WEARABLE HEALTH TECHNOLOGIES IN PREVENTIVE MEDICINE: SOCIAL, BEHAVIORAL, AND CLINICAL IMPLICATIONS – A LITERATURE REVIEW

Authors

DOI:

https://doi.org/10.31435/ijitss.2(50).2026.5470

Keywords:

Wearable Devices, Digital Health, Health Monitoring, Sleep Tracking, Preventive Medicine, Disease Prevention

Abstract

Research Objective: The purpose of this literature review is to assess the current state of knowledge regarding wearable health technologies and their role in preventive medicine, with particular emphasis on their clinical, behavioral, and social implications. This article focuses on the impact of wearable devices on the cardiovascular system, includingatrial fibrillation detection and sleep monitoring. Furthermore, the impact of these devices on changing patient health behaviors and their integration into the healthcare system was discussed.

Methods: This article is literature review hich synthesizes 33 articles on the impact of wearable devices on sleep monitoring and preventive medicine, particularly cardiovascular diseases. The review focused on themes such as measurement accuracy, clinical applications, technological advancements, and behavioral and social impacts.

Results: Wearable devices are advanced tools capable of continuously monitoring physiological parameters. The integration of sensors, wireless communication technologies, and artificial intelligence enables real-time data collection and predictive analysis. These devices aid in the early detection of cardiovascular abnormalities (e.g., atrial fibrillation), sleep disorders, and metabolic conditions. This article addresses the limitations of measurement accuracy and challenges associated with data interpretation. Furthermore, behavioral benefits are identified, including increased health awareness and motivation for physical activity.

Conclusion: Wearable technologies, thanks to their continuous monitoring capabilities, can be a key to early diagnosis and behavior modification. Their effectiveness depends on technological capabilities, user engagement, and the healthcare system's readiness to integrate patient-generated data. To increase their importance in medicine, we must focus on standardization, algorithm transparency, cybersecurity, and equal access for all users.

References

Alpert, J., Manini, T., Roberts, M., Kota, N., Satya, P., Mendoza, T., Solberg, L., & Rashidi, P. (2020). Secondary care provider attitudes towards patient generated health data from smartwatches. NPJ Digital Medicine, 3, Article 27. https://doi.org/10.1038/s41746-020-0236-4

Asgari Mehrabadi, M., Azimi, I., Sarhaddi, F., Axelin, A., Niela-Vilén, H., Myllyntausta, S., Stenholm, S., Dutt, N., Liljeberg, P., & Rahmani, A. M. (2020). Sleep tracking of a commercially available smart ring and smartwatch against medical-grade actigraphy in everyday settings: Instrument validation study. JMIR mHealth and uHealth, 8(10), Article e20465. https://doi.org/10.2196/20465

Bent, B., Goldstein, B. A., Kibbe, W. A., & Dunn, J. P. (2020). Investigating sources of inaccuracy in wearable optical heart rate sensors. NPJ Digital Medicine, 3, Article 18. https://doi.org/10.1038/s41746-020-0226-6

Berryhill, S., Morton, C. J., Dean, A., Berryhill, A., Provencio-Dean, N., Patel, S. I., Estep, L., Combs, D., Mashaqi, S., Gerald, L. B., Krishnan, J. A., & Parthasarathy, S. (2020). Effect of wearables on sleep in healthy individuals: A randomized crossover trial and validation study. Journal of Clinical Sleep Medicine, 16(5), 775–783. https://doi.org/10.5664/jcsm.8356

Bumgarner, J. M., Lambert, C. T., Hussein, A. A., Cantillon, D. J., Baranowski, B., Wolski, K., Lindsay, B. D., Wazni, O. M., & Tarakji, K. G. (2018). Smartwatch algorithm for automated detection of atrial fibrillation. Journal of the American College of Cardiology, 71(21), 2381–2388.

Canali, S., Schiaffonati, V., & Aliverti, A. (2022). Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness. PLOS Digital Health, 1(10), Article e0000104. https://doi.org/10.1371/journal.pdig.0000104

de Gans, C. J., Burger, P., van den Ende, E. S., Hermanides, J., Nanayakkara, P. W. B., Gemke, R. J. B. J., Rutters, F., & Stenvers, D. J. (2024). Sleep assessment using EEG-based wearables: A systematic review. Sleep Medicine Reviews, 76, Article 101951. https://doi.org/10.1016/j.smrv.2024.101951

de Zambotti, M., Rosas, L., Colrain, I. M., & Baker, F. C. (2019). The sleep of the ring: Comparison of the ŌURA sleep tracker against polysomnography. Behavioral Sleep Medicine, 17(2), 124–136. https://doi.org/10.1080/15402002.2017.1300587

del-Valle-Soto, C., Pimentel, J. C., Castillo, J. V., Nolazco-Flores, J. A., Velázquez, R., Aldás, J. V., & Visconti, P. (2024). A comprehensive review of behavior change techniques in wearables and IoT: Implications for health and well-being. Sensors, 24.

देवी, D. H., Duraisamy, K., Armghan, A., Alsharari, M., Aliqab, K., Sorathiya, V., Das, S., & Rashid, N. (2023). 5G technology in healthcare and wearable devices: A review. Sensors, 23(5), Article 2519. https://doi.org/10.3390/s23052519

Dias, D., & Cunha, J. P. S. (2018). Wearable health devices: Vital sign monitoring, systems and technologies. Sensors, 18(8), Article 2414. https://doi.org/10.3390/s18082414

Im, E., Kang, S., & Kim, H. (2025). Development of a validation and inspection tool for armband-based lifelog data (VITAL) to facilitate the clinical use of wearable data: A prototype and usability evaluation. arXiv. https://doi.org/10.48550/arXiv.2501.14133

Zhang, F. (2025). Progress in health monitoring smart wearable devices: A review. Theoretical and Natural Science, 119(1), 118–128. https://doi.org/10.54254/2753-8818/2025.AU24710

Girginov, V., Moore, P. J., Olsen, N., Godfrey, T., & Cooke, F. P. (2020). Wearable technology-stimulated social interaction for promoting physical activity: A systematic review. Cogent Social Sciences, 6.

Guillodo, E., Lemey, C., Simonnet, M., Walter, M., Baca-García, E., Masetti, V., Moga, S., Larsen, M., HUGOPSY Network, Ropars, J., & Berrouiguet, S. (2020). Clinical applications of mobile health wearable-based sleep monitoring: Systematic review. JMIR mHealth and uHealth, 8(4), Article e10733.

Henriksen, A., Svartdal, F., Grimsgaard, S., Hartvigsen, G., & Hopstock, L. A. (2022). Polar Vantage and Oura physical activity and sleep trackers: Validation and comparison study. JMIR Formative Research, 6(5), Article e27248. https://doi.org/10.2196/27248

Keesara, S., Jonas, A., & Schulman, K. (2020). Covid-19 and health care’s digital revolution. The New England Journal of Medicine, 382(23), Article e82. https://doi.org/10.1056/NEJMp2005835

Lobo, P., Morais, P., Murray, P., & Vilaça, J. L. (2024). Trends and innovations in wearable technology for motor rehabilitation, prediction, and monitoring: A comprehensive review. Sensors, 24(24), Article 7973. https://doi.org/10.3390/s24247973

Masoumian Hosseini, M., Masoumian Hosseini, S. T., Qayumi, K., Hosseinzadeh, S., & Sajadi Tabar, S. S. (2023). Smartwatches in healthcare medicine: Assistance and monitoring; a scoping review. BMC Medical Informatics and Decision Making, 23(1), Article 248. https://doi.org/10.1186/s12911-023-02350-w

Miao, F., Wu, D., Liu, Z., Zhang, R., Tang, M., & Li, Y. (2023). Wearable sensing, big data technology for cardiovascular healthcare: Current status and future prospective. Chinese Medical Journal, 136(9), 1015–1025. https://doi.org/10.1097/CM9.0000000000002117

Miller, D. J., Sargent, C., & Roach, G. D. (2022). A validation of six wearable devices for estimating sleep, heart rate and heart rate variability in healthy adults. Sensors, 22(16), Article 6317. https://doi.org/10.3390/s22166317

O’Reilly-Shah, V., & Mackey, S. (2016). Survalytics: An open-source cloud-integrated experience sampling, survey, and analytics and metadata collection module for Android operating system apps. JMIR mHealth and uHealth, 4(2), Article e46. https://doi.org/10.2196/mhealth.5397

Pennington, N., & Dam, L. (2023). Social interaction, support preferences, and the use of wearable health trackers. Frontiers in Communication. https://doi.org/10.3389/fcomm.2023.1256452

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

Piwek, L., Ellis, D. A., Andrews, S., & Joinson, A. (2016). The rise of consumer health wearables: Promises and barriers. PLOS Medicine, 13(2), Article e1001953. https://doi.org/10.1371/journal.pmed.1001953

Rieder, A., Eseryel, U. Y., Lehrer, C., & Jung, R. (2021). Why users comply with wearables: The role of contextual self-efficacy in behavioral change. International Journal of Human-Computer Interaction, 37(3), 281–294.

Robbins, R., Weaver, M. D., Sullivan, J. P., Quan, S. F., Gilmore, K., Shaw, S., Benz, A., Qadri, S., Barger, L. K., Czeisler, C. A., & Duffy, J. F. (2024). Accuracy of three commercial wearable devices for sleep tracking in healthy adults. Sensors, 24(20), Article 6532. https://doi.org/10.3390/s24206532

Sathyanarayana, A., Ofli, F., Fernández-Luque, L., Srivastava, J., Elmagarmid, A. K., Arora, T., & Taheri, S. (2016). Robust automated human activity recognition and its application to sleep research. IEEE ICDMW, 495–502.

Schyvens, A. M., Peters, B., Van Oost, N. C., Aerts, J. M., Masci, F., Neven, A., Dirix, H., Wets, G., Ross, V., & Verbraecken, J. (2025). A performance validation of six commercial wrist-worn wearable sleep-tracking devices for sleep stage scoring compared to polysomnography. Sleep Advances, 6(2), Article zpaf021. https://doi.org/10.1093/sleepadvances/zpaf021

South, B. R., Mowery, D., Suo, Y., Leng, J., Ferrández, Ó., Meystre, S. M., & Chapman, W. W. (2014). Evaluating the effects of machine pre-annotation and an interactive annotation interface on manual de-identification of clinical text. Journal of Biomedical Informatics, 50, 162–172. https://doi.org/10.1016/j.jbi.2014.05.002

Sun, Y., Chen, J., Ji, M., & Li, X. (2025). Wearable technologies for health promotion and disease prevention in older adults: Systematic scoping review and evidence map. Journal of Medical Internet Research, 27, Article e69077. https://doi.org/10.2196/69077

Vo, D. K., & Trinh, K. T. L. (2024). Advances in wearable biosensors for healthcare: Current trends, applications, and future perspectives. Biosensors, 14(11), Article 560. https://doi.org/10.3390/bios14110560

Webb, M. J., Wadley, G., & Sanci, L. A. (2018). Experiences of general practitioners and practice support staff using a health and lifestyle screening app in primary health care: Implementation case study. JMIR mHealth and uHealth, 6(4), Article e105. https://doi.org/10.2196/mhealth.8778

Downloads

Published

2026-06-08

How to Cite

Polewczak Karp, E. M., Szwed, A. ., Sołtys, A., Warzocha-Żurek, D. A. ., Borzęcka , K. A. ., Wawrzonek, K. ., Andryszko, K., Dymon, M. ., Ziemba-Furgała, N. M. ., & Krysa, P. . (2026). WEARABLE HEALTH TECHNOLOGIES IN PREVENTIVE MEDICINE: SOCIAL, BEHAVIORAL, AND CLINICAL IMPLICATIONS – A LITERATURE REVIEW. International Journal of Innovative Technologies in Social Science, 2(2(50). https://doi.org/10.31435/ijitss.2(50).2026.5470

Most read articles by the same author(s)