Impact of artificial intelligence-assisted health management on blood pressure and self-management efficacy in older adults with hypertension
- 1Health Management Center, The First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan, China
- 2Department of Pain, The First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan, China
Abstract
Purpose This paper examined the impacts of artificial intelligence (AI)-assisted health management on blood pressure control and self-management effectiveness in older adults with hypertension.Materials and Methods Two hundred hypertensive patients were randomly assigned to a usual care group (routine health management) or an intervention group (AI-assisted health management, including aspects such as intelligent monitoring, early warning and proactive intervention, among others) (n = 100 each). Primary outcomes included blood pressure control rate (<140/<90 mm Hg) and systolic and diastolic blood pressure (SBP and DBP). Secondary outcomes included improvement in lifestyle behaviors, level of hypertension knowledge awareness, self-management efficacy, medication beliefs, quality of life, and management satisfaction.Results Following one year intervention, the intervention group demonstrated a higher blood pressure control rate than the usual care group (88.66% vs. 64.89%), along with lower SBP (128.49 ± 6.63 vs. 135.38 ± 7.31 mmHg) and DBP (77.49 ± 6.07 vs. 81.84 ± 5.44 mmHg) (all P < 0.05). Additionally, the intervention group showed superior improvements in smoking behavior change, alcohol consumption behavior change, low-salt and low-fat diet adherence, and regular exercise attainment, as well as higher scores on the Hypertension Knowledge-Level Scale, Hypertension Patient Self-Management Behavior Rating Scale, Modified Beliefs about Medicines Questionnaire, physical component summary and the mental component summary, and Client Satisfaction Questionnaire-8 (all P < 0.05).Conclusion AI-assisted health management enhances blood pressure control, and improves self-management capacity, quality of life, and service satisfaction in older adults with hypertension.
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BibTeX
@article{yang2026impact,
title = {{Impact of artificial intelligence-assisted health management on blood pressure and self-management efficacy in older adults with hypertension}},
author = {Xiaorui Yang and Xinyue Huang and Yue Cui and Ke Zhao},
journal = {Blood Pressure},
year = {2026},
month = aug,
doi = {10.1080/08037051.2026.2715847},
url = {https://doi.org/10.1080/08037051.2026.2715847},
note = {CC BY},
}
RIS
TY - JOUR
TI - Impact of artificial intelligence-assisted health management on blood pressure and self-management efficacy in older adults with hypertension
AU - Xiaorui Yang
AU - Xinyue Huang
AU - Yue Cui
AU - Ke Zhao
PY - 2026
DA - 2026/08/01
JO - Blood Pressure
DO - 10.1080/08037051.2026.2715847
UR - https://doi.org/10.1080/08037051.2026.2715847
AB - Purpose This paper examined the impacts of artificial intelligence (AI)-assisted health management on blood pressure control and self-management effectiveness in older adults with hypertension.Materials and Methods Two hundred hypertensive patients were randomly assigned to a usual care group (routine health management) or an intervention group (AI-assisted health management, including aspects such as intelligent monitoring, early warning and proactive intervention, among others) (n = 100 each). Primary outcomes included blood pressure control rate (<140/<90 mm Hg) and systolic and diastolic blood pressure (SBP and DBP). Secondary outcomes included improvement in lifestyle behaviors, level of hypertension knowledge awareness, self-management efficacy, medication beliefs, quality of life, and management satisfaction.Results Following one year intervention, the intervention group demonstrated a higher blood pressure control rate than the usual care group (88.66% vs. 64.89%), along with lower SBP (128.49 ± 6.63 vs. 135.38 ± 7.31 mmHg) and DBP (77.49 ± 6.07 vs. 81.84 ± 5.44 mmHg) (all P < 0.05). Additionally, the intervention group showed superior improvements in smoking behavior change, alcohol consumption behavior change, low-salt and low-fat diet adherence, and regular exercise attainment, as well as higher scores on the Hypertension Knowledge-Level Scale, Hypertension Patient Self-Management Behavior Rating Scale, Modified Beliefs about Medicines Questionnaire, physical component summary and the mental component summary, and Client Satisfaction Questionnaire-8 (all P < 0.05).Conclusion AI-assisted health management enhances blood pressure control, and improves self-management capacity, quality of life, and service satisfaction in older adults with hypertension.
SN - 1651-1999
SN - 0803-7051
ER -