WEARABLE TECHNOLOGIES IN HEALTH MONITORING: EFFECTIVENESS IN PREVENTING LIFESTYLE DISEASES
Abstract
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.
References
Abbas, J. R., Gantwerker, E., Volk, M., Payton, T., McGrath, B. A., Tolley, N., & Isba, R. (2024). Describing, evaluating, and exploring barriers to adoption of virtual reality: An international modified Delphi consensus study involving clinicians, educators, and industry professionals. Journal of Medical Extended Reality, 1(1), 202-214. https://doi.org/10.1089/jmxr.2024.0022
Berardi, C., De Togni, A., Antonini, M., Hinwood, M., Jordan, Z., Wechtler, H., & Paolucci, F. (2024). Barriers and facilitators to the implementation of digital technologies in mental health systems: A qualitative systematic review to inform a policy framework. BMC Health Services Research, 24, Article 243. https://doi.org/10.1186/s12913-023-10536-1
Franssen, W. M. A., Franssen, G. H. L. M., Spaas, J., Solmi, F., & Eijnde, B. O. (2020). Can consumer wearable activity tracker-based interventions improve physical activity and cardiometabolic health in patients with chronic diseases? A systematic review and meta-analysis of randomised controlled trials. International Journal of Behavioral Nutrition and Physical Activity, 17(1), Article 57. https://doi.org/10.1186/s12966-020-00955-2
Gal, R., May, A. M., van Overmeeren, E. J., Simons, M., & Monninkhof, E. M. (2018). The Effect of Physical Activity Interventions Comprising Wearables and Smartphone Applications on Physical Activity: A Systematic Review and Meta-analysis. Sports Medicine - Open, 4(1), Article 42. https://doi.org/10.1186/s40798-018-0157-9
Hodkinson, A., Kontopantelis, E., Adeniji, C., van Marwijk, H., McMillan, B., Bower, P., & Panagioti, M. (2021). Interventions Using Wearable Physical Activity Trackers Among Adults With Cardiometabolic Conditions: A Systematic Review and Meta-analysis. JAMA Network Open, 4(7), e2116382. https://doi.org/10.1001/jamanetworkopen.2021.16382
Jafleh, S. A., Jain, S., Hickey, B. A., Sclaroff, C., & Caggiano, D. (2024). The Role of Wearable Devices in Chronic Disease Monitoring and Patient Care: A Comprehensive Review. Cureus, 16(9), e68921. https://doi.org/10.7759/cureus.68921
Jancev, M., Diduck, Q., Watt, K., Lam, S., Cvitanovic, J., Patel, S., Mintsopoulos, V., Sivapathasundaram, B., Rayner, J., Sheu, N., Maguire, B., Kueper, J. K., Hung, R. K. C., Carpino, M., Imran, S. A., & Nerenberg, K. (2024). Continuous glucose monitoring in adults with type 2 diabetes: a systematic review and meta-analysis. Diabetologia, 67(5), 798-822. https://doi.org/10.1007/s00125-024-06107-6
Kamei, T., Yamamoto, Y., Kajii, F., Nakayama, Y., & Kawakami, C. (2020). The use of wearable devices in chronic disease management to enhance adherence and improve telehealth outcomes: A systematic review and meta-analysis. Journal of Telemedicine and Telecare, 28(5), 342-359. https://doi.org/10.1177/1357633X20937573
Kong, S. H., & Cho, Y. M. (2024). Effects of continuous glucose monitoring on glycemic control in type 2 diabetes: A systematic review and meta-analysis of randomized controlled trials. Healthcare, 12(5), Article 571. https://doi.org/10.3390/healthcare12050571
Longhini, J., Marzano, M., Bargeri, S., Giustino, V., Marini, S., Cabras, F., Curreli, M., Zigrino, M., & Buzzacchera, C. F. (2024). Wearable Devices to Improve Physical Activity and Reduce Sedentary Behaviour: An Umbrella Review. Sports Medicine - Open, 10(1), Article 13. https://doi.org/10.1186/s40798-024-00678-9
Maiorino, M. I., Signoriello, S., Maio, A., Chiodini, P., Bellastella, G., Scappaticcio, L., Longo, M., Giugliano, D., & Esposito, K. (2020). Effects of Continuous Glucose Monitoring on Metrics of Glycemic Control in Diabetes: A Systematic Review With Meta-analysis of Randomized Controlled Trials. Diabetes Care, 43(5), 1146-1156. https://doi.org/10.2337/dc19-1459
Mattison, G., Canfell, O., Forrester, D., Dobbins, C., Smith, D., Töyräs, J., & Sullivan, C. (2022). The Influence of Wearables on Health Care Outcomes in Chronic Disease: Systematic Review. Journal of Medical Internet Research, 24(7), e36690. https://doi.org/10.2196/36690
OECD. (2023). Health at a Glance 2023: OECD Indicators. Paris: OECD Publishing. https://doi.org/10.1787/7a7afb35-en
Sun, F., Norman, I. J., & While, A. E. (2025). Wearable Technologies for Health Promotion and Disease Prevention in Older Adults: Systematic Scoping Review. Journal of Medical Internet Research, 27, e69077. https://doi.org/10.2196/69077
Tang, M. S. S., Moore, K., McGavigan, A., Clark, R. A., & Ganesan, A. N. (2020). Effectiveness of Wearable Trackers on Physical Activity in Healthy Adults: Systematic Review and Meta-Analysis of Randomized Controlled Trials. JMIR mHealth and uHealth, 8(7), e15576. https://doi.org/10.2196/15576
Uhl, S., Berger, C., Hinder, M., & Caverius, P. (2024). Effectiveness of Continuous Glucose Monitoring on Metrics of Glycemic Control in Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis of Randomized Controlled Trials. The Journal of Clinical Endocrinology & Metabolism, 109(4), 892-903. https://doi.org/10.1210/clinem/dgad652
Wang, J. B., Cadmus-Bertram, L. A., Natarajan, L., White, M. M., Madanat, H., Nichols, J. F., Ayala, G. X., & Pierce, J. P. (2022). The Effectiveness of Wearable Devices as Physical Activity Interventions for Preventing and Treating Obesity in Children and Adolescents: Systematic Review and Meta-analysis. JMIR mHealth and uHealth, 10(4), e32435. https://doi.org/10.2196/32435
World Health Organization. (2023). Noncommunicable diseases. Geneva: WHO. Retrieved from https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases
Perez, M. V., Mahaffey, K. W., Hedlin, H., Rumsfeld, J. S., Garcia, A., Ferris, T., Balasubramanian, V., Russo, A. M., Rajmane, A., Cheung, L., Hung, G., Lee, J., Kowey, P., Talati, N., Nag, D., Gummidipundi, S. E., Beatty, A., Hills, M. T., Desai, S., Granger, C. B., … Apple Heart Study Investigators (2019). Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation. The New England journal of medicine, 381(20), 1909–1917. https://doi.org/10.1056/NEJMoa1901183
Ding, E. Y., Tran, K. V., Lessard, D., Wang, Z., Han, D., Mohagheghian, F., Mensah Otabil, E., Noorishirazi, K., Mehawej, J., Filippaios, A., Naeem, S., Gottbrecht, M. F., Fitzgibbons, T. P., Saczynski, J. S., Barton, B., Chon, K., & McManus, D. D. (2023). Accuracy, Usability, and Adherence of Smartwatches for Atrial Fibrillation Detection in Older Adults After Stroke: Randomized Controlled Trial. JMIR cardio, 7, e45137. https://doi.org/10.2196/45137
Belani, S., Wahood, W., Hardigan, P., Placzek, A. N., & Ely, S. (2021). Accuracy of Detecting Atrial Fibrillation: A Systematic Review and Meta-Analysis of Wrist-Worn Wearable Technology. Cureus, 13(12), e20362. https://doi.org/10.7759/cureus.20362
Tran, K. V., Filippaios, A., Noorishirazi, K., Ding, E., Han, D., Mohagheghian, F., Dai, Q., Mehawej, J., Wang, Z., Lessard, D., Otabil, E. M., Hamel, A., Paul, T., Gottbrecht, M. F., Fitzgibbons, T. P., Saczynski, J., Chon, K. H., & McManus, D. D. (2023). False Atrial Fibrillation Alerts from Smartwatches are Associated with Decreased Perceived Physical Well-being and Confidence in Chronic Symptoms Management. Cardiology and cardiovascular medicine, 7(2), 97–107. https://doi.org/10.26502/fccm.92920314
Islam, S. M. S., Chow, C. K., Daryabeygikhotbehsara, R., Subedi, N., Rawstorn, J., Tegegne, T., Karmakar, C., Siddiqui, M. U., Lambert, G., & Maddison, R. (2022). Wearable cuffless blood pressure monitoring devices: a systematic review and meta-analysis. European heart journal. Digital health, 3(2), 323–337. https://doi.org/10.1093/ehjdh/ztac021
Stergiou, G. S., Mukkamala, R., Avolio, A., Kyriakoulis, K. G., Mieke, S., Murray, A., Parati, G., Schutte, A. E., Sharman, J. E., Asmar, R., McManus, R. J., Asayama, K., De La Sierra, A., Head, G., Kario, K., Kollias, A., Myers, M., Niiranen, T., Ohkubo, T., Wang, J., … European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability (2022). Cuffless blood pressure measuring devices: review and statement by the European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability. Journal of hypertension, 40(8), 1449–1460. https://doi.org/10.1097/HJH.0000000000003224
Noci, F., Capodici, A., Nuti, S., Passino, C., Emdin, M., & Giannoni, A. (2025). Wearable technologies to predict and prevent and heart failure hospitalizations: a systematic review. European heart journal. Digital health, 6(5), 868–877. https://doi.org/10.1093/ehjdh/ztaf079
Bhatia, A., & Maddox, T. M. (2020). Remote Patient Monitoring in Heart Failure: Factors for Clinical Efficacy. International journal of heart failure, 3(1), 31–50. https://doi.org/10.36628/ijhf.2020.0023
Hettikankanamage, N., Shafiabady, N., Chatteur, F., Wu, R. M. X., Ud Din, F., & Zhou, J. (2025). eXplainable Artificial Intelligence (XAI): A Systematic Review for Unveiling the Black Box Models and Their Relevance to Biomedical Imaging and Sensing. Sensors, 25(21), 6649. https://doi.org/10.3390/s25216649
Sadeghi Z, et al. A review of Explainable Artificial Intelligence in healthcare. (2024). ScienceDirect. https://www.sciencedirect.com/science/article/pii/S0045790624002982
Jahfari AN, et al. Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review. PMC. 2022. https://pmc.ncbi.nlm.nih.gov/articles/PMC8811688/
JAMA / JAMA Cardiology / review on cuffless BP devices (narrative/recommendations 2025). https://jamanetwork.com/journals/jamacardiology/fullarticle/10.1001/jamacardio.2025.0662
Odeh VA, et al. Recent Advances in the Wearable Devices for Monitoring and Management of Heart Failure. PMC (2024). https://pmc.ncbi.nlm.nih.gov/articles/PMC11522764/
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