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Latha Venkatesh

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Review Jul 2026

Home-Based Elderly Care Monitoring and Healthy Aging Promotion System Using Smart Technologies

The rapid escalation of the global aging demographic presents an unprecedented burden on contemporary healthcare infrastructure, necessitating a paradigm shift from traditional, reactive institutionalised care to proactive, home-based management strategies. This comprehensive review article evaluates the current state of the art in home-based elderly care monitoring and healthy aging promotion systems driven by integrated smart technologies. By synthesizing multi-disciplinary evidence across nursing, healthcare informatics, biomedical engineering, and digital health domains, this paper examines how the convergence of the Internet of Things (IoT), wearable physiological sensors, Artificial Intelligence (AI), Machine Learning (ML), smart home environments, mobile health (mHealth) platforms, and telemedicine networks can cooperatively support independent living.We delineate the structural architecture of these systems, mapping the transition of raw sensory telemetry from edge devices through cloud computing layers to actionable clinical decision-making interfaces. Clinical outcomes, including significantly reduced hospitalization rates, accelerated emergency response times, enhanced medication adherence, and improved quality of life indicators, are evaluated alongside the pervasive challenges that hinder widespread clinical translation. These systematic barriers include severe technical limitations in interoperability and battery longevity, ethical concerns surrounding continuous surveillance, and critical gaps in data privacy and cybersecurity infrastructure.Finally, this review outlines essential future paradigms, emphasizing user-centered co-design methodologies, edge-computing solutions to optimize data bandwidth, and the integration of next-generation generative AI frameworks capable of delivering predictive, context-aware personalized care. Ultimately, this work provides a rigorous roadmap for researchers, nursing professionals, healthcare practitioners, and engineers to collaborate on developing robust, ethically sound, and  sustainable smart ambient assisted living ecosystems that safeguard autonomy and promote holistic wellness among the global aging population.

Renuka, Navdeep Singh, Latha Venkatesh · 0 citations
Review Open access Jul 2026

A Comprehensive Scoping Review of School-Based Mental Health Nursing Interventions for the Early Identification and Management of Anxiety and Depression Among Adolescents

Adolescence represents a critical developmental period marked by heightened vulnerability to internalizing disorders, specifically anxiety and depression. Left unaddressed, these conditions significantly impair educational attainment, social relationships, and long-term functional trajectories. School nurses occupy a unique, strategically advantageous position within the educational ecosystem, serving as accessible healthcare providers capable of bridging the gap between undetected psychological distress and evidence-based mental health support. This review synthesizes existing literature surrounding school-based mental health nursing interventions focused on the early identification and management of anxiety and depression among adolescents.Utilizing an integrative mapping approach, we synthesized evidence from primary studies published between 2012 and 2026. The findings illustrate that nurse-led interventions—primarily encompassing brief Cognitive-behavioral Therapy (CBT) modules, structured psychoeducation, mindfulness-based emotion regulation techniques, and universal screening protocols demonstrate significant efficacy in reducing symptom severity and mitigating physical manifestations of distress, such as somatic complaints.

Arvind Kumar Singh, Sonia Nanda, Latha Venkatesh · 0 citations
Review Jul 2026

Medication Administration Safety and Error Prevention System Using Intelligent Nursing Support Technology

A systematic appraisal of high-impact literature across databases was conducted, demonstrating that integrated closed-loop medication management infrastructures substantially reduce MAEs by automating patient identification, prescription label parsing via computer vision, and real-time physiological response tracking.

Shivanand H Honakeri, Hemanth C K, Latha Venkatesh · 0 citations