Effect of Digital Intervention on Self-management of Hypertensive Patients at High Risk of Stroke

Official title

Digital Intervention Based on BCW Theory Has a High Blood Pressure in High-risk Population of Stroke Study on the Effect of Stress on Self-management Behavior of Patients

Overview

Stroke is the second leading cause of death in the world, and the number of stroke patients in China ranks the first in the world. Hypertension is the most important risk factor. Studies have shown that 80% of stroke can be prevented by controlling risk factors. However, the management level of hypertension patients in China is still low, and their self-management ability is insufficient. Digital health management, such as remote monitoring, AI and mobile health platforms, provides a new way for hypertension prevention and control. Foreign studies have shown that digital interventions can effectively improve patients' self-management behaviors, such as diet, exercise and blood pressure control. Interventions based on wechat, APP and other tools in China have also achieved positive results, but face challenges such as patient acceptance, system adaptation and data continuity. Based on behavior change wheel (BCW) theory \*\* and digital platform, this study formulated personalized intervention programs for hypertension patients in high-risk groups of stroke, and promoted health behavior change from three aspects of \*\* ability, motivation and opportunity \*\*. By improving disease cognition and strengthening self-management, the incidence of stroke can be ultimately reduced, and a new strategy for hypertension prevention and control in the community can be provided.

Interventions

• Device Digital intervention has a high blood pressure in the high-risk population of stroke Study on the effect of stress on self-management behavior of patients
  Intervention group (n = 60) : Interventions were developed for five behavioral problems, as follows: 1. Lack of knowledge about hypertension \- Measures: APP push knowledge (risk factors, medication, lifestyle, etc.), blood pressure monitoring teaching, monthly online lectures, regular feedback and encouragement of blood pressure data. 2. Poor medication compliance \- Measures: Medication reminders were set by the APP, and repeated and recorded when no medication was taken. 3. Obesity/o

Primary outcome measures

• Hypertension Self-Management Behavior Rating Scale (HPSMBRS) [Time frame: From the beginning of enrollment to the end 6 months later]
• Hypertension Knowledge Scale (HK-LS) [Time frame: From the beginning of enrollment to the end 6 months later]
• Stroke premonitory symptom alertness assessment questionnaire [Time frame: From the beginning of enrollment to the end 6 months later]
• Self-rating Depression Scale (PHQ-9) [Time frame: From the beginning of enrollment to the end 6 months later]
• Generalized Anxiety Disorder-7 (GAD-7) [Time frame: From the beginning of enrollment to the end 6 months later]

Secondary outcome measures (6)

• Blood Pressure (mmHg) [Time frame: From the beginning of enrollment to the end 6 months later]
• Blood lipid (mmol/L) [Time frame: From the beginning of enrollment to the end 6 months later]
• Fasting blood glucose (mmol/L) [Time frame: From the beginning of enrollment to the end 6 months later]
• Glycosylated hemoglobin (HbA1c)(%) [Time frame: From the beginning of enrollment to the end 6 months later]
• Blood homocysteine (Hcy) (mmol/L) [Time frame: From the beginning of enrollment to the end 6 months later]
• Is the risk of stroke reduced? : Risk prediction for atherosclerotic cardiovascular disease in China Prediction for ASCVD Risk in China, China-PAR [Time frame: From the beginning of enrollment to the end 6 months later]

Eligibility criteria

Inclusion criteria

(1) hypertensive patients at high risk of stroke screened in the National Screening and Intervention Project for High-risk Population of Stroke (2) willing to participate Cooperate and sign the informed consent form

Exclusion criteria

(1) TIA and stroke patients (2) severe cognitive impairment (MMSE≤9) and (3) inability to use smartphones (4) Refusal to participate

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation

Randomized

Model

Parallel assignment

Masking

Open label

Primary purpose

Prevention

Study locations

Center list to be confirmed — check the primary protocol.

Identifiers

NCT: NCT07089810 · 2025-K116-01

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗