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Record W2906320679 · doi:10.2196/12601

Improving Blood Pressure Among African Americans With Hypertension Using a Mobile Health Approach (the MI-BP App): Protocol for a Randomized Controlled Trial

2018· article· en· W2906320679 on OpenAlexvenueno aff
Lorraine R Buis, Katee Dawood, Reema Kadri, Rachelle Dawood, Caroline R. Richardson, Zora Djurić, Ananda Sen, Melissa Plegue, David W. Hutton, Aaron Brody, Candace D. McNaughton, Robert D. Brook, Phillip D. Levy

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood Institute
KeywordsmHealthMedicineAfrican americanPsychological interventionEthnic groupGerontologyBlood pressurePopulationAmbulatory blood pressureHealth careProtocol (science)Randomized controlled trialEmergency departmentPublic healthFamily medicineAlternative medicineNursingEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: African Americans shoulder significant disparities related to hypertension (HTN), which is a serious public health problem in the city of Detroit, Michigan, where more than 80% of the population is African American. Connectivity through smartphones, use of home blood pressure (BP) monitoring, and newly developed mobile health (mHealth) interventions can facilitate behavioral changes and may improve long-term self-care for chronic conditions, but implementation of a combined approach utilizing these methods has not been tested among African American patients with uncontrolled HTN. Since African Americans are more likely than other racial or ethnic subgroups to utilize the emergency department (ED) for ambulatory care, this presents an opportunity to intervene on a population that is otherwise difficult to reach. OBJECTIVE: The MI-BP app aims to reduce health disparities related to HTN in the community by employing a user-centered intervention focused on self-BP monitoring, physical activity, reduced sodium intake, and medication adherence. We seek to test the efficacy of MI-BP, an mHealth app for HTN self-management, on BP control (primary aim), physical activity, sodium intake, and medication adherence (secondary aim) in African Americans with HTN. This study also seeks to evaluate the cost-effectiveness of MI-BP when compared with usual care methods. METHODS: This is a 1-year randomized controlled trial that will recruit individuals who have uncontrolled HTN from 2 EDs in the city of Detroit, with a planned sample size of 396 randomized participants. To be eligible for inclusion, potential participants must be African American, 25 to 70 years old, previously diagnosed with HTN, have a smartphone compatible with MI-BP, and have uncontrolled BP at triage and on repeat measurement at least 1-hour post triage vitals. Once a participant is deemed eligible, all study procedures and subsequent follow-up visits (8 in total) are conducted at the Wayne State University Clinical Research Service Center. We seek to determine the effect of MI-BP on BP for 1 year (using BP control and mean systolic BP as coprimary outcomes and physical activity, sodium intake, and medication adherence as secondary outcomes) compared with usual care controls. RESULTS: Recruitment for this study began in January 2018. The study will continue through 2021. CONCLUSIONS: As the first of its kind conducted in an ED setting, MI-BP was designed to document the efficacy and acceptability of a multicomponent mHealth approach to help African Americans with uncontrolled BP modify their lifestyle to better manage their HTN. We expect to lay the foundation to sustainably reduce HTN-related health disparities through better integration of multiple behavior self-monitoring and improve outcomes for those who traditionally rely on the ED for chronic disease care. TRIAL REGISTRATION: ClinicalTrials.gov NCT02360293; http://clinicaltrials.gov/ct2/show/NCT02360293. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/12601.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.281
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0070.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.229
GPT teacher head0.573
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designRandomized trial
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2018
Admission routes1
Has abstractyes

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