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This study evaluates the impact of a fully digital, autonomous, and artificial intelligence (AI)-driven lifestyle coaching program on managing blood pressure (BP) among adults diagnosed with hypertension. Participants received a BP monitor and a wearable activity tracker to facilitate data collection. This data, along with responses from a questionnaire mobile app, were analyzed by an automated analytics engine employing statistical and machine learning techniques. The program delivered tailored lifestyle coaching directly to participants through a mobile app, aiming for precise and effective BP management.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| AI-Driven Lifestyle Coaching Group | Experimental |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI-Driven Lifestyle Coaching Program | Behavioral | The intervention provides participants with automated and personalized lifestyle recommendations involving a sophisticated analytics engine using advanced statistics and machine learning. |
| Measure | Description | Time Frame |
|---|---|---|
| Average change in systolic blood pressure (SBP) from baseline to 12 weeks | 12 weeks | |
| Average change in diastolic blood pressure (DBP) from baseline to 12 weeks | 12 weeks | |
| Average change in SBP from baseline to 24 weeks | 24 weeks | |
| Average change in DBP from baseline to 24 weeks | 24 weeks | |
| Percent change of participants with controlled BP (SBP<130 and DBP<80) from baseline to 12 weeks | 12 weeks | |
| Percent change of participants with controlled BP (SBP<130 and DBP<80) from baseline to 24 weeks | 24 weeks | |
| Percent change of participants with Stage 2 Hypertension (SBP≥140 or DBP≥90) from baseline to 12 weeks | 12 weeks | |
| Percent change of participants with Stage 2 Hypertension (SBP≥140 or DBP≥90) from baseline to 24 weeks | 24 weeks |
| Measure | Description | Time Frame |
|---|---|---|
| Average weekly percentage of active participants measuring their BP | 24 weeks | |
| Average weekly percentage of active participants syncing their wearable | 24 weeks | |
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Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of California, San Diego | La Jolla | California | 92093 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 38805253 | Derived | Leitner J, Chiang PH, Agnihotri P, Dey S. The Effect of an AI-Based, Autonomous, Digital Health Intervention Using Precise Lifestyle Guidance on Blood Pressure in Adults With Hypertension: Single-Arm Nonrandomized Trial. JMIR Cardio. 2024 May 28;8:e51916. doi: 10.2196/51916. |
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| ID | Term |
|---|---|
| D006973 | Hypertension |
| ID | Term |
|---|---|
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
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| Average weekly percentage of active participants answering the mobile app questionnaire |
| 24 weeks |
| Number of manual clinician outreaches based on the escalation rules set for the study | 24 weeks |