F. P. (2015). Evidence-based early detection of developmental-behavioral problems in primary care. Journal of Pediatric Health Care, 29(1), 46-53.
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[10] Brauner, C. B., & Stephens, C. B. (2006). Estimating the prevalence of early childhood serious emotional/behavioral disorders. Public Health Reports, 121(3), 303-310.
[11] Costello, E. J. (2016). Early detection and prevention of mental health problems: developmental epidemiology and systems of support. Journal of Clinical Child & Adolescent Psychology, 45(6), 710-717.
[12] Sadler, C., & Sugai, G. (2009). Effective behavior and instructional support: A district model for early identification and prevention of reading and behavior problems. Journal of Positive Behavior Interventions, 11(1), 35-46.
[13] Lipkin, P. H., et al. (2020). Promoting optimal development: identifying infants and young children with developmental disorders through developmental surveillance and screening. Pediatrics, 145(1).
[14] Ilic, S. B., et al. (2020). Early identification of children with developmental delay and behavioural problems according to parents concerns in the Republic of Serbia. Early Child Development and Care.
[15] Bitsko, R. H. (2016). Health care, family, and community factors associated with mental, behavioral, and developmental disorders in early childhood. MMWR, 65.
[16] Schroeder, S. R., & Courtemanche, A. (2012). Early prevention of severe neurodevelopmental behavior disorders. Journal of Mental Health Research in Intellectual Disabilities, 5(3-4), 203-214.
[17] Council on Children With Disabilities, et al. (2006). Identifying infants and young children with developmental disorders in the medical home. Pediatrics, 118(1), 405-420.
[18] Jones, D., et al. (2002). Early identification of children at risk for costly mental health service use. Prevention Science, 3(4), 247-256.
[19] Roberts, C., et al. (2003). Early intervention for behaviour problems in young children with developmental disabilities. International Journal of Disability, Development and Education, 50(3), 275-292.
[20] Kendziora, K. T. (2004). Early intervention for emotional and behavioral disorders. Handbook of Research in Emotional and Behavioral Disorders, 327-351.
[21] 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.
[22] Ashifa, K. M. (2020). Effect of substance abuse on physical health of adolescents. European Journal of Molecular & Clinical Medicine, 7(2), 3155–3160.
[23] Ashifa, K. M. (2020). Physical health hazards of schizophrenia patients. Systematic Reviews in Pharmacy, 11(12), 1848–1850.
[24] Ashifa, K. M. (2021). Analysis on the determinants of health status among tribal communities. Journal of Cardiovascular Disease Research, 12(3), 531–534.
[25] Ashifa, K. M. (2021). Health status of primitive tribal women in India. Journal of Cardiovascular Disease Research, 12(5), 772.
[26] 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.
[27] 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.
[28] 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.
[29] Devi, M., Manokaran, D., Sehgal, R. K., Shariff, S. A., & Vettriselvan, R. (2025). Precision Medicine, Personalized Treatment, and Network-Driven Innovations: Transforming Healthcare With AI. In AI for Large Scale Communication Networks (pp. 303-322). IGI Global Scientific Publishing.
[30] 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.
[31] 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).
[32] 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).
[33] 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.
[34] Kariveliparambil, A., Rasi, R. A., Ahmad, M. S., Oztas, N., & Ayan, F. S. (2026). Evolving Social Capital in Indigenous Communities. Journal of Social Service Research, 52(1), 147–166.
[35] 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.
[36] 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.
[37] 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).
[38] 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.
[39] 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.
[40] 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.
[41] 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.
[42] 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.
[43] Vettriselvan, R., & Rajan FSA, A. J. (2019). Occupational Health Issues Faced by Women in Spinners. Indian Journal of Public Health Research & Development, 10(1).
[44] 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.
[45] 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.
[46] Vettriselvan, R., Velmurugan, P. R., Varshney, K. R., EP, J., & Deepika, R. (2025). Health Impacts of Smartphone and Internet Addictions Across Age Groups. In Impacts of Digital Technologies Across Generations (pp. 187-210). IGI Global Scientific Publishing.
[47] 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.
[48] 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.
[49] 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.
[50] Kumar, A., et al. (2024). Malignant parotid gland tumours: A case series from a tertiary care centre in Western Uttar Pradesh. Journal of Carcinogenesis, 24(2), 157–163. https://doi.org/10.64149/J.Carcinog.24.2.157-163
[51] Avinash, K., Aanieq, M., Kanwar, S., Mansi, S., & Thajana Devi, K. (2025). Reinke’s Edema in A 5-Year-Old Child — A Rare Entity. Ame Journal of Surgery and Clinical Case Reports, 15(1), 1-4.
[52] Patel, A. M., Goel, S., Rai, V., Gopal, A. V., Gupta, V., & Nagpal, S. (2025). Anaesthetic management of 60-year-old female with ankylosing spondylitis undergoing a restorative surgery: A case report. International Journal of Medical and All Body Health Research, 6(2), 152–154. https://doi.org/10.54660/IJMBHR.2025.6.2.152-154
[53] Jain, T., Sahu, R. L., Bhatia, R., & Pratap, H. (2025). A comparative analysis of functional outcome of distal femur fractures treated with locking compression plate fixation and non-locking plate fixation. International Journal of Medical and All Body Health Research, 6(3), 200–207. https://doi.org/10.54660/IJMBHR.2025.6.3.200-207
[54] Kumar, A., Sinha, G., Sharma, M., Srivastava, S., & Acharya, K. (2025). Oncocytic variant of mucoepidermoid carcinoma parotid — a surgical case report. Journal of Contemporary Clinical Practice, 11(10), 291-294.
[55] Kumar, A., Titoria, C., Sinha, G., Sharma, M., & Yadav, E. (2025). Rare Coexistence of Follicular Adenoma Thyroid and Colloid Goitre — A Surgical Case Report. Journal of Contemporary Clinical Practice, 11(7), 391-395.
[56] 56. Mahaveerakannan, R., Anitha, C., Balamanigandan, R., & Saraswathi, S. (2025). Enhanced Public Security: Modified YOLO Network for Unattended Object Detection in Dynamic Environments. In 2025 Global Conference in Emerging Technology (GINOTECH) (pp. 1-8). IEEE

Dr. Subhash Chandra, Komal Sharma, Vishal Kumar

Pediatric Respiratory Disorders; Allergic Rhinitis; Childhood Asthma; Pediatric Allergy Management; Respiratory Health; Pediatric Immunology.

Paediatric respiratory and allergic disorders are major global health concerns due to rapidly increasing prevalence and devastating effects on physical health, quality of life, and healthcare consumption of children. Allergic rhinitis, asthma, atopic dermatitis, and other respiratory allergies are among the most prevalent chronic diseases affecting children worldwide. Early diagnosis, effective clinical treatment, and preventive measures are essential to minimise disease burden and improve health outcomes in children. This cross-sectional analytical study questions clinical management approaches used in these conditions and evaluates determinants of therapeutic outcomes among 256 paediatric patients diagnosed with respiratory or allergic conditions in specialised paediatric healthcare centres. Clinical information was collected through medical record review, semi-structured caregiver interviews, and standardised assessment forms. Disease phenomenology, therapeutic interventions, medication compliance, environmental risk factors, and healthcare service access were analysed. Descriptive statistics, ANOVA, and multivariate regression were used to determine determinants of disease severity and treatment efficacy. Findings show that allergic rhinitis (30.5%) and asthma (25.8%) are the most common respiratory-allergic diseases; environmental allergens and family history are the most apparent risk factors. Early clinical diagnosis (F=7.12, p=0.001) and medication adherence (F=6.35, p=0.003) consistently improved symptom management and prevented complications. Digital health technologies and precision medicine are increasingly important in delivering optimal respiratory care to children.

[1] Ashifa, K. M. (2021). Analysis on the determinants of health status among tribal communities. Journal of Cardiovascular Disease Research, 12(3), 531–534.
[2] Berger, W. E. (2004). Allergic rhinitis in children: diagnosis and management strategies. Pediatric Drugs, 6(4), 233–250.
[3] Bertrand, P., & Sánchez, I. (2020). Pediatric respiratory diseases: A comprehensive textbook. Springer.
[4] Brough, H. A., Kalayci, O., Sediva, A., Untersmayr, E., Munblit, D., Rodriguez del Rio, P., & Eigenmann, P. A. (2020). Managing childhood allergies and immunodeficiencies during respiratory virus epidemics — the 2020 COVID-19 pandemic. Pediatric Allergy and Immunology, 31(5), 442–448.
[5] Cardinale, F., Ciprandi, G., Barberi, S., Bernardini, R., Caffarelli, C., Calvani, M., & Marseglia, G. L. (2020). Consensus statement of the Italian society of pediatric allergy and immunology for the pragmatic management of children and adolescents with allergic or immunological diseases during the COVID-19 pandemic. Italian Journal of Pediatrics, 46(1), 84.
[6] 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.
[7] Cutrera, R., Baraldi, E., Indinnimeo, L., Miraglia Del Giudice, M., Piacentini, G., Scaglione, F., & Duse, M. (2017). Management of acute respiratory diseases in the pediatric population: the role of oral corticosteroids. Italian Journal of Pediatrics, 43(1), 31.
[8] Devi, M., Manokaran, D., Sehgal, R. K., Shariff, S. A., & Vettriselvan, R. (2025). Precision Medicine, Personalized Treatment, and Network-Driven Innovations: Transforming Healthcare With AI. In AI for Large Scale Communication Networks (pp. 303–322). IGI Global.
[9] Elkin, N., Mohammed, A. K., Kılınçel, Ş., Soydan, A. M., Tanrıver, S. Ç., Çelik, Ş., & Ranganathan, M. (2025). Mental health literacy and happiness among university students: A social work perspective to promoting well-being. Frontiers in Psychiatry, 16, 1541316.
[10] Hendaus, M. A., Jomha, F. A., & Ehlayel, M. (2016). Allergic diseases among children: nutritional prevention and intervention. Therapeutics and Clinical Risk Management, 361–372.
[11] Lack, G. (2001). Pediatric allergic rhinitis and comorbid disorders. Journal of Allergy and Clinical Immunology, 108(1), S9–S15.
[12] Leung, D. Y., Sampson, H., Geha, R., & Szefler, S. J. (2010). Pediatric allergy: principles and practice E-Book. Elsevier Health Sciences.
[13] Lieberman, P., & Anderson, J. A. (Eds.). (2007). Allergic diseases: diagnosis and treatment. Springer Science & Business Media.
[14] Patella, V., Delfino, G., Florio, G., Spadaro, G., Chieco Bianchi, F., Senna, G., & Di Gioacchino, M. (2020). Management of the patient with allergic and immunological disorders in the pandemic COVID-19 era. Clinical and Molecular Allergy, 18(1), 18.
[15] 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.
[16] Ricci, G., Patrizi, A., Giannetti, A., Dondi, A., Bendandi, B., & Masi, M. (2010). Does improvement management of atopic dermatitis influence the appearance of respiratory allergic diseases? Clinical and Molecular Allergy, 8(1), 8.
[17] Scadding, G. K. (2015). Optimal management of allergic rhinitis. Archives of Disease in Childhood, 100(6), 576–582.
[18] 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.
[19] Taussig, L. M., & Landau, L. I. (2008). Pediatric Respiratory Medicine E-Book. Elsevier Health Sciences.
[20] 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.
[21] Woloski, J. R., Heston, S., & Calderon, S. P. E. (2016). Respiratory allergic disorders. Primary Care: Clinics in Office Practice, 43(3), 401–415.

Dr. Bhawna Kohli, Pradeep Kumar, Prashant Saraswat

Immunization Coverage; Vaccine Effectiveness; Childhood Vaccination; Public Health Immunization Programs; Vaccine Uptake; Digital Health Interventions.

Immunisation programmes represent one of the most effective interventions in global public health with regard to preventing infectious diseases and mitigating child mortality. Despite significant progress in global vaccination campaigns, disparities in immunisation rates continue due to socioeconomic disparities, healthcare access barriers, and vaccine hesitancy. This cross-sectional analytical study evaluates immunisation coverage and vaccine effectiveness among children using data collected on 268 children between 0–15 years of age visiting primary healthcare centres and immunisation clinics. Data on vaccination status, parental knowledge, healthcare access, and digital health interventions were collected through structured surveys and clinical immunisation history. Descriptive statistics, one-way ANOVA, and logistic regression determined variables contributing to vaccine uptake and efficacy. Findings indicate that good immunisation coverage is strongly linked with increased healthcare access (F=5.12, p=0.006), parental education (F=6.28, p=0.002), and systematic digital reminder systems (F=6.85, p=0.001). Digital health-based interventions including text-message reminders and electronic immunisation registries significantly increased vaccination compliance. Low parental education (β=0.42, p=0.002) and absence of reminder systems (β=0.39, p=0.003) were the strongest predictors of incomplete immunisation. Coverage gaps persist among groups with restricted healthcare access and lower socioeconomic status. The study highlights the paramount role of community-based health education, digital monitoring tools, and stronger immunisation infrastructure in increasing vaccine coverage and population health outcomes.

[1] Bielicki, J. A., Achermann, R., & Berger, C. (2012). Timing of measles immunization and effective population vaccine coverage. Pediatrics, 130(3), e600–e606.
[2] Carpiano, R. M., Polonijo, A. N., Gilbert, N., Cantin, L., & Dubé, E. (2019). Socioeconomic status differences in parental immunization attitudes and child immunization in Canada. Preventive Medicine, 123, 278–287.
[3] 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.
[4] Costantino, C., Casuccio, A., & Restivo, V. (2020). Vaccination and vaccine effectiveness: A commentary. Vaccines, 8(3), 545.
[5] Devi, M., Manokaran, D., Sehgal, R. K., Shariff, S. A., & Vettriselvan, R. (2025). Precision Medicine, Personalized Treatment, and Network-Driven Innovations: Transforming Healthcare With AI. In AI for Large Scale Communication Networks (pp. 303–322). IGI Global.
[6] Elkin, N., Mohammed, A. K., Kılınçel, Ş., Soydan, A. M., Tanrıver, S. Ç., Çelik, Ş., & Ranganathan, M. (2025). Mental health literacy and happiness among university students: A social work perspective to promoting well-being. Frontiers in Psychiatry, 16, 1541316.
[7] Fairbrother, G., Freed, G. L., & Thompson, J. W. (2000). Measuring immunization coverage. American Journal of Preventive Medicine, 19(3), 78–88.
[8] Giannone, G., Giuliano, A. R., Bandini, M., Marandino, L., Raggi, D., Earle, W., & Necchi, A. (2022). HPV vaccination and HPV-related malignancies: impact, strategies and optimizations toward global immunization coverage. Cancer Treatment Reviews, 111, 102467.
[9] Markowitz, L. E., Drolet, M., Perez, N., Jit, M., & Brisson, M. (2018). Human papillomavirus vaccine effectiveness by number of doses: systematic review of data from national immunization programs. Vaccine, 36(32), 4806–4815.
[10] Odone, A., Ferrari, A., Spagnoli, F., Visciarelli, S., Shefer, A., Pasquarella, C., & Signorelli, C. (2015). Effectiveness of interventions that apply new media to improve vaccine uptake and vaccine coverage: a systematic review. Human Vaccines & Immunotherapeutics, 11(1), 72–82.
[11] Placzek, H., & Madoff, L. C. (2011). The use of immunization registry-based data in vaccine effectiveness studies. Vaccine, 29(3), 399–411.
[12] Rand, C. M., Brill, H., Albertin, C., Humiston, S. G., Schaffer, S., Shone, L. P., & Szilagyi, P. G. (2015). Effectiveness of centralized text message reminders on human papillomavirus immunization coverage for publicly insured adolescents. Journal of Adolescent Health, 56(5), S17–S20.
[13] 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.
[14] Reifferscheid, L., Kiely, M. S., Lin, M. S. N., Libon, J., Kennedy, M., & MacDonald, S. E. (2023). Effectiveness of hospital-based strategies for improving childhood immunization coverage: A systematic review. Vaccine, 41(36), 5233–5244.
[15] 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.
[16] Shefer, A., Briss, P., Rodewald, L., Bernier, R., Strikas, R., Yusuf, H., & Hinman, A. R. (1999). Improving immunization coverage rates: an evidence-based review of the literature. Epidemiologic Reviews, 21(1), 96–142.
[17] Shim, E., & Galvani, A. P. (2012). Distinguishing vaccine efficacy and effectiveness. Vaccine, 30(47), 6700–6705.
[18] Siddiqui, F. A., Padhani, Z. A., Salam, R. A., Aliani, R., Lassi, Z. S., Das, J. K., & Bhutta, Z. A. (2022). Interventions to improve immunization coverage among children and adolescents: a meta-analysis. Pediatrics, 149(Supplement 6), e2021053852D.
[19] Uskun, E., Uskun, S. B., Uysalgenc, M., & Yagız, M. (2008). Effectiveness of a training intervention on immunization to increase knowledge of primary healthcare workers and vaccination coverage rates. Public Health, 122(9), 949–958.
[20] Vakili, R., Ghazizadeh Hashemi, A., Khademi, G., Ajilian Abbasi, M., & Saeidi, M. (2015). Immunization coverage in WHO regions: a review article. Journal of Pediatric Perspectives, 3(2.1), 111–118.
[21] 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.

Dr. Hiru Navaney, Dr. Nasima Khatoon, Neha

Pediatric Nutrition; Growth Monitoring; Anthropometric Assessment; Child Development; Malnutrition; Digital Health Monitoring.

Nutritional assessment and growth monitoring provide essential information about ontogenetic changes and the overall health of paediatric patients. Early diagnosis of nutritional deficiencies and growth disruptions allows clinicians to treat individuals in a timely fashion, alleviating the risk of developing chronic developmental complications. Despite global improvements, malnutrition, stunted growth, and micronutrient insufficiencies remain serious public health challenges complicating the health of millions of children across geographic locations. This cross-sectional analytical study assessed 228 children between one and twelve years of age in paediatric clinical environments. Main anthropometric indices including height-for-age, weight-for-age, and body mass index were measured and supplemented by clinical nutritional assessment and dietary intake data. Other covariates included parental socioeconomic status, healthcare access, and current growth monitoring regimens. ANOVA and multivariate regression models explained associations between nutritional indicators and growth outcomes. Findings confirm that anthropometric measures remain robust predictors of nutritional status and growth patterns. Children from lower socioeconomic backgrounds and with limited healthcare access showed greater rates of undernutrition and delayed growth. Systematic growth monitoring and antecedent nutritional interventions showed substantial gains in developmental processes. Emerging digital health and automated monitoring systems show significant potential in improving accuracy and depth of paediatric nutritional evaluations.

[1] Ashifa, K. M. (2021). Analysis on the determinants of health status among tribal communities. Journal of Cardiovascular Disease Research, 12(3), 531–534.
[2] Ashworth, A., Shrimpton, R., & Jamil, K. (2008). Growth monitoring and promotion: review of evidence of impact. Maternal & Child Nutrition, 4, 86–117.
[3] 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.
[4] de Arriba Muñoz, A., García Castellanos, M. T., Cajal, M. D., Beisti Ortego, A., Ruiz, I. M., & Labarta Aizpún, J. I. (2022). Automated growth monitoring app (GROWIN): a mobile Health tool to improve diagnosis and early management of growth and nutritional disorders in childhood. Journal of the American Medical Informatics Association, 29(9), 1508–1517.
[5] Devi, M., Manokaran, D., Sehgal, R. K., Shariff, S. A., & Vettriselvan, R. (2025). Precision Medicine, Personalized Treatment, and Network-Driven Innovations: Transforming Healthcare With AI. In AI for Large Scale Communication Networks (pp. 303–322). IGI Global.
[6] Elkin, N., Mohammed, A. K., Kılınçel, Ş., Soydan, A. M., Tanrıver, S. Ç., Çelik, Ş., & Ranganathan, M. (2025). Mental health literacy and happiness among university students: A social work perspective to promoting well-being. Frontiers in Psychiatry, 16, 1541316.
[7] Green Corkins, K., & Teague, E. E. (2017). Pediatric nutrition assessment: anthropometrics to zinc. Nutrition in Clinical Practice, 32(1), 40–51.
[8] Hall, D. M. (2000). Growth monitoring. Archives of Disease in Childhood, 82(1), 10–15.
[9] Hong, L. (2025). Assessing and Monitoring Children’s Nutritional Status. In Healthy Food for Children (pp. 61–79). Springer Nature Singapore.
[10] Leroy, J. L., Brander, R. L., Frongillo, E. A., Larson, L. M., Ruel, M. T., & Avula, R. (2025). Perspective: Can Growth Monitoring and Promotion Accurately Diagnose or Screen for Inadequate Growth of Individual Children? Advances in Nutrition, 16(3), 100367.
[11] Lotfi, M. (1988). Growth monitoring: a brief literature review of current knowledge. Food and Nutrition Bulletin, 10(4), 1–8.
[12] Maqbool, A., Olsen, I. E., & Stallings, V. A. (2008). Clinical assessment of nutritional status. Nutrition in Pediatrics: Basic Science and Clinical Applications (4th ed., pp. 6–7).
[13] Mascarenhas, M. R., Zemel, B., & Stallings, V. A. (1998). Nutritional assessment in pediatrics. Nutrition, 14(1), 105–115.
[14] Panpanich, R., & Garner, P. (1999). Growth monitoring in children. Cochrane Database of Systematic Reviews, 4.
[15] 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.
[16] Sampaio, A. D. S., Epifanio, M., Costa, C. A. D., Bosa, V. L., Benedetti, F. J., Sarria, E. E., & Mattiello, R. (2018). Evidence on nutritional assessment techniques and parameters used to determine the nutritional status of children and adolescents: systematic review. Ciência & Saúde Coletiva, 23(12), 4209–4219.
[17] Scott, B. J., Artman, H., & Jeor, S. T. S. (1993). Growth assessment in children: a review. Topics in Clinical Nutrition, 8(1), 5–31.
[18] Secker, D. J., & Jeejeebhoy, K. N. (2007). Subjective global nutritional assessment for children. The American Journal of Clinical Nutrition, 85(4), 1083–1089.
[19] Sentongo, T. (2019). A new approach to comprehensive growth and nutrition assessment in children. Pediatric Annals, 48(11), e425–e433.
[20] 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.
[21] 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.
[22] Yap, F., Lee, Y. S., & Aw, M. M. H. (2018). Growth assessment and monitoring during childhood. Annals of the Academy of Medicine Singapore, 47(4), 149–155.
[23] Zsakai, A., Annar, D., Koronczai, B., Molnar, K., Varro, P., Toth, E., & Muzsnai, A. (2023). A new monitoring system for nutritional status assessment in children at home. Scientific Reports, 13(1), 4155.

Dr. Vishal Garg, Yashswi Chauhan, Ajay Kumar

Neonatal Intensive Care Unit; Neonatal Survival Outcomes; Premature Infants; Neonatal Mortality; Neonatal Critical Care; Neonatal Technology.

Neonatal intensive care units (NICUs) represent a critical node in improving the survival of premature and critically ill infants. In recent decades, neonatology has witnessed significant improvements in respiratory support systems, infection control measures, neuroprotective therapies, and advanced digital health surveillance systems, radically changing how high-risk neonates are managed. Despite these achievements, neonatal mortality remains a significant global health challenge, particularly in areas where access to specialised care is limited. This study explores how these developments impact survival of high-risk newborns in tertiary care hospitals. An analytical hospital-based study targeted 212 neonates admitted to NICU over twelve months. Clinical records and monitoring systems were searched to extract data on gestational age, birth weight, respiratory support modalities, neonatal infection incidence, duration of NICU stay, and survival outcomes. Statistical analysis using descriptive statistics, ANOVA, and logistic regression identified important clinical and technological factors related to neonatal survival. Results demonstrate that prompt respiratory support, advanced neonatal monitoring, timely infection treatment, and neonatal-specific care guidelines contribute significantly to survival rates of premature and critically ill babies. Neonates receiving CPAP support showed survival rates of 86.5%, while those receiving comprehensive monitoring and early intervention demonstrated 88.2% survival. Infection control measures and multidisciplinary care delivery further reduced complications and accelerated recovery.

[1] Allen, M. C. (2002). Preterm outcomes research: a critical component of neonatal intensive care. Mental Retardation and Developmental Disabilities Research Reviews, 8(4), 221–233.
[2] Battin, M., Ling, E. W., Whitfield, M. F., Mackinnon, M., & Effer, S. B. (1998). Has the outcome for extremely low gestational age (ELGA) infants improved following recent advances in neonatal intensive care? American Journal of Perinatology, 15(8), 469–477.
[3] Biban, P., Marlow, N., Te Pas, A. B., Fanaroff, A. A., & Jobe, A. H. (2021). Advances in neonatal critical care: pushing at the boundaries and connecting to long-term outcomes. Critical Care Medicine, 49(12), 2003–2016.
[4] 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.
[5] Crilly, C. J., Haneuse, S., & Litt, J. S. (2021). Predicting the outcomes of preterm neonates beyond the neonatal intensive care unit: what are we missing? Pediatric Research, 89(3), 426–445.
[6] Devi, M., Manokaran, D., Sehgal, R. K., Shariff, S. A., & Vettriselvan, R. (2025). Precision Medicine, Personalized Treatment, and Network-Driven Innovations: Transforming Healthcare With AI. In AI for Large Scale Communication Networks (pp. 303–322). IGI Global.
[7] Elkin, N., Mohammed, A. K., Kılınçel, Ş., Soydan, A. M., Tanrıver, S. Ç., Çelik, Ş., & Ranganathan, M. (2025). Mental health literacy and happiness among university students: A social work perspective to promoting well-being. Frontiers in Psychiatry, 16, 1541316.
[8] Hack, M. (2013). The outcome of neonatal intensive care. In Klaus and Fanaroff’s Care of the High-Risk Neonate (pp. 525–534).
[9] Johnston, M. V., Fatemi, A., Wilson, M. A., & Northington, F. (2011). Treatment advances in neonatal neuroprotection and neurointensive care. The Lancet Neurology, 10(4), 372–382.
[10] Noble, L. (2003). Developments in neonatal technology continue to improve infant outcomes. Pediatric Annals, 32(9), 595–603.
[11] Rajak, A. (2025). Advancements in neonatal care: innovations in early diagnosis and treatment. Journal of Advanced Healthcare Research in Pediatrics, 1(1), 01–06.
[12] 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.
[13] Richardson, D. K., Gray, J. E., Gortmaker, S. L., Goldmann, D. A., Pursley, D. M., & McCormick, M. C. (1998). Declining severity adjusted mortality: evidence of improving neonatal intensive care. Pediatrics, 102(4), 893–899.
[14] Shah, V., Warre, R., & Lee, S. K. (2013). Quality improvement initiatives in neonatal intensive care unit networks: achievements and challenges. Academic Pediatrics, 13(6), S75–S83.
[15] Shane, A. L., & Stoll, B. J. (2014). Neonatal sepsis: progress towards improved outcomes. Journal of Infection, 68, S24–S32.
[16] 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.
[17] Tudor, S., Bhatia, R., Liem, M., Wani, T. A., Boyd, J., & Raza Khan, U. (2025). Opportunities and Challenges of Using Artificial Intelligence in Predicting Clinical Outcomes and Length of Stay in Neonatal Intensive Care Units: Systematic Review. Journal of Medical Internet Research, 27, e63175.
[18] 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.
[19] Vidyasagar, D. (2002). A global view of advancing neonatal health and survival. Journal of Perinatology, 22(7), 513–515.
[20] Wilson-Costello, D. (2007). Is there evidence that long-term outcomes have improved with intensive care? Seminars in Fetal and Neonatal Medicine, 12(5), 344–354.
[21] Woelile, T. A., Kibret, G. T., Workie, H. M., Amare, A. T., Tigabu, A., Aynalem, Y. A., & Birlie, T. A. (2021). Survival status and predictors of mortality among low-birth-weight neonates admitted to the neonatal intensive care unit. Pediatric Health, Medicine and Therapeutics, 451–466.

Dr. Yogesh Goel, Sangeeta Sharma, Dipesh Kumar

Pediatric Morbidity; Child Mortality; Social Determinants of Health; Healthcare Accessibility; Pediatric Epidemiology; Child Health Outcomes

Pediatric morbidity and mortality remain vital indicators of population health and healthcare system effectiveness. Despite major progress in child survival over recent decades, preventable diseases and deaths continue in most settings due to multifaceted socioeconomic, environmental, and healthcare-related determinants. This cross-sectional study examines determinants of morbidity and mortality patterns among 236 paediatric patients admitted to tertiary healthcare facilities over twelve months. Variables studied included demographic characteristics, nutritional status, parental educational attainment, household income, healthcare accessibility, environmental sanitation indicators, and clinical diagnosis. Descriptive statistics, ANOVA, and logistic regression analyses identified important predictors of morbidity and mortality. Findings revealed high correlations among malnutrition, late access to care, low parental education, and poor sanitation with high paediatric morbidity rates. Neonatal complications (OR=2.96), severe malnutrition (OR=2.84), and delayed hospital admission (OR=2.17) were the leading mortality predictors. Socioeconomic differences were significant in producing unbalanced health outcomes. These results highlight the urgency of integrated child health interventions combining medical, environmental, and social improvements. Enhancement of primary healthcare infrastructure, maternal education, nutrition programmes, and preventive services can significantly reduce paediatric morbidity and mortality.

[1] Awasthi, S., & Agarwal, S. (2003). Determinants of childhood mortality and morbidity in urban slums in India. Indian Pediatrics, 40(12), 1145–1161.
[2] Beck, A. F., Tschudy, M. M., Coker, T. R., Mistry, K. B., Cox, J. E., Gitterman, B. A., & Fierman, A. H. (2016). Determinants of health and pediatric primary care practices. Pediatrics, 137(3).
[3] Bicego, G. T. (1990). Trends, age patterns, and determinants of childhood mortality in Haiti. The Johns Hopkins University.
[4] 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.
[5] Chakrabarti, A. (2012). Determinants of child morbidity and factors governing utilization of child health care: evidence from rural India. Applied Economics, 44(1), 27–37.
[6] Das Gupta, M. (1990). Death clustering, mothers’ education and the determinants of child mortality in rural Punjab, India. Population Studies, 44(3), 489–505.
[7] Devi, M., Manokaran, D., Sehgal, R. K., Shariff, S. A., & Vettriselvan, R. (2025). Precision Medicine, Personalized Treatment, and Network-Driven Innovations: Transforming Healthcare With AI. In AI for Large Scale Communication Networks (pp. 303–322). IGI Global.
[8] Dietz, W. H. (1998). Childhood weight affects adult morbidity and mortality. The Journal of Nutrition, 128(2), 411S–414S.
[9] Elkin, N., Mohammed, A. K., Kılınçel, Ş., Soydan, A. M., Tanrıver, S. Ç., Çelik, Ş., & Ranganathan, M. (2025). Mental health literacy and happiness among university students: A social work perspective to promoting well-being. Frontiers in Psychiatry, 16, 1541316.
[10] Hobcraft, J. N., McDonald, J. W., & Rutstein, S. O. (1985). Demographic determinants of infant and early child mortality: a comparative analysis. Population Studies, 39(3), 363–385.
[11] Islam, M., Usman, M., Mahmood, A., Abbasi, A. A., & Song, O. Y. (2020). Predictive analytics framework for accurate estimation of child mortality rates for Internet of Things enabled smart healthcare systems. International Journal of Distributed Sensor Networks, 16(5), 1550147720928897.
[12] Jofiro, G., Jemal, K., Beza, L., & Bacha Heye, T. (2018). Prevalence and associated factors of pediatric emergency mortality at Tikur Anbessa specialized tertiary hospital. BMC Pediatrics, 18(1), 316.
[13] Mosley, W. H., & Chen, L. C. (1984). An analytical framework for the study of child survival in developing countries. Population and Development Review, 10, 25–45.
[14] Park, M. B., Hwang, B. D., & Nam, Y. H. (2024). Investigating the role of social determinants in child mortality and life expectancy: longitudinal analysis of 200 countries from 1990 to 2021. Child Indicators Research, 17(4), 1871–1889.
[15] 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.
[16] 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.
[17] Strong, K. L., Pedersen, J., Johansson, E. W., Cao, B., Diaz, T., Guthold, R., & Liu, L. (2021). Patterns and trends in causes of child and adolescent mortality 2000–2016: setting the scene for child health redesign. BMJ Global Health, 6(3), e004760.
[18] Trinidad, S., & Kotagal, M. (2022). Social determinants of health as drivers of inequities in pediatric injury. Seminars in Pediatric Surgery, 31(5), 151221.
[19] Trinidad, S., & Kotagal, M. (2023). Socioeconomic factors and pediatric injury. Current Trauma Reports, 9(2), 47–55.
[20] Tsegaye, H., Demelash, A., Aklilu, D., & Girma, B. (2023). Determinants of pediatrics emergency mortality at comprehensive specialized hospitals of South Ethiopia, 2022: unmatched case-control study. BMC Pediatrics, 23(1), 192.
[21] 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.
[22] Yassin, K. M. (2000). Indices and sociodemographic determinants of childhood mortality in rural Upper Egypt. Social Science & Medicine, 51(2), 185–197.

Liswaniso Lyato Charity, Dr. Siyumbwa Costa

Drug Abuse; Primary School Learners; Senanga District; Zambia; Prevention; AI Health Promotion; Substance Use; Digital Intervention.

Drug abuse among primary school learners represents a growing public health and educational challenge in sub-Saharan Africa, with documented consequences for cognitive development, academic performance, social behaviour, and long-term health outcomes. In Senanga District, Western Province, Zambia, primary school teachers and administrators report increasing encounters with substance use among learners as young as ten years old. This article investigates the causes and effects of drug abuse among primary school learners in Senanga District, situating local findings within global scholarship on adolescent substance use prevention, AI-powered health promotion, and community-based intervention models. Drawing on a descriptive survey employing qualitative and quantitative methods, the study identifies peer influence, family dysfunction, poverty, emotional distress, and community drug availability as primary causal factors. Academic underperformance, absenteeism, behavioural difficulties, health deterioration, and school dropout are documented as key effects. The article argues that AI-driven health literacy platforms, digital peer education tools, and community-based digital support networks offer promising complementary interventions for drug abuse prevention in primary school contexts. Policy recommendations are presented.

[1] Akila, V., Prabhu, G., Akila, R., & Swadhi, R. (2025). Performance metrics in blockchain-enabled AIML for cognitive IoT in large-scale networks. In AI for large scale communication networks (pp. 265–288). IGI Global Scientific Publishing.
[2] Arockia, V. J., Vettriselvan, R., Rajesh, D., Velmurugan, P. R. R., & Cheelo, C. (2025). Leveraging AI and learning analytics for enhanced distance learning. In AI and learning analytics in distance learning (pp. 179–206). IGI Global Scientific Publishing.
[3] Ashifa, K. M. (2019). Developmental initiatives for persons with disabilities. Indian Journal of Public Health Research & Development, 10(12), 1257–1261.
[4] Ashifa, K. M. (2020a). Effect of substance abuse on physical health of adolescents. European Journal of Molecular & Clinical Medicine, 7(2), 3155–3160.
[5] Ashifa, K. M. (2020b). Physical health hazards of schizophrenia patients. Systematic Reviews in Pharmacy, 11(12), 1848–1850.
[6] Ashifa, K. M. (2021a). Analysis on the determinants of health status among tribal communities. Journal of Cardiovascular Disease Research, 12(3), 531–534.
[7] Ashifa, K. M. (2021b). Health status of primitive tribal women in India. Journal of Cardiovascular Disease Research, 12(5), 772.
[8] 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.
[9] 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.
[10] Devi, M., Manokaran, D., Sehgal, R. K., Shariff, S. A., & Vettriselvan, R. (2025). Precision medicine, personalized treatment, and network-driven innovations. In AI for large scale communication networks (pp. 303–322). IGI Global.
[11] Elkin, N., Mohammed, A. K., Kılınçel, Ş., Soydan, A. M., Tanrıver, S. Ç., Çelik, Ş., & Ranganathan, M. (2025). Mental health literacy and happiness among university students. Frontiers in Psychiatry, 16, 1541316.
[12] Gayathri, R. K., Vettriselvan, R., Rajesh, D., Balakrishnan, R., Kumar, R., & Kavitha, J. (2025a). 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).
[13] Gayathri, R. K., Vettriselvan, R., Rajesh, D., Balakrishnan, R., Kumar, R., & Kavitha, J. (2025b). Strategic role of human resource management in enhancing occupational health and safety practices. Texila International Journal of Public Health, 13(2).
[14] 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.
[15] Kariveliparambil, A., Rasi, R. A., Ahmad, M. S., Öztaş, N., & Ayan, F. S. (2026a). Evolving social capital in indigenous communities. Journal of Social Service Research, 52(1), 147–166.
[16] Kariveliparambil, A., R A, R., Ahmad, M. S., Ramesh, S., & Kuriakose, A. (2026b). Invisible burdens of platform work. International Journal of Qualitative Studies on Health and Well-Being, 21(1).
[17] Kombo, D. K., & Tromp, D. L. A. (2014). Proposal and thesis writing: An introduction. Paulines Publications Africa.
[18] Meena, G., Vettriselvan, R., Rajesh, D., & Velmurugan, P. R. (2025). Diversity and inclusion: Harnessing the power of inclusivity for business success. In Security and strategy models for key-solving institutional frameworks (pp. 203–234). IGI Global Scientific Publishing.
[19] Mohanbabu, S., & Vettriselvan, R. (2025a). Focusing supply chain and container terminal challenges. International Journal of Procurement Management, 24(1), 92–114.
[20] Mohanbabu, S., & Vettriselvan, R. (2025b). Will machine learning resolve the issues in container management. International Journal of Process Management and Benchmarking, 20(4), 559–575.
[21] Orodho, J. A., & Kombo, D. K. (2012). Research methods. Kenyatta University Press.
[22] Rajeswari, M., Rohini, V., Sathya Aarthi, R., Rameshkumaar, V. P., & Arul Krishnan, S. (2026). Blockchain 2.0 for secure, transparent, and autonomous logistics systems. In R. Vettriselvan & N. Suresh (Eds.), Intelligent motion control for human-centered systems (pp. 233–258). IGI Global Scientific Publishing.
[23] 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.
[24] Rasi, R. A., & Ashifa, K. M. (2019). Role of community-based programmes for active ageing. Indian Journal of Public Health Research & Development, 10(12).
[25] Shanthi, H. J., Gokulakrishnan, A., Sharma, S., Deepika, R., & Swadhi, R. (2025). Leveraging artificial intelligence for enhancing urban health. In Nexus of AI, climatology, and urbanism for smart cities (pp. 275–306). IGI Global.
[26] Swadhi, R., Gayathri, K., Suresh, N. V., Catherine, S., & Velmurugan, P. R. (2025a). Leveraging machine learning for enhanced patient engagement and outcomes. In Impact of digital transformation on business growth and performance (pp. 313–340). IGI Global Scientific Publishing.
[27] Swadhi, R., Velmurugan, P. R., Gayathri, K., & Catherine, S. (2025b). Evolving critical themes in advanced human resource management. In Critical aspects in advanced human resource management (pp. 75–102). IGI Global Scientific Publishing.
[28] Vasantha, S., Swadhi, R., Gayathri, K., Selvalakshmi, V., & UmaDevi, A. (2025). Fostering personalized learning and achieving equity in education. In Transforming education with AI-powered personalized learning (pp. 201–236). IGI Global Scientific Publishing.
[29] Venice, J. A., Arivazhagan, D., Suman, N., Shanthi, H. J., & Swadhi, R. (2025a). Recommendation systems and content personalization. In AI for large scale communication networks (pp. 323–348). IGI Global Scientific Publishing.
[30] Venice, J. A., Vettriselvan, R., Jain, S., Madusudanan, K., & Aarthy, C. C. J. (2025b). Performance evaluation and metrics in blockchain powered AI/ML. In Transforming education with AI-powered personalized learning (pp. 143–178). IGI Global Scientific Publishing.
[31] Venice, J. A., Vettriselvan, R., Rajesh, D., Suresh, N. V., & Abirami, P. (2025c). Enabling personalized learning and adaptive systems through strategic management. In Bridging academia and industry through cloud integration in education (pp. 49–72). IGI Global Scientific Publishing.
[32] Venice, J. A., Vettriselvan, R., Rajesh, D., Xavier, P., & Shanthi, H. J. (2025d). Optimizing performance metrics in blockchain-enabled AI/ML data analytics. In Enhancing automated decision-making through AI (pp. 97–122). IGI Global.
[33] Venice, J. A., Sripathi, S. K., & Moonga, B. (2025e). Social deviance and the influence of internet exposure. ASET Journal of Management Science, 4(SI-1).
[34] Venice, J. A. A., Jio, W., Kant, S., Sharda, S., & Mittal, S. (2025f). Ethical leadership effect on the regulation of AI in cyber security. In Ethical challenges of AI and warfare (pp. 133–152). IGI Global Scientific Publishing.
[35] Venice, J. A. A., Muthuraman, M., Kant, S., & Mittal, S. (2026). Community engagement effect on school leadership through digital volunteerism. In Strengthening community engagement and school leadership through digital volunteerism (pp. 85–114). IGI Global Scientific Publishing.
[36] Vettriselvan, R. (2025). Harnessing innovation and digital marketing in the era of industry 5.0. In The future of small business in industry 5.0 (pp. 163–186). IGI Global.
[37] 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.
[38] Vettriselvan, R., & Rajan FSA, A. J. (2019). Occupational health issues faced by women in spinners. Indian Journal of Public Health Research & Development, 10(1).
[39] Vettriselvan, R., Deepan, A., Jaiswani, G., Balakrishnan, A., & Sakthivel, R. (2025a). Health consequences of early marriage. In Social, political, and health implications of early marriage (pp. 189–212). IGI Global.
[40] Vettriselvan, R., Velmurugan, P. R., Varshney, K. R., EP, J., & Deepika, R. (2025b). Health impacts of smartphone and internet addictions across age groups. In Impacts of digital technologies across generations (pp. 187–210). IGI Global.
[41] Vettriselvan, R., Velmurugan, P. R., Suresh, N. V., & Catherine, S. (2025c). Strategies, best practices, and pitfalls in the era of digital transformation. In Impact of digital transformation on business growth and performance (pp. 67–98). IGI Global Scientific Publishing.
[42] Vettriselvan, R., Selvi, K., Kumar, A. S., Ranjani, R. D., & Varshney, K. R. (2025d). Ranking methodologies: Criteria and controversies in global higher education. In Global university ranking systems (pp. 109–140). IGI Global Scientific Publishing.
[43] Vettriselvan, R., Gokuldas, P. G., & Sambamoorthy, N. (2025e). Designing language materials to motivate, engage, and empower learners. In Exploring the psychology of language materials development (pp. 279–302). IGI Global Scientific Publishing.
[44] Vettriselvan, R., Ramya, R., Selvalakshmi, V., Jyothi, P., & Velmurugan, P. R. (2026a). Empowering patients through knowledge: Educational strategies in rehabilitation. In Holistic approaches to health recovery (pp. 263–290). IGI Global Scientific Publishing.
[45] Vettriselvan, R., Velmurugan, P. R., Savariapitchai, M., & Swadhi, R. (2026b). AI and international volunteering: Redefining global engagement in the digital age. In Impacts of AI on international volunteering (pp. 1–24). IGI Global Scientific Publishing.
[46] Vijayalakshmi, M., Subramani, A. K., Vettriselvan, R., Catherin, T. C., & Deepika, R. (2025a). Sustainability and responsibility in the digital era. In Digital citizenship and building a responsible online presence (pp. 285–306). IGI Global.
[47] Vijayalakshmi, M., Subramani, A. K., Vettriselvan, R., Velmurugan, P. R., & Hasine, J. (2025b). Strategic collaborations in medical innovation and AI-driven globalization. In Navigating strategic partnerships for sustainable startup growth (pp. 85–110). IGI Global.
[48] Vinodh, N., Subramani, A. K., & Vettriselvan, R. (2026a). Navigating ethics, society, and governance in the digital age. In Ethics, justice, and governance in the age of AI and digital societies (pp. 1–26). IGI Global Scientific Publishing.
[49] Vinodh, N., Subramani, A. K., & Vettriselvan, R. (2026b). Transforming the future of management and medical education. In AI education strategies for future-proofing curriculum design (pp. 459–476). IGI Global Scientific Publishing.
[50] 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.

Lackson Muyonkoma Mudeda, Dr. Siyumbwa Costa

Educational Technology; Academic Performance; Teaching Effectiveness; Kalabo District; Zambia; Artificial Intelligence; Digital Transformation.

The integration of technology into educational institutions has become a defining feature of twenty-first-century schooling, reshaping instructional practices, learner engagement, and academic outcomes globally. However, in resource-constrained rural contexts such as Kalabo District in Zambia’s Western Province, the relationship between technology access and academic performance remains complex, uneven, and empirically underexplored. This article investigates the impact of technology on student academic performance and teaching effectiveness in three selected primary schools in Kalabo District, contextualising local findings within global scholarship on artificial intelligence, adaptive learning, blockchain credentialing, and digital transformation in education. Drawing on a descriptive survey of teachers and pupils, findings reveal that technology integration where available significantly enhances learner engagement, critical thinking, and content retention, while teaching effectiveness improves through digital resource access and lesson planning support. However, infrastructure deficits, teacher digital literacy gaps, and inequitable device access constrain these benefits. The article argues that AI-powered adaptive platforms and offline-capable digital tools offer contextually appropriate pathways for advancing technology-enhanced teaching in remote Zambian schools. Policy recommendations are presented.

[1] Akila, V., Prabhu, G., Akila, R., & Swadhi, R. (2025). Performance metrics in blockchain-enabled AIML for cognitive IoT in large-scale networks. In AI for large scale communication networks (pp. 265–288). IGI Global Scientific Publishing.
[2] Arockia, V. J., Vettriselvan, R., Rajesh, D., Velmurugan, P. R. R., & Cheelo, C. (2025). Leveraging AI and learning analytics for enhanced distance learning. In AI and learning analytics in distance learning (pp. 179–206). IGI Global Scientific Publishing.
[3] Ashifa, K. M. (2019). Developmental initiatives for persons with disabilities. Indian Journal of Public Health Research & Development, 10(12), 1257–1261.
[4] Ashifa, K. M. (2020a). Effect of substance abuse on physical health of adolescents. European Journal of Molecular & Clinical Medicine, 7(2), 3155–3160.
[5] Ashifa, K. M. (2020b). Physical health hazards of schizophrenia patients. Systematic Reviews in Pharmacy, 11(12), 1848–1850.
[6] Ashifa, K. M. (2021a). Analysis on the determinants of health status among tribal communities. Journal of Cardiovascular Disease Research, 12(3), 531–534.
[7] Ashifa, K. M. (2021b). Health status of primitive tribal women in India. Journal of Cardiovascular Disease Research, 12(5), 772.
[8] 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.
[9] 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.
[10] Devi, M., Manokaran, D., Sehgal, R. K., Shariff, S. A., & Vettriselvan, R. (2025). Precision medicine, personalized treatment, and network-driven innovations. In AI for large scale communication networks (pp. 303–322). IGI Global.
[11] Elkin, N., Mohammed, A. K., Kılınçel, Ş., Soydan, A. M., Tanrıver, S. Ç., Çelik, Ş., & Ranganathan, M. (2025). Mental health literacy and happiness among university students. Frontiers in Psychiatry, 16, 1541316.
[12] Gayathri, R. K., Vettriselvan, R., Rajesh, D., Balakrishnan, R., Kumar, R., & Kavitha, J. (2025a). 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).
[13] Gayathri, R. K., Vettriselvan, R., Rajesh, D., Balakrishnan, R., Kumar, R., & Kavitha, J. (2025b). Strategic role of human resource management in enhancing occupational health and safety practices. Texila International Journal of Public Health, 13(2).
[14] 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.
[15] Kariveliparambil, A., Rasi, R. A., Ahmad, M. S., Öztaş, N., & Ayan, F. S. (2026a). Evolving social capital in indigenous communities. Journal of Social Service Research, 52(1), 147–166.
[16] Kariveliparambil, A., R A, R., Ahmad, M. S., Ramesh, S., & Kuriakose, A. (2026b). Invisible burdens of platform work. International Journal of Qualitative Studies on Health and Well-Being, 21(1).
[17] Kombo, D. K., & Tromp, D. L. A. (2014). Proposal and thesis writing: An introduction. Paulines Publications Africa.
[18] Meena, G., Vettriselvan, R., Rajesh, D., & Velmurugan, P. R. (2025). Diversity and inclusion: Harnessing the power of inclusivity for business success. In Security and strategy models for key-solving institutional frameworks (pp. 203–234). IGI Global Scientific Publishing.
[19] Mohanbabu, S., & Vettriselvan, R. (2025a). Focusing supply chain and container terminal challenges. International Journal of Procurement Management, 24(1), 92–114.
[20] Mohanbabu, S., & Vettriselvan, R. (2025b). Will machine learning resolve the issues in container management. International Journal of Process Management and Benchmarking, 20(4), 559–575.
[21] Orodho, J. A., & Kombo, D. K. (2012). Research methods. Kenyatta University Press.
[22] Rajeswari, M., Rohini, V., Sathya Aarthi, R., Rameshkumaar, V. P., & Arul Krishnan, S. (2026). Blockchain 2.0 for secure, transparent, and autonomous logistics systems. In R. Vettriselvan & N. Suresh (Eds.), Intelligent motion control for human-centered systems (pp. 233–258). IGI Global Scientific Publishing.
[23] 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.
[24] Rasi, R. A., & Ashifa, K. M. (2019). Role of community-based programmes for active ageing. Indian Journal of Public Health Research & Development, 10(12).
[25] Shanthi, H. J., Gokulakrishnan, A., Sharma, S., Deepika, R., & Swadhi, R. (2025). Leveraging artificial intelligence for enhancing urban health. In Nexus of AI, climatology, and urbanism for smart cities (pp. 275–306). IGI Global.
[26] Swadhi, R., Gayathri, K., Suresh, N. V., Catherine, S., & Velmurugan, P. R. (2025a). Leveraging machine learning for enhanced patient engagement and outcomes. In Impact of digital transformation on business growth and performance (pp. 313–340). IGI Global Scientific Publishing.
[27] Swadhi, R., Velmurugan, P. R., Gayathri, K., & Catherine, S. (2025b). Evolving critical themes in advanced human resource management. In Critical aspects in advanced human resource management (pp. 75–102). IGI Global Scientific Publishing.
[28] Vasantha, S., Swadhi, R., Gayathri, K., Selvalakshmi, V., & UmaDevi, A. (2025). Fostering personalized learning and achieving equity in education. In Transforming education with AI-powered personalized learning (pp. 201–236). IGI Global Scientific Publishing.
[29] Venice, J. A., Arivazhagan, D., Suman, N., Shanthi, H. J., & Swadhi, R. (2025a). Recommendation systems and content personalization. In AI for large scale communication networks (pp. 323–348). IGI Global Scientific Publishing.
[30] Venice, J. A., Vettriselvan, R., Jain, S., Madusudanan, K., & Aarthy, C. C. J. (2025b). Performance evaluation and metrics in blockchain powered AI/ML. In Transforming education with AI-powered personalized learning (pp. 143–178). IGI Global Scientific Publishing.
[31] Venice, J. A., Vettriselvan, R., Rajesh, D., Suresh, N. V., & Abirami, P. (2025c). Enabling personalized learning and adaptive systems through strategic management. In Bridging academia and industry through cloud integration in education (pp. 49–72). IGI Global Scientific Publishing.
[32] Venice, J. A., Vettriselvan, R., Rajesh, D., Xavier, P., & Shanthi, H. J. (2025d). Optimizing performance metrics in blockchain-enabled AI/ML data analytics. In Enhancing automated decision-making through AI (pp. 97–122). IGI Global.
[33] Venice, J. A., Sripathi, S. K., & Moonga, B. (2025e). Social deviance and the influence of internet exposure. ASET Journal of Management Science, 4(SI-1).
[34] Venice, J. A. A., Jio, W., Kant, S., Sharda, S., & Mittal, S. (2025f). Ethical leadership effect on the regulation of AI in cyber security. In Ethical challenges of AI and warfare (pp. 133–152). IGI Global Scientific Publishing.
[35] Venice, J. A. A., Muthuraman, M., Kant, S., & Mittal, S. (2026). Community engagement effect on school leadership through digital volunteerism. In Strengthening community engagement and school leadership through digital volunteerism (pp. 85–114). IGI Global Scientific Publishing.
[36] Vettriselvan, R. (2025). Harnessing innovation and digital marketing in the era of industry 5.0. In The future of small business in industry 5.0 (pp. 163–186). IGI Global.
[37] 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.
[38] Vettriselvan, R., & Rajan FSA, A. J. (2019). Occupational health issues faced by women in spinners. Indian Journal of Public Health Research & Development, 10(1).
[39] Vettriselvan, R., Deepan, A., Jaiswani, G., Balakrishnan, A., & Sakthivel, R. (2025a). Health consequences of early marriage. In Social, political, and health implications of early marriage (pp. 189–212). IGI Global.
[40] Vettriselvan, R., Velmurugan, P. R., Varshney, K. R., EP, J., & Deepika, R. (2025b). Health impacts of smartphone and internet addictions across age groups. In Impacts of digital technologies across generations (pp. 187–210). IGI Global.
[41] Vettriselvan, R., Velmurugan, P. R., Suresh, N. V., & Catherine, S. (2025c). Strategies, best practices, and pitfalls in the era of digital transformation. In Impact of digital transformation on business growth and performance (pp. 67–98). IGI Global Scientific Publishing.
[42] Vettriselvan, R., Selvi, K., Kumar, A. S., Ranjani, R. D., & Varshney, K. R. (2025d). Ranking methodologies: Criteria and controversies in global higher education. In Global university ranking systems (pp. 109–140). IGI Global Scientific Publishing.
[43] Vettriselvan, R., Gokuldas, P. G., & Sambamoorthy, N. (2025e). Designing language materials to motivate, engage, and empower learners. In Exploring the psychology of language materials development (pp. 279–302). IGI Global Scientific Publishing.
[44] Vettriselvan, R., Ramya, R., Selvalakshmi, V., Jyothi, P., & Velmurugan, P. R. (2026a). Empowering patients through knowledge: Educational strategies in rehabilitation. In Holistic approaches to health recovery (pp. 263–290). IGI Global Scientific Publishing.
[45] Vettriselvan, R., Velmurugan, P. R., Savariapitchai, M., & Swadhi, R. (2026b). AI and international volunteering: Redefining global engagement in the digital age. In Impacts of AI on international volunteering (pp. 1–24). IGI Global Scientific Publishing.
[46] Vijayalakshmi, M., Subramani, A. K., Vettriselvan, R., Catherin, T. C., & Deepika, R. (2025a). Sustainability and responsibility in the digital era. In Digital citizenship and building a responsible online presence (pp. 285–306). IGI Global.
[47] Vijayalakshmi, M., Subramani, A. K., Vettriselvan, R., Velmurugan, P. R., & Hasine, J. (2025b). Strategic collaborations in medical innovation and AI-driven globalization. In Navigating strategic partnerships for sustainable startup growth (pp. 85–110). IGI Global.
[48] Vinodh, N., Subramani, A. K., & Vettriselvan, R. (2026a). Navigating ethics, society, and governance in the digital age. In Ethics, justice, and governance in the age of AI and digital societies (pp. 1–26). IGI Global Scientific Publishing.
[49] Vinodh, N., Subramani, A. K., & Vettriselvan, R. (2026b). Transforming the future of management and medical education. In AI education strategies for future-proofing curriculum design (pp. 459–476). IGI Global Scientific Publishing.
[50] 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.

Dr. Moushmi Gautam, Ketan Sharma, Dr. Supriya Maitiy

Fertility Preservation; Oncofertility; Oocyte Vitrification; Ovarian Tissue Cryopreservation; Sperm Cryopreservation; Assisted Reproductive Technology; Precision Medicine; Reproductive Autonomy; Reproductive Justice; Cryobiology; Regenerative Reproductive Medicine.

Fertility preservation has emerged as a leading field in contemporary reproductive medicine, driven by increasing cancer survival rates, delays in childbearing, gonadotoxic treatment protocols, and evolving societal values. Remarkable advances in cryopreservation, vitrification, ovarian tissue transplantation, and sperm preservation have expanded reproductive autonomy and clinical capabilities. This comprehensive analytical synthesis evaluates existing fertility preservation modalities for both female and male populations, examining laboratory innovations, precision medicine integration, assisted reproductive technology, ethical implications, and future translational challenges. Current modalities—oocyte vitrification, embryo cryopreservation, ovarian tissue cryopreservation, sperm banking, and experimental germline stem cell methods—are evaluated on the basis of efficacy, safety, accessibility, and long-term reproductive success. The ethical debate surrounding elective fertility preservation, reproductive justice, and age-related fertility decline is critically examined. This review highlights the urgent need for precise patient stratification, equitable access models, interdisciplinary coordination, and integration of emerging biomedical technologies to optimise fertility outcomes in contemporary reproductive care.

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[4] 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.
[5] Devi, M., Manokaran, D., Sehgal, R. K., Shariff, S. A., & Vettriselvan, R. (2025). Precision Medicine, Personalized Treatment, and Network-Driven Innovations: Transforming Healthcare With AI. In AI for Large Scale Communication Networks (pp. 303–322). IGI Global.
[6] Dolmans, M. M., & Manavella, D. D. (2019). Recent advances in fertility preservation. Journal of Obstetrics and Gynaecology Research, 45(2), 266–279.
[7] Dondorp, W. J., & De Wert, G. M. (2009). Fertility preservation for healthy women: ethical aspects. Human Reproduction, 24(8), 1779–1785.
[8] Donnez, J., & Dolmans, M. M. (2013). Fertility preservation in women. Nature Reviews Endocrinology, 9(12), 735–749.
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[10] Doungkamchan, C., & Orwig, K. E. (2021). Recent advances: Fertility preservation and fertility restoration options for males and females. Faculty Reviews, 10, 55.
[11] Elkin, N., Mohammed, A. K., Kılınçel, Ş., Soydan, A. M., Tanrıver, S. Ç., Çelik, Ş., & Ranganathan, M. (2025). Mental health literacy and happiness among university students: A social work perspective to promoting well-being. Frontiers in Psychiatry, 16, 1541316.
[12] Fisch, B., & Abir, R. (2018). Female fertility preservation: past, present and future. Reproduction, 156(1), F11–F27.
[13] Grin, L., Girsh, E., & Harlev, A. (2021). Male fertility preservation—methods, indications and challenges. Andrologia, 53(2), e13635.
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