Hypertension Prevention and ManagementNCT07147413
Digital Health Platform Blood Pressure Management Study
A study testing Behavioral/Digital Health Intervention in people with Hypertension Prevention and Management, run by Taipei Veterans General Hospital, Taiwan at 1 site in Taiwan.
Trial summary
This pilot study evaluated the effectiveness of an AI health education assistant compared to case manager support in hypertension management. Key outcomes included changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP), compliance with health behaviors, 722 goal achievement (monitoring… Read more about this study
- Who is it for?
- Ages 18 to 75 yearsHealthy volunteers can take part
- Conditions the study is for
- Hypertension Prevention and Management
- What is being tested?
- Behavioral/Digital Health Intervention
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 1,726 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Sep 2025to 31 Dec 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 75 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Participants must meet all of the following criteria:
- Aged 18 to 75 years at the time of enrollment
- Able and willing to provide informed consent
- Able to operate a mobile phone and interact with the digital platform
- Willing to participate in home blood pressure monitoring
Who cannot join
- Participants will be excluded if they meet any of the following criteria:
- Systolic BP consistently <120 mmHg and diastolic BP <70 mmHg, based on baseline home monitoring (considered low BP not targeted in this study)
- Pregnant or planning to become pregnant during the study period
- Unable to operate a smartphone or digital device independently
- Cognitive impairment or language barrier that prevents understanding of study procedures or informed consent
- Severe comorbidities that may interfere with study participation or outcomes (e.g., advanced heart failure, end-stage renal disease)
- Current participation in another interventional clinical study that could conflict with this protocol
- Unwillingness to follow home blood pressure monitoring protocol or adhere to follow-up schedule
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Taiwan1 site, 1 recruiting
- Recruiting
Taipei Veterans General Hospital
Taipei
Hao-Min Cheng, hmcheng@vghtpe.gov.tw
About this study
This pilot study evaluated the effectiveness of an AI health education assistant compared to case manager support in hypertension management. Key outcomes included changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP), compliance with health behaviors, 722 goal achievement (monitoring, measurements, lifestyle improvements), and Technology Acceptance Model (TAM) metrics, including perceived usefulness (PU), perceived ease of use (PEU), and behavioral intention (BI). This study aims to examine whether the AI assistant group will achieve greater reductions in systolic and diastolic blood pressure compared to the case manager group. Additionally, it will evaluate whether the AI assistant group will demonstrate higher engagement in 722 goals and greater perceived ease of use. The results of this study are expected to provide further evidence supporting the potential of AI-driven interventions.
Read the detailed description
Background: This pilot study aimed to evaluate the effectiveness of an AI health education assistant compared with case manager support in managing hypertension. The primary focus was on changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP), compliance with health behaviors, engagement in 722 goal achievement (monitoring, measurements, and lifestyle improvements), and Technology Acceptance Model (TAM) metrics, including perceived usefulness (PU), perceived ease of use (PEU), and behavioral intention (BI). This study aims to examine whether the AI assistant group will achieve greater reductions in systolic and diastolic blood pressure compared to the case manager group. Additionally, it will evaluate whether the AI assistant group will demonstrate higher engagement in 722 goals and greater perceived ease of use.
Methods: This two-arm, randomized controlled pilot study enrolled participants aged 18-75 years with hypertension. Participants were allocated to either the AI health education assistant group or the case manager group. The AI group received app-based interventions, including medication reminders, behavioral nudges, educational quizzes, and abnormal blood pressure alerts powered by AI-driven monitoring. The case manager group received personalized lifestyle advice, medication reminders, and regular follow-ups from human case managers. Blood pressure readings were collected at baseline and 6 months, and TAM metrics were assessed through questionnaires. Compliance with health behaviors and engagement in 722 goals were evaluated through app interaction logs. The sample size was determined based on a non-inferiority design comparing two independent groups. The primary outcome was the change in systolic blood pressure (SBP), which was defined as the post-intervention value minus the pre-intervention value. A one-sided significance level of 0.05 and a statistical power of 80% were assumed. The sample size calculation used a pooled standard deviation of 11.6 mmHg derived from the pilot study. A non-inferiority margin of 3 mmHg and an expected mean difference of 1.34 mmHg between the AI intervention group and the control group were also assumed. The required sample size was estimated to be 604 participants per group. After allowing for a 30% dropout rate, 863 participants will be required in each group, resulting in a total sample size of 1,726 participants for the two groups. Statistical analyses included paired t-tests for within-group changes, independent t-tests for between-group comparisons, and linear regression models to assess associations between intervention type and TAM metrics, adjusting for baseline values.
Discussion: This study will provide preliminary evidence on the feasibility and potential benefits of AI-driven interventions for hypertension management. It will further evaluate the AI assistant's ability to improve blood pressure control, increase engagement in 722 goals, and enhance technology acceptance. These findings will deliver important insights for clinicians and inform future clinical practice.
- Conditions
- Hypertension Prevention and Management
- Being tested
- Behavioral/Digital Health Intervention
- Keywords
- Hypertension, Blood pressure, Prevention, Management
- Medical subject headings
- Hypertension
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Behavioral/Digital Health InterventionBehavioural
Participants in this group will utilize an AI-powered digital health management platform designed to optimize blood pressure control. The platform provides personalized medication and blood pressure measurement reminders, tailored health education, and interactive quizzes to improve hypertension awareness and engagement. Data from blood pressure monitors will be scanned and uploaded, and the system will alert participants and case managers to abnormal readings, enabling timely interventions.
| Study group | Role | What they receive |
|---|---|---|
| AI assistant | Experimental | The AI group received app-based interventions, including medication reminders, behavioral nudges, educational quizzes, and abnormal blood pressure alerts powered by AI-driven monitoring. Receives: Behavioral: Behavioral/Digital Health Intervention |
| Case manager | No intervention | The case manager group received personalized lifestyle advice, medication reminders, and regular follow-ups from human case managers. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Reduction in Systolic and Diastolic Blood Pressure at 6 Months by Home Blood Pressure Monitoring
Change in average systolic and diastolic blood pressure (SBP and DBP) from baseline to 6 months, measured using validated automated home blood pressure monitors. Participants will follow the 722 protocol (2 readings per occasion, twice daily, over 7 consecutive days). Data are collected via the digital health platform and automatically uploaded. Outcome is calculated as the difference in mean SBP between baseline and 6-month readings. [Unit of Measure: mmHg]; [Method of Assessment: Home blood pressure monitoring (HBPM) using certified devices (certified by Taiwan FDA)]
Measured: 6 months
Secondary outcomes (4)
Reduction in Systolic and Diastolic Blood Pressure at 12 Months by Home Blood Pressure Monitoring
Change in average systolic and diastolic blood pressure (SBP and DBP) from baseline to 12 months, measured using validated automated home blood pressure monitors. Participants will follow the 722 protocol (2 readings per occasion, twice daily, over 7 consecutive days). Data are collected via the digital health platform and automatically uploaded. Outcome is calculated as the difference in mean SBP between baseline and 6-month readings. [Unit of Measure: mmHg]; [Method of Assessment: Home blood pressure monitoring (HBPM) using certified devices (certified by Taiwan FDA)]
Measured: 12 months
Improvement in Hypertension Knowledge, Attitudes, and Behaviors (KAB)
Change in participants' scores on a validated Hypertension Knowledge, Attitudes, and Behaviors (KAB) questionnaire between baseline and 6-month follow-up. The questionnaire assesses understanding of blood pressure management, behavioral intentions, and lifestyle practices. Statistical evaluation using Wilcoxon Signed-Rank Test. [Unit of Measure: Score on KAB questionnaire]; [Method of Assessment: Structured questionnaire administered digitally before and after intervention]
Measured: 6 months
Adherence to 722 Blood Pressure Monitoring Protocol and Medication Compliance
Proportion of participants who complete home blood pressure monitoring in accordance with the 722 protocol and demonstrate adherence to their prescribed antihypertensive medication regimen.
- BP Monitoring Adherence: At least 2 measurements per occasion, twice daily (morning and evening), for 7 consecutive days.
- Medication Compliance: Taking prescribed antihypertensive medication(s) as directed (correct dosage and frequency) over the same monitoring periods.
Adherence is defined as meeting both criteria at baseline and again at 6 months. This measure reflects participants' engagement with blood pressure self-monitoring behaviors and their consistency in following prescribed treatment.
[Unit of Measure: Percentage of participants]; [Method of Assessment:
- App-based log review of BP measurements synced from devices.
- Medication adherence assessed via app-based self-reports.]
Measured: 6 months
Change in Time in Therapeutic Range (TTR) for Systolic Blood Pressure
Change in the proportion of days during which a participant's home systolic blood pressure readings are within the target range (110-130 mmHg) over a 7-day observation period at baseline and at 6 months. TTR is calculated as the number of days with SBP within target range divided by total valid measurement days (minimum of 4 valid days required per observation period). Improvement in TTR reflects better blood pressure stability.
[Unit of Measure: Percentage of days in target range]; [Method of Assessment: Home blood pressure monitor data uploaded via app and analyzed based on Taiwan Hypertension Society's TTR definition]
Measured: Baseline and 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Aug 2025
- Study start1 Sep 2025
- Primary completion31 Dec 2027 (estimated)
- Study completion31 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Hypertension Prevention and ManagementStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 1,726 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Taipei Veterans General Hospital, Taiwan
- Sponsor type
- Other government
- Collaborators
- Ministry of Health and Welfare, Taiwan
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07147413
- Sponsor's protocol ID
- 2024-07-021BCF
- Status last verified
- Jul 2026
- First submitted
- 21 Jul 2025
- Last updated
- 15 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 15 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Digital Health Platform Blood Pressure Management Study
- ClinicalTrials.gov ID
- NCT07147413
- Acronym / sponsor ID
- 2024-07-021BCF
- Conditions
- Hypertension Prevention and Management
- Keywords
- Hypertension, Blood pressure, Prevention, Management
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 1,726 participants (estimated)
- Lead sponsor
- Taipei Veterans General Hospital, TaiwanOther government
- Collaborators
- Ministry of Health and Welfare, Taiwan
- Study start
- 1 Sep 2025 (actual)
- Primary completion
- 31 Dec 2027 (estimated)
- Study completion
- 31 Dec 2027 (estimated)
- First posted
- 29 Aug 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This pilot study evaluated the effectiveness of an AI health education assistant compared to case manager support in hypertension management. Key outcomes included changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP), compliance with health behaviors, 722 goal achievement (monitoring, measurements, lifestyle improvements), and Technology Acceptance Model (TAM) metrics, including perceived usefulness (PU), perceived ease of use (PEU), and behavioral intention (BI). This study aims to examine whether the AI assistant group will achieve greater reductions in systolic and diastolic blood pressure compared to the case manager group. Additionally, it will evaluate whether the AI assistant group will demonstrate higher engagement in 722 goals and greater perceived ease of use. The results of this study are expected to provide further evidence supporting the potential of AI-driven interventions.
Detailed description
Background: This pilot study aimed to evaluate the effectiveness of an AI health education assistant compared with case manager support in managing hypertension. The primary focus was on changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP), compliance with health behaviors, engagement in 722 goal achievement (monitoring, measurements, and lifestyle improvements), and Technology Acceptance Model (TAM) metrics, including perceived usefulness (PU), perceived ease of use (PEU), and behavioral intention (BI). This study aims to examine whether the AI assistant group will achieve greater reductions in systolic and diastolic blood pressure compared to the case manager group. Additionally, it will evaluate whether the AI assistant group will demonstrate higher engagement in 722 goals and greater perceived ease of use.
Methods: This two-arm, randomized controlled pilot study enrolled participants aged 18-75 years with hypertension. Participants were allocated to either the AI health education assistant group or the case manager group. The AI group received app-based interventions, including medication reminders, behavioral nudges, educational quizzes, and abnormal blood pressure alerts powered by AI-driven monitoring. The case manager group received personalized lifestyle advice, medication reminders, and regular follow-ups from human case managers. Blood pressure readings were collected at baseline and 6 months, and TAM metrics were assessed through questionnaires. Compliance with health behaviors and engagement in 722 goals were evaluated through app interaction logs. The sample size was determined based on a non-inferiority design comparing two independent groups. The primary outcome was the change in systolic blood pressure (SBP), which was defined as the post-intervention value minus the pre-intervention value. A one-sided significance level of 0.05 and a statistical power of 80% were assumed. The sample size calculation used a pooled standard deviation of 11.6 mmHg derived from the pilot study. A non-inferiority margin of 3 mmHg and an expected mean difference of 1.34 mmHg between the AI intervention group and the control group were also assumed. The required sample size was estimated to be 604 participants per group. After allowing for a 30% dropout rate, 863 participants will be required in each group, resulting in a total sample size of 1,726 participants for the two groups. Statistical analyses included paired t-tests for within-group changes, independent t-tests for between-group comparisons, and linear regression models to assess associations between intervention type and TAM metrics, adjusting for baseline values.
Discussion: This study will provide preliminary evidence on the feasibility and potential benefits of AI-driven interventions for hypertension management. It will further evaluate the AI assistant's ability to improve blood pressure control, increase engagement in 722 goals, and enhance technology acceptance. These findings will deliver important insights for clinicians and inform future clinical practice.
Study design
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (participant)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI assistant | Experimental | Behavioral: Behavioral/Digital Health InterventionThe AI group received app-based interventions, including medication reminders, behavioral nudges, educational quizzes, and abnormal blood pressure alerts powered by AI-driven monitoring. |
| Case manager | No intervention | –The case manager group received personalized lifestyle advice, medication reminders, and regular follow-ups from human case managers. |
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- Aged 18 to 75 years at the time of enrollment
- Able and willing to provide informed consent
- Able to operate a mobile phone and interact with the digital platform
- Willing to participate in home blood pressure monitoring
Key exclusion criteria (8 listed)
- Systolic BP consistently <120 mmHg and diastolic BP <70 mmHg, based on baseline home monitoring (considered low BP not targeted in this study)
- Pregnant or planning to become pregnant during the study period
- Unable to operate a smartphone or digital device independently
- Cognitive impairment or language barrier that prevents understanding of study procedures or informed consent
- Severe comorbidities that may interfere with study participation or outcomes (e.g., advanced heart failure, end-stage renal disease)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Behavioral/Digital Health InterventionParticipants in this group will utilize an AI-powered digital health management platform designed to optimize blood pressure control. The platform provides personalized medication and blood pressure measurement reminders, tailored health education, and interactive quizzes to improve hypertension awareness and engagement. Data from blood pressure monitors will be scanned and uploaded, and the system will alert participants and case managers to abnormal readings, enabling timely interventions. | Behavioural | AI assistant |
Primary outcome
Reduction in Systolic and Diastolic Blood Pressure at 6 Months by Home Blood Pressure Monitoring
Time frame: 6 months
Change in average systolic and diastolic blood pressure (SBP and DBP) from baseline to 6 months, measured using validated automated home blood pressure monitors. Participants will follow the 722 protocol (2 readings per occasion, twice daily, over 7 consecutive days). Data are collected via the digital health platform and automatically uploaded. Outcome is calculated as the difference in mean SBP between baseline and 6-month readings. [Unit of Measure: mmHg]; [Method of Assessment: Home blood pressure monitoring (HBPM) using certified devices (certified by Taiwan FDA)]
4 secondary outcomes
Reduction in Systolic and Diastolic Blood Pressure at 12 Months by Home Blood Pressure Monitoring
Time frame: 12 months
Improvement in Hypertension Knowledge, Attitudes, and Behaviors (KAB)
Time frame: 6 months
Adherence to 722 Blood Pressure Monitoring Protocol and Medication Compliance
Time frame: 6 months
Change in Time in Therapeutic Range (TTR) for Systolic Blood Pressure
Time frame: Baseline and 6 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Jul 2026.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Behavioral/Digital Health Intervention in people with Hypertension Prevention and Management, run by Taipei Veterans General Hospital, Taiwan at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 15 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Hao-Min Cheng (886-2-28757302, hmcheng@vghtpe.gov.tw), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Reduction in Systolic and Diastolic Blood Pressure at 6 Months by Home Blood Pressure Monitoring (time frame: 6 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Jul 2026.