WEARABLE TECHNOLOGIES IN HEALTH MONITORING: EFFECTIVENESS IN PREVENTING LIFESTYLE DISEASES

Research objectives: This comprehensive systematic review and meta-analysis aims to critically evaluate the clinical evidence on the effectiveness, feasibility, and cost-effectiveness of wearable technologies in health monitoring and the prevention of lifestyle diseases between 2020 and 2024. The study focuses on two main pillars of innovation: devices for monitoring physical activity and health parameters (smartwatches, fitness bands, continuous glucose monitors) and artificial intelligence (AI)-based data analysis systems that enable early risk detection and personalization of health interventions. In addition, the review analyzes the ethical, legal, social, and implementation (ELSI) barriers that must be overcome to enable the large-scale implementation of wearable technologies in healthcare systems. Methods: A scoping review of scientific literature was conducted in databases including PubMed, Scopus, and Google Scholar, using inclusion criteria that included randomized controlled trials (RCTs), systematic reviews, and meta-analyses published from January 2020 to July 2024. Seven key meta-analyses and twenty RCTs were analyzed in detail, focusing on effect sizes (Hedges' g, standardized mean difference - SMD), adherence rates, and impact on clinical endpoints. The risk of systematic error and regulatory frameworks were also assessed. Main results: Wearable technologies showed moderate to high effectiveness in monitoring health parameters and modifying health-related behaviors. A meta-analysis of interventions using wearable devices to monitor physical activity showed a statistically significant increase in the number of steps per day (weighted mean difference: 1519 steps/day, 95% CI 1096-1942) and moderate to large effect sizes (SMD = 0.449) compared to control groups (Hodkinson et al., 2021; Tang et al., 2020). Continuous glucose monitoring (CGM) has shown particularly high effectiveness in diabetes control. A meta-analysis of 15 RCTs (2,461 patients) showed a significant reduction in HbA1c (weighted mean difference: -0.17%, 95% CI -0.29 to -0.06) and an increase in time in range (TIR) of 70.74 minutes (95% CI 46.73-94.76) compared to standard care (Maiorino et al., 2020). The main barriers included: problems with measurement accuracy in real-world settings, user fatigue leading to low long-term adherence, protection of health data privacy, and lack of standardization and interoperability between devices and EHR (electronic health record) systems. Conclusions: Wearable technologies are becoming an integral part of preventive medicine and chronic disease management. The future lies in blended care models that combine continuous health monitoring with AI predictive algorithms and clinical oversight. Long-term RCT studies (≥12 months) and a clear regulatory framework regarding the accuracy of medical devices, data collection ethics, and legal liability must be established before widespread implementation in healthcare systems.