Wearable-Integrated Education and Its Association with Self-Management and Quality of Life Among Patients with Hypertension: A Quasi-Experimental Study
Abstract
Introduction: Hypertension is a leading global health concern requiring sustained self-management to prevent complications and improve quality of life. While digital health interventions are increasingly adopted, evidence on the effectiveness of wearable-integrated education in hypertension management remains limited.
Objective: This study aimed to evaluate the effectiveness of wearable-integrated education on self-management behaviors and quality of life in patients with hypertension.
Methods: A quasi-experimental study was conducted with 200 hypertensive patients recruited from community health centers. Participants were allocated into an intervention group (n = 100), which received wearable-integrated educational modules providing personalized feedback and reminders, and a control group (n = 100), which received standard health education. Outcomes included self-management, measured using the Hypertension Self-Management Behavior Questionnaire (HSMBQ), and quality of life, assessed with the WHOQOL-BREF. Descriptive, correlation, and multivariate regression analyses were performed.
Results: Participants had a mean age of 54.2 years (SD = 9.1), with no significant baseline differences between groups. Post-intervention, the intervention group reported significantly higher self-management scores (78.4 ± 8.6 vs. 70.2 ± 9.1; p < 0.001) and quality of life scores (82.6 ± 10.2 vs. 75.1 ± 11.0; p < 0.001) compared with controls. Correlation analyses indicated that higher education, shorter duration of hypertension, and intervention participation were positively associated with outcomes. Multivariate regression confirmed the intervention as an independent predictor of both self-management (β = 0.39, p < 0.001) and quality of life (β = 0.36, p < 0.001), with models explaining 29% and 26% of the variance, respectively.
Conclusion: Wearable-integrated education significantly improves self-management behaviors and quality of life among hypertensive patients. These findings highlight the potential of integrating wearable technology with educational strategies as a scalable, community nursing–driven approach to hypertension managementKeywords
References
Anisah, S. N., & Djuwita, R. (2019). Reliability and validity of WHOQOL BREF into Indonesian version as a measure of quality of life of tuberculosis patients. Indian Journal of Public Health Research and Development, 10(12), 1972–1977. https://doi.org/10.37506/v10/i12/2019/ijphrd/192160
Baral, N., Volgman, A. S., Seri, A., Chelikani, V., Isa, S., Javvadi, S. L. P., Paul, T. K., & Mitchell, J. D. (2023). Adding pharmacist-led home blood pressure telemonitoring to usual care for blood pressure control: A systematic review and meta-analysis. American Journal of Cardiology, 203, 161–168. https://doi.org/10.1016/j.amjcard.2023.06.109
Boima, V., Denneson, L. M., Agyemang, C., & Agyei-Baffour, P. (2024). Effectiveness of digital health interventions on blood pressure control, lifestyle behaviours and medication adherence in low- and middle-income countries: Systematic review and meta-analysis of randomized controlled trials. EClinicalMedicine, 69, 102299. https://doi.org/10.1016/j.eclinm.2024.102299
Karami, M., Ashtarian, H., Rajati, M., Hamzeh, B., & Rajati, F. (2023). The effect of health literacy intervention on adherence to medication of uncontrolled hypertensive patients using M-health. BMC Medical Informatics and Decision Making, 23, 289. https://doi.org/10.1186/s12911-023-02393-z
Katz, M. E., Mszar, R., Grimshaw, A. A., Gunderson, C. G., Onuma, O. K., Lu, Y., & Spatz, E. S. (2024). Digital health interventions for hypertension management in U.S. populations experiencing health disparities: A systematic review and meta-analysis. JAMA Network Open, 7, e2450399. https://doi.org/10.1001/jamanetworkopen.2024.50399
Konlan, K. D., & Shin, J. (2023). Determinants of self-care and home-based management of hypertension: An integrative review. Global Heart, 18(1), 73. https://doi.org/10.5334/gh.1190
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
NCD Risk Factor Collaboration (NCD-RisC). (2021). Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: A pooled analysis of 1201 population-representative studies with 104 million participants. The Lancet, 398(10304), 957–980. https://doi.org/10.1016/S0140-6736(21)01330-1
Omboni, S. (2019). Connected health in hypertension management. Frontiers in Cardiovascular Medicine, 6, 76. https://doi.org/10.3389/fcvm.2019.00076
Rojanasumapong, A., Jiraporncharoen, W., Nantsupawat, N., Gilder, M. E., Angkurawaranon, C., & Pinyopornpanish, K. (2021). Internet use, electronic health literacy, and hypertension control among the elderly at an urban primary care center in Thailand: A cross-sectional study. International Journal of Environmental Research and Public Health, 18(18), 9574. https://doi.org/10.3390/ijerph18189574
Sadeghi, M., Molazem, Z., & Mokhtari-Nouri, J. (2022). Effect of a continuous care model on quality of life in patients with hypertension: A randomized controlled clinical trial. BMC Primary Care, 23(1), 265. https://doi.org/10.1186/s12875-022-01798-5
Siopis, G., Cheema, B. S., & Lambert, G. W. (2023). Effectiveness, reach, uptake, and feasibility of digital health interventions for adults with hypertension: Systematic review and meta-analysis. The Lancet Digital Health, 5(3), e144–e159. https://doi.org/10.1016/S2589-7500(22)00226-3
Wang, Y., Tan, J., Zhao, J., Wang, T., Ma, T., Shao, L., & Sun, W. (2025). Wearable devices as tools for better hypertension management in elderly patients. Medical Science Monitor, 31, e946079. https://doi.org/10.12659/MSM.946079
World Health Organization. (2021). Guideline for the pharmacological treatment of hypertension in adults. World Health Organization. (ISBN: 978-92-4-003398-6). Zhou, Y., Li, S.-J., Huang, R.-Q., Ma, H.-M., Wang, A.-Q., Tang, X.-Y., Pei, R.-Y., & Piao, M.-H. (2024). Behavior change techniques used in self-management interventions based on mHealth apps for adults with hypertension: Systematic review and meta-analysis of randomized controlled trials. Journal of Medical Internet Research, 26, e54978. https://doi.org/10.2196/54978
Wu, S.-S., Tu, X.-M., Mou, G.-Q., Long, C.-H., & Li, S.-S. (2025). Effectiveness of mobile health interventions on management of patients with hypertension: A systematic review of systematic reviews. Frontiers of Nursing, 12(1), 1–12. https://doi.org/10.2478/FON-2025-0001
Zhang, Y., Tan, X., & Wang, Q. (2023). Effectiveness of a mHealth intervention on hypertension control in a low-resource rural setting: A randomized clinical trial. Frontiers in Public Health, 11, 1049396. https://doi.org/10.3389/fpubh.2023.1049396
Zhao, Q., Tang, H., et al. (2012). Hypertensive Patient Self Management Scale: 21 items across four domains (treatment, diet/exercise, lifestyle, risk factor management); Cronbach’s α = 0.854; Validity: KMO = 0.703, CVI = 0.875–1, ICC = 0.767
DOI: https://doi.org/10.17509/jpki.v12i1.91277
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