Dr. Shalini Bhusan, Vaibhav, Mohd. Khursheed

Prenatal Screening; Noninvasive Prenatal Testing (NIPT); Foetal Diagnostics; Cell-free DNA; Doppler Imaging; Genomic Sequencing; Prenatal Ethics; Precision Medicine; Digital Health Integration; Maternal-Foetal Medicine.

Prenatal screening and foetal diagnostics have undergone transformative evolution from biochemical serum screening to cell-free DNA analysis, advanced genomic sequencing, and high-resolution foetal imaging. The shift from invasive diagnostic modalities toward highly sensitive noninvasive prenatal screening (NIPS) has redefined risk assessment paradigms in obstetric care. This comprehensive analytical study evaluates technological, ethical, clinical, and psychosocial dimensions of contemporary prenatal diagnostics through a retrospective observational analysis of 520 pregnancies undergoing prenatal screening at a tertiary centre. Logistic regression modelling identified advanced maternal age (β=0.48, p<0.001), abnormal ultrasound markers (β=0.44, p<0.001), and positive NIPS results (β=0.56, p<0.001) as significant predictors of invasive diagnostic confirmation. Integration of NIPS reduced invasive procedures by 41% (p<0.01). Ethical concerns regarding informed consent and equitable access significantly influenced screening uptake (β=0.32, p<0.05). The final predictive model explained 82% of variance in diagnostic outcomes (R²=0.82). Findings support a paradigm shift toward precision prenatal medicine integrating genomic technologies, ethical governance, digital counselling platforms, and psychosocial screening frameworks.

[1] Beaudet, A. L. (2016). Using fetal cells for prenatal diagnosis: History and recent progress. American Journal of Medical Genetics Part C: Seminars in Medical Genetics, 172(2), 123–127.
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[5] Cohen, S. M., Chen, M., & Sun, L. (2025). Advancements in prenatal diagnosis: from noninvasive prenatal tests to novel fetal imaging. Frontiers in Medicine, 12, 1682161.
[6] Cuckle, H., & Maymon, R. (2016). Development of prenatal screening—A historical overview. Seminars in Perinatology, 40(1), 12–22.
[7] De Jong, A., Dondorp, W. J., Frints, S. G., de Die-Smulders, C. E., & De Wert, G. M. (2011). Advances in prenatal screening: the ethical dimension. Nature Reviews Genetics, 12(9), 657–663.
[8] De Jong, A., Maya, I., & Van Lith, J. M. (2015). Prenatal screening: current practice, new developments, ethical challenges. Bioethics, 29(1), 1–8.
[9] 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.
[10] 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.
[11] Evans, M. I., Wapner, R. J., & Berkowitz, R. L. (2016). Noninvasive prenatal screening or advanced diagnostic testing: caveat emptor. American Journal of Obstetrics and Gynecology, 215(3), 298–305.
[12] Fox, C. E., & Kilby, M. D. (2016). Prenatal diagnosis in the modern era. Obstetrician & Gynaecologist, 18(3).
[13] Geifman-Holtzman, O., & Ober Berman, J. (2008). Prenatal diagnosis: update on invasive versus noninvasive fetal diagnostic testing from maternal blood. Expert Review of Molecular Diagnostics, 8(6), 727–751.
[14] Levy, B., & Stosic, M. (2018). Traditional prenatal diagnosis: past to present. Prenatal Diagnosis, 3–22.
[15] Makhamreh, M. M., Chong, M. L., & Van den Veyver, I. B. (2025). Advancements in Prenatal Genetic Screening and Testing: Emerging Technologies and Evolving Applications. Diagnostics, 15(20), 2579.
[16] McLennan, A. (2003). Advances in prenatal screening. Australian Family Physician, 32(3).
[17] Nikolić, M. V., & Popović, J. (2024). Advantages and limitations of currently available methods of prenatal diagnostics. Acta Fac. Med. Naissensis, 41(3), 283–298.
[18] Oyelese, Y., Schioppo, D., & O’Brien, B. (2025). Prenatal screening and diagnosis: time for a paradigm shift. American Journal of Perinatology, 42(04), 538–545.
[19] 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.
[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] Tian, M., Feng, L., Li, J., & Zhang, R. (2023). Focus on the frontier issue: progress in noninvasive prenatal screening for fetal trisomy from clinical perspectives. Critical Reviews in Clinical Laboratory Sciences, 60(4), 248–269.
[22] Van den Veyver, I. B. (2016). Recent advances in prenatal genetic screening and testing. F1000Research, 5, 2591.
[23] Ilson, H. (2014). Advances in prenatal diagnostics. Biomarkers in Medicine, 8(4), 453–454.

Dr. Alpana Bansal, Shilki Sharma, Anupama Choudhary

High-risk Pregnancy; Antenatal Surveillance; Doppler Velocimetry; Cardiotocography; Thrombophilia; Advanced Maternal Age; Obstetric Critical Care; Precision Medicine; Multidisciplinary Obstetrics; Digital Health Monitoring.

High-risk pregnancies contribute disproportionately to maternal and perinatal morbidity and mortality despite advancements in obstetric surveillance and tertiary care infrastructure. Effective management requires integration of clinical expertise, structured antenatal monitoring, multidisciplinary coordination, and emerging digital health innovations. This analytical study evaluates determinants, management strategies, and clinical outcomes among 480 high-risk pregnancies managed in a tertiary care institution over four years. Multivariate logistic regression demonstrated that hypertensive disorders (β=0.52, p<0.001), thrombophilia (β=0.41, p<0.001), advanced maternal age (β=0.36, p<0.01), and inadequate antenatal compliance (β=0.44, p<0.001) significantly predicted adverse maternal outcomes. Structured Doppler monitoring reduced fetal compromise risk by 38% (p<0.01). The final predictive model explained 79% of variance in adverse maternal-fetal outcomes (R²=0.79). Findings support a systems-based management framework combining classical obstetric evidence, personalised thromboprophylaxis, psychosocial assessment, and AI-assisted risk stratification. High-risk pregnancy care must transition from reactive intervention to proactive, digitally enhanced, multidisciplinary management to optimise maternal and neonatal survival.

[1] Brown, V. A., Sawers, R. S., Parsons, R. J., Duncan, S. L., & Cooke, I. D. (1982). The value of antenatal cardiotocography in the management of high-risk pregnancy: a randomized controlled trial. BJOG: An International Journal of Obstetrics & Gynaecology, 89(9), 716–722.
[2] 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.
[3] Correa-de-Araujo, R., & Yoon, S. S. (2021). Clinical outcomes in high-risk pregnancies due to advanced maternal age. Journal of Women’s Health, 30(2), 160–167.
[4] Dangal, G. (2007). High-risk pregnancy. The Internet Journal of Gynecology and Obstetrics, 7(1), 1–7.
[5] Dargaud, Y., Rugeri, L., Fleury, C., Battie, C., Gaucherand, P., Huissoud, C., & Trzeciak, M. C. (2017). Personalized thromboprophylaxis using a risk score for the management of pregnancies with high risk of thrombosis: a prospective clinical study. Journal of Thrombosis and Haemostasis, 15(5), 897–906.
[6] Datta, S. (Ed.). (2006). Anesthetic and obstetric management of high-risk pregnancy. Springer Science & Business Media.
[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] Effer, S. B. (1969). Management of high-risk pregnancy: report of a combined obstetrical and neonatal intensive care unit. Canadian Medical Association Journal, 101(7), 55.
[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] Hoxha, A., Tormene, D., Campello, E., & Simioni, P. (2022). Treatment of refractory/high-risk pregnancies with antiphospholipid syndrome: a systematic review of the literature. Frontiers in Pharmacology, 13, 849692.
[11] James, D. K., Steer, P. J., Weiner, C. P., & Gonik, B. (2010). High risk pregnancy e-book: Management options—expert consult. Elsevier Health Sciences.
[12] Pattinson, R. C., Norman, K., & Odendaal, H. J. (1994). The role of Doppler velocimetry in the management of high risk pregnancies. BJOG: An International Journal of Obstetrics & Gynaecology, 101(2), 114–120.
[13] Queenan, J. T., Spong, C. Y., & Lockwood, C. J. (Eds.). (2012). Queenan’s management of high-risk pregnancy: an evidence-based approach. John Wiley & Sons.
[14] 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.
[15] Sarig, G., Vidergor, G., & Brenner, B. (2009). Assessment and management of high-risk pregnancies in women with thrombophilia. Blood Reviews, 23(4), 143–147.
[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] Spong, C. Y., & Lockwood, C. J. (Eds.). (2023). Queenan’s Management of High-risk Pregnancy: An Evidence-based Approach. John Wiley & Sons.
[18] Trivedi, S. S. (2015). Management of High-Risk Pregnancy—a practical approach. JP Medical Ltd.
[19] 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.
[20] Zhu, J., Said, F. M., & Tan, C. H. (2024). Progress in Research on the Management of High-Risk Pregnancies in China. International Journal of Biotechnology and Biomedicine (IJBB), 1(2), 44–56.

Isaac Flannery Muimui Muimui, Dr. J. Arockia Venice

ICT In Education; Remote Schools; Digital Divide; Artificial Intelligence; Zambia; Teacher Challenges; Digital Transformation.

The integration of information and communication technology (ICT) into education has become a global policy priority, yet remote schools in developing nations continue to face profound challenges in its effective implementation. This article examines the challenges confronting teachers in remote Zambian schools in teaching ICT, and situates these challenges within the broader global discourse on artificial intelligence, digital transformation, and technology-mediated learning. Drawing on a descriptive survey study of two selected remote schools, the article identifies infrastructure deficits, limited teacher ICT competence, inadequate professional development, resource scarcity, and connectivity barriers as primary impediments. The study argues that AI-powered adaptive platforms, offline-capable digital tools, and blockchain-enabled institutional management systems offer promising pathways toward bridging the digital divide in remote educational contexts. Policy recommendations targeting infrastructure investment, teacher capacity building, and community engagement are offered

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[2] 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.
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[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. Frontiers in Psychiatry, 16, 1541316.
[8] 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).
[9] 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 in business schools in India. Texila International Journal of Public Health, 13(2).
[10] 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.
[11] 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.
[12] Kariveliparambil, A., R A, R., Ahmad, M. S., Ramesh, S., & Kuriakose, A. (2026b). Invisible burdens of platform work: A qualitative study of food-delivery riders’ lived experiences in urban India. International Journal of Qualitative Studies on Health and Well-Being, 21(1).
[13] Kombo, D. K., & Tromp, D. L. A. (2014). Proposal and thesis writing: An introduction. Paulines Publications Africa.
[14] 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.
[15] Mohanbabu, S., & Vettriselvan, R. (2025a). Focusing supply chain and container terminal challenges from the lens of Indian industries’ perspectives. International Journal of Procurement Management, 24(1), 92–114.
[16] Mohanbabu, S., & Vettriselvan, R. (2025b). Will machine learning resolve the issues in container management in ports and logistics industries? International Journal of Process Management and Benchmarking, 20(4), 559–575.
[17] Orodho, J. A., & Kombo, D. K. (2012). Research methods. Kenyatta University Press.
[18] 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.
[19] 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.
[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] 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.
[22] 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.
[23] Vasantha, S., Swadhi, R., Gayathri, K., Selvalakshmi, V., & UmaDevi, A. (2025). Fostering personalized learning and achieving equity in education: The role of AI-powered curriculum development. In Transforming education with AI-powered personalized learning (pp. 201–236). IGI Global Scientific Publishing.
[24] Venice, J. A., Arivazhagan, D., Suman, N., Shanthi, H. J., & Swadhi, R. (2025a). Recommendation systems and content personalization: Algorithms, applications, and adaptive learning. In AI for large scale communication networks (pp. 323–348). IGI Global Scientific Publishing.
[25] Venice, J. A., Vettriselvan, R., Jain, S., Madusudanan, K., & Aarthy, C. C. J. (2025b). 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.
[26] 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.
[27] 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.
[28] Venice, J. A., Sripathi, S. K., & Moonga, B. (2025e). Social deviance and the influence of internet exposure: A study of secondary school students in Lusaka. ASET Journal of Management Science, 4(SI-1).
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[30] 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.
[31] 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.
[32] 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.
[33] Vettriselvan, R., & Rajan FSA, A. J. (2019). Occupational health issues faced by women in spinners. Indian Journal of Public Health Research & Development, 10(1).
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[35] 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.
[36] 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.
[37] 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: Methodologies, impact, and repercussions (pp. 109–140). IGI Global Scientific Publishing.
[38] 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.
[39] Vijayalakshmi, M., Subramani, A. K., Vettriselvan, R., Catherin, T. C., & Deepika, R. (2025a). 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.
[40] 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.
[41] 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.
[42] Vinodh, N., Subramani, A. K., & Vettriselvan, R. (2026b). Transforming the future of management and medical education: AI-driven innovations in curriculum design. In AI education strategies for future-proofing curriculum design (pp. 459–476). IGI Global Scientific Publishing.
[43] 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. Paridhi Garg, Neha Kakran, Vishal Kumar

Gynecologic Oncology; Precision Medicine; Targeted Therapy; Immunotherapy; Artificial Intelligence; Minimally Invasive Surgery; Surgical De-escalation; Telemedicine; Health Equity; Workforce Sustainability; Value-Based Care; Cancer Disparities.

Gynecologic oncology is undergoing transformative evolution driven by developments in molecular medicine, artificial intelligence integration, surgical innovation, telehealth expansion, and global health equity efforts. Advances in early detection models, biomarker-based targeted therapies, immunotherapy modalities, minimally invasive surgery, and surgical de-escalation have revolutionised the treatment paradigm for ovarian, cervical, and endometrial cancers. Simultaneously, demographic changes, workforce sustainability concerns, fundamental healthcare organisation challenges, and systemic inequalities are reshaping care delivery models. This paper synthesises emerging trends infiltrating gynecologic oncology in an evidence-based and holistic manner, incorporating diagnostic innovation, precision therapeutics, digital health, and surgical advances while addressing contemporary issues of workforce sustainability and global inequity. The analysis identifies precision oncology, AI-based diagnostics, telemedicine integration, multidisciplinary care, and equity-based systems as key pillars of contemporary gynecologic cancer care. Sustained interdisciplinary cooperation, policy innovation, and strategic infrastructure investment are identified as prerequisites for translating technological advances into equitable, sustainable, and patient-centric outcomes.

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[2] Boitano, T. K., Blank, S. V., Havrilesky, L. J., Huh, W. K., & Myers, E. R. (2024). Too much of a good thing? Projecting the need for gynecologic oncologists over the next 20 years. Gynecologic Oncology, 191, 287–291.
[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] 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.
[5] Di Fiore, R., Suleiman, S., Ellul, B., O’toole, S. A., Savona-Ventura, C., Felix, A., & Calleja-Agius, J. (2021). GYNOCARE update: modern strategies to improve diagnosis and treatment of rare gynecologic tumors. Cancers, 13(3), 493.
[6] Doddi, S., Salichs, O., Mushuni, M., & Kunte, S. (2023). Demographic disparities in trend of gynecological cancer in the United States. Journal of Cancer Research and Clinical Oncology, 149(13), 11541–11547.
[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] Eskandar, K. (2024). Advancements in gynecology: A comprehensive review of emerging research and innovations. Journal of Medical and Clinical Nursing Studies.
[9] Hicks-Courant, K., Kanter, G. P., Giuntoli, R. L., Schapira, M. M., Bekelman, J. E., Latif, N. A., & Ko, E. M. (2021). An increase in multi-site practices: the shifting paradigm for gynecologic cancer care delivery. Gynecologic Oncology, 160(1), 3–9.
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[11] Kanbergs, A., Melamed, A., Viveros-Carreño, D., Wu, C. F., Wilke, R. N., Zamorano, A., & Agusti, N. (2025). Surgical deescalation within gynecologic oncology. JAMA Network Open, 8(1), e2453604.
[12] Kosimov, F. M. (2025). Modern Trends and Innovations in Gynecology: Advancements in Women’s Healthcare. Journal of Modern Educational Achievements, 3, 89–92.
[13] Kyrgiou, M., Bowden, S., Denny, L., Fagotti, A., Abu-Rustum, N. R., Ramirez, P. T., & Querleu, D. (2024). Innovation in gynaecological cancer: highlighting global disparities. The Lancet Oncology, 25(4), 425–430.
[14] Meena, J., Banerjee, D., Kim, S. I., Komatsu, H., Kwok, S. T., Lai, Y. L., & Noh, J. J. (2025). Current status and challenges in training the next generation of gynecologic cancer care providers in Asia. Journal of Gynecologic Oncology, 36(6), e103.
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Chani Nyambe S, Dr. J. Arockia Venice

Learner-Centred Education; Artificial Intelligence; Digital Transformation; Primary Education; Zambia; Personalised Learning; Cognitive IoT.

The convergence of artificial intelligence (AI), digital transformation, and learner-centred pedagogy has redefined educational practice globally. In Zambia, despite national policy mandating learner-centred instruction, rural primary schools continue to face significant implementation gaps. This article synthesises findings from a descriptive survey conducted in three primary schools in Sioma District, Western Province, with global scholarship on AI-powered personalised learning, blockchain-enabled credentialing, and adaptive curriculum design. Findings confirm that learner-centred methods enhance critical thinking, motivation, and academic mastery among primary pupils, while resource deficits, time constraints, and limited teacher professional development remain primary barriers. The study argues that strategically deploying AI and digital technologies in contextually appropriate ways can substantially advance learner-centred reform in developing nations. Policy and practice recommendations are offered.

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Dr. Zeineb ESSID

AI-augmented leadership; Employee well-being; MENA region.

Purpose: This study aims to examine the direct effects of AI-augmented leadership on employee well-being within the Middle East and North Africa (MENA) region.
Design/methodology/approach: A quantitative approach was employed, analyzing survey data collected from 104 professionals in Tunisia, Egypt, and Saudi Arabia.
Findings: The results reveal that AI-enhanced leadership has a positive and direct impact on employee well-being. Originality/value: This study provides a pioneering analysis of how AI-assisted leadership directly influences employee well-being in the underexplored MENA region. It introduces a human-centered framework tailored to the region’s unique characteristics, promoting ethical and context-sensitive adoption of AI technologies in organizations undergoing digital transformation.

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[35] Paschen, J., Kietzmann, J., & Kietzmann, T. C. (2023). Artificial intelligence in marketing: Past, present and future. Journal of Business Research, 144, 735–747.
[36] Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. https://doi.org/10.3758/BRM.40.3.879
[37] Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/amr.2018.0072
[38] Ryff, C. D., & Keyes, C. L. M. (1995). The structure of psychological well-being revisited. Journal of Personality and Social Psychology, 69(4), 719–727. https://doi.org/10.1037/0022-3514.69.4.719
[39] Taris, T. W., & Schaufeli, W. B. (2015). Individual well-being and performance at work: A conceptual and theoretical overview. In M. van Veldhoven & R. Peccei (Eds.), Well-being and performance at work: The role of context (pp. 15 –34). Psychology Press.

Dr. O.S.Vedavalli

Sustainability; Economics; Buying Intent; Web Loyalty; E-Commerce Platform.

Participating in any kind of online business activity is becoming more and more important to the financial viability of companies of all sizes and industries. Even though e-commerce has few technical barriers to entry, many businesses’ capacity to adjust to new online markets is essential to their long-term financial success. To compete with the combined markets of industrialized nations, India’s e-commerce industry has experienced a notable upswing. Online shopping platforms are crucial for firms operating in these conditions, and this study explores the major factors that influence Indian consumers’ desire to utilize and support them. Given the fierce rivalry between Indian e-commerce platforms, it is especially important to comprehend the elements that affect consumer choice. A quantitative survey of 242 seasoned Indian internet buyers was carried out. Structural equation modeling (SEM) analysis of the data showed that a model with three factor components predicts whether or not customers will choose an online shopping platform. Web Loyalty (WL) and Buying Intent (BI) are both indicated by Digital Shopping Experience (DSE). These results demonstrate the need for e-commerce platforms to concentrate on important DSP components, such as improving the company’s reputation, providing a wide variety of products, creating intuitive online shopping experiences, and raising platform awareness. Both e-commerce experts and researchers with an interest in e-commerce can benefit from these insights.

[1] Abbass, K.; Begum, H.; Alam, A.S.A.F.; Awang, A.H.; Abdelsalam, M.K.; Egdair, I.M.M.; Wahid, R. Fresh Insight Through A Keynesian Theory Approach to Investigate the Economic Impact of the Covid-19 Pandemic In Pakistan. Sustainability 2022, 14, 1054.
[2] Cordes, D. L., & Marinova, D. (2023). Systematic literature review of the role of e-commerce in providing pathways to sustainability for poverty alleviation in Sub-Saharan Africa. Discover Sustainability, 4(1), 7.
[3] Elkington, J. Enter the Triple Bottom Line. In The Triple Bottom Line; Routledge: London, UK, 2013; pp. 23–38.
[4] Gatto, A. A Pluralistic Approach to Economic and Business Sustainability: A Critical Meta-Synthesis of Foundations, Metrics, and Evidence of Human and Local Development. Corp. Soc. Responsib. Environ. Manag. 2020, 27, 1525–1539.
[5] Goerner, S.J.; Lietaer, B.; Ulanowicz, R.E. Quantifying Economic Sustainability: Implications for Free-Enterprise Theory, Policy and Practice. Ecol. Econ. 2009, 69, 76–81.
[6] Hansmann, R.; Mieg, H.A.; Frischknecht, P. Principal Sustainability Components: Empirical Analysis of Synergies Between the Three Pillars of Sustainability. Int. J. Sustain. Dev. World Ecol. 2012, 19, 451–459.
[7] Kennedyd, S. I., Marjerison, R. K., Yu, Y., Zi, Q., Tang, X., & Yang, Z. (2022). E-commerce engagement: A prerequisite for economic sustainability—An empirical examination of influencing factors. Sustainability, 14(8), 4554.
[8] Klaassen, G.A.J.; Opschoor, J.B. Economics of Sustainability or the Sustainability of Economics: Different Paradigms. Ecol. Econ. 1991, 4, 93–115.
[9] Komeily, A.; Srinivasan, R.S. A Need for Balanced Approach to Neighborhood Sustainability Assessments: A Critical Review and Analysis. Sustain. Cities Soc. 2015, 18, 32–43.
[10] Kuhlman, T.; Farrington, J. What Is Sustainability? Sustainability 2010, 2, 3436–3448.
[11] Pinto, A. S., Guerra-Mota, M., & Dias, I. (2023). Impact of E-commerce on Corporate Sustainability—Case Study. In Marketing and Smart Technologies: Proceedings of ICMarkTech 2022, Volume 2 (pp. 599-611). Singapore: Springer Nature Singapore.
[12] Purvis, B.; Mao, Y.; Robinson, D. Three Pillars of Sustainability: In Search of Conceptual Origins. Sustain. Sci. 2019, 14, 681–695.
[13] Sindakis, S., Showkat, S., & Su, J. (2023). Unveiling the Influence: Exploring the Impact of Interrelationships among E-Commerce Supply Chain Members on Supply Chain Sustainability. Sustainability, 15(24), 16642.
[14] Soini, K.; Birkeland, I. Exploring the Scientific Discourse On Cultural Sustainability. Geoforum 2014, 51, 213–223.
[15] Zucman, G. Global Wealth Inequality. Annu. Rev. Econ. 2019, 11, 109–138.

Dr. N. Gurumurthy, Prof. K. Jayachandra Reddy

Rural Development; Entrepreneurship; Economic Growth; Challenges; Opportunities

The foundation of a nation lies in the strong developments of living standard of its people. For this purpose, they have to overcome some issues such as economic disparity, social inequality, and gender bias. India is a vast democratic country in the world. She became first country in the population growth. It has a significant amount of rural population engaged in various cottage industries that serve as a source of livelihood to them. Population growth presents many challenges. This article addresses the rural economic issues which can help alleviate poverty. Conducting a systematic survey of rural communities and their economic activities can aid in improving their living conditions. Encouraging rural entrepreneurship can empower individuals to establish businesses, fostering economic self-reliance and reducing unemployment.

Rural development is an essential for the sustainable economic progress and social well-being. This study examines how entrepreneurship can generate and drive rural development, emphasizing its role in employment generation, poverty reduction, and regional economic balance. By leveraging local resources and skills, rural entrepreneurship can serve as a catalyst for sustainable economic transformation.

[1] M. W. Rutherford, B. E. Whitacre, L. Captain, S. Ekin, J. Angle, T. Hensley and J. F. O’Hara, “Promoting Rural Entrepreneurship Through Technology: A Case Study Using Productivity Enhancing Technology Experience Kits (PETE-Kits),” IEEE Trans. Educ., vol. PP, pp. 1–?, 2025, doi: 10.1109/TE.2025.3557023.
[2] “User innovation and entrepreneurship: case studies from rural India,” J. Innovation Entrepreneurship, vol. 4, article no. 5, Apr. 2015.
[3] M. Abbasi, H. Jafari and K. Alizadeh, “Factors that influence rural entrepreneurship: case-study evidence from Torbat-e Heydarie, Kadkan district,” Revista Eletrônica em Gestão, Educação e Tecnologia Ambiental, 2025, doi: 10.5902/2236117063506.
[4] P. Vidhya Priya and M. Mohanasundari, “Sustainable Rural Development through Entrepreneurship: A Study on Start-Up Enterprises,” Int. J. Eng. Fin. Manage., vol. 7, no. 3, 2025.
[5] S. Parwez, “Community-based entrepreneurship: evidences from a retail case study,” J. Innovation Entrepreneurship, vol. 6, article 14, 2017.
[6] O. Onaopemipo Olalekan, “Rural Entrepreneurship in the Digital Age: A Systematic Review,” Int. J. Sustain. Rural Dev., vol. 1, no. 1, pp. 1–5, Jul. 2024.
[7] Z. A. Parray, R. A. A. Rather, S. A. Bhat and P. S. Ahmad, “Investigating the Rural and Entrepreneurial Development through Microfinance,” Int. Res. J. Bus. Stud., vol. 15, no. 2, pp. 177–190, 2024.
[8] E. Ujarura Kamutuezu, H. Winschiers-Theophilus and A. Peters, “An Exploration of Factors Influencing the Adoption of ICT Enabled Entrepreneurship Applications in Namibian Rural Communities,” arXiv:2108.09789, 2021.
[9] A. Bhatia-Kalluri, “E-commerce for Rural Micro-Entrepreneurs: Mapping Restrictions, Ecologies of Use and Trends for Development,” arXiv:2108.09759, 2021.

Phone V. Tamilarasi, S. Tamilselvan

Online Advertising; Consumer Behavior; Mobile Phones; Digital Marketing; Social Media.

The shift in advertising expenditure from traditional media to digital platforms is a defining trend of the modern marketing era. This study investigates the impact of online advertising on the consumer buying behavior specifically for mobile phones, one of the most heavily advertised product categories online. Utilizing a descriptive research design, primary data was collected from 161 respondents through a structured questionnaire. The findings indicate that online advertising is highly effective in creating awareness and providing information, with 69.6% of respondents finding it informative. Social media and e-commerce platforms are the dominant channels, with Flipkart (70.8%) and Amazon (70.2%) being the most preferred sites for purchase. However, the influence on the final purchase decision is nuanced; while ads create awareness, their repetitive and intrusive nature can cause irritation (47.8%). The study concludes that online advertising is a powerful, indispensable tool for reach and information dissemination in the consumer journey, but its ultimate effectiveness in driving purchases depends on a strategic balance between informativeness, entertainment, and respect for consumer privacy.

[1] Gupta, A., & Mehta, R., “Determinants of Consumer Engagement with Mobile Phone Ads,” Journal of Interactive Advertising, Vol. 24, Issue 1, 2024, pp. 45-59.
[2] Sharma, N., “The Role of Creativity and Entertainment in Online Ad Effectiveness,” Indian Journal of Marketing, Vol. 54, Issue 2, 2024, pp. 112-125.
[3] Khan, S., & Rani, P., “Influencer Marketing and E-WOM in the Smartphone Industry,” Journal of Digital & Social Media Marketing, Vol. 13, Issue 3, 2025, pp. 234-248.
[4] Joseph, L., & Thomas, S., “Personalization vs. Privacy: The Consumer Dilemma in Digital Advertising,” Journal of Consumer Behaviour, Vol. 22, Issue 4, 2025, pp. 301-315.
[5] Kotler, P., Keller, K. L., & Chernev, A., Marketing Management, 16th ed., Pearson Education, 2023.
[6] Smith, T. J., & Taylor, R., “Digital Media and Purchase Intent: A Study of Young Consumers,” International Journal of Internet Marketing and Advertising, Vol. 18, Issue 1, 2024, pp. 78-94.

V. Subasree, Dr. E. Karthikeyan, V. Radhakrishnan

Digital Payments; Customer Perception; UPI; Cashless Economy; Financial Technology.

The Indian economy is undergoing a rapid digital transformation, significantly propelled by government initiatives like Digital India and demonetization. This shift has placed digital payment systems at the forefront of financial transactions. This study investigates consumer perceptions of these systems to understand the key factors influencing their adoption and sustained usage. Utilizing a descriptive research design, primary data was collected from 100 respondents through a structured questionnaire, focusing on demographics, usage patterns, and perceptions of convenience, security, and usefulness. The findings indicate a high adoption rate (90%), driven primarily by perceived convenience (53% agree/strongly agree) and time-saving benefits (53% agree/strongly agree). While a majority of users show brand loyalty (54% agree/strongly agree on using one app), perceptions on security and absolute usefulness were more varied. The study concludes that while digital payments are widely accepted, enhancing security measures, ensuring system stability, and improving user education are critical for deepening adoption and moving towards a truly cash-lite economy.

[1] National Payments Corporation of India, “A Decade in Review: The Transformation of India’s Payments Landscape,” NPCI White Paper, 2020.
[2] Reserve Bank of India, “Annual Report on Trends and Progress of Banking in India,” RBI Publication, 2022-2023.
[3] Ministry of Electronics and Information Technology, “Digital India: Programme of Transformation,” Government of India Report, 2021.
[4] Kapoor, A., & Dwivedi, Y. K., “The Rise of Digital Payments in India: A Study of Consumer Adoption,” Journal of Financial Technology, Vol. 5, Issue 2, 2021, pp. 112-125.
[5] Gupta, S., “Post-Demonetization: Analyzing the Surge in Digital Payment Transactions,” Indian Journal of Economics and Business, Vol. 19, Issue 3, 2020, pp. 45-58