Mukalere, Justine
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Examining ICT Interventions for Rural Health System Connectivity: Challenges and Gaps for Improvement: A Systematic Review Mukalere, Justine; Ssembatya, Richard; Habinka, Annabella
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1123

Abstract

Community healthcare interventions in Low- and Lower-Middle-Income Countries (LLMICs) frequently face record management issues that hinder effective linkage between community services and national health systems, contributing to persistently high mortality rates. This study aimed to identify and analyze ICT-based community health interventions implemented in LLMICs, evaluate their effectiveness, and explore challenges limiting their impact. A comprehensive literature search was conducted in June 2024 across ACM Library, PubMed, ScienceDirect, and Google Scholar, focusing on studies published between January 2019 and May 2024. Inclusion criteria targeted ICT-based interventions conducted in LLMICs, available in English, with accessible full texts and clearly defined ICT components. Of the 792 records initially screened, only 9 met the eligibility requirements. Most interventions addressed individual components such as data collection, monitoring, consultations, referrals, and reminders. However, they often lacked integrated systems for data management, continuity of care, and follow-up, limiting their long-term effectiveness. While the review was restricted to open-access studies, the findings offer crucial insights into the design and implementation of ICT-based health solutions. The absence of process integration in current interventions remains a major barrier. Future research and policy development should focus on designing comprehensive, integrated ICT frameworks to strengthen community-to-health system linkages and improve health outcomes in LLMICs.
AI-SEC-EDU Conceptual Framework: Securing E-Learning in Low-Income Countries’ Higher Education Institutions Mukalere, Justine; Omona, David Andrew; Ikwap, Agatha Flavia
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1297

Abstract

The evolving digital threat landscape, characterized by sophisticated AI-driven attacks, increasingly targets Higher Education Institutions (HEIs) through e-learning systems. This study introduces the AI-SEC-EDU framework to guide the integration of security controls and AI-enabled intelligence into cybersecurity strategies for e-learning platforms. The framework is based on a narrative review of existing cybersecurity interventions for e-learning in Low-Income Countries (LICs) and their approach to managing cybersecurity in the age of Artificial Intelligence. A search across four databases—ACM, Springer, ScienceDirect, and Google Scholar—in May 2025 identified 621 papers, of which eight met the inclusion criteria using PICO and PRISMA guidelines. The selected papers focused on cybersecurity in e-learning, discussing frameworks, models, and algorithms for platforms like Moodle, Google Classroom, and Coursera, some of which incorporate AI and open-source options. The study identifies three key security risk domains: technological infrastructure, human factors, and institutional governance, all of which are compounded by limited AI integration. Existing measures focus on system hardening but fail to address AI-based threat prediction and human behavior vulnerabilities. The AI-SEC model integrates AI, user awareness, and governance controls to provide adaptive, context-sensitive cybersecurity solutions for e-learning in LICs. This framework serves as a diagnostic and planning tool, aligning policies, institutional practices, and national strategies.