Evidence map›Paper›PMID 39892162›Full record

ArticlePregnancy hypertension2025

Home blood pressure monitoring and mobile health application practices among pregnant persons with and at risk of hypertensive disorders of pregnancy.

Mawulorm Ki Denu, Cassie Shao, Katherine Tak, Sanjna Iyengar, Kelton Do, Nouran Y Nagy, Ganeev Singh, Katherine Anais Sadaniantz, Sravya Shankara, Lara C Kovell

Abstract read
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In one paragraph

Article in Pregnancy hypertension, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Mawulorm Ki DenuDivision of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
Cassie ShaoDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
Katherine TakDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
Sanjna IyengarDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
Kelton DoDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
Nouran Y NagyDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
Ganeev SinghDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
Katherine Anais SadaniantzDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
Sravya ShankaraDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
Lara C KovellDivision of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States. Electronic address: Lara.kovell@umassmemorial.org.

Funding

Development of a Mobile Health Intervention for Blood Pressure Management in PregnancyK23HL163450 · UNIV OF MASSACHUSETTS MED SCH WORCESTER · 2025 to 2025
$266k
NHLBI NIH HHS K23 HL163450
6 · The paper itself

Abstract

objectivesTo examine training in and current home blood pressure monitoring (HBPM) practices in pregnancies with hypertensive disorders of pregnancy (HDP) or risk factors for HDP; and to explore interest in using mHealth applications for communicating with healthcare providers. STUDY

designA cross-sectional survey was conducted on HBPM practices/training and interest in using mobile health (mHealth) applications among pregnant persons at an academic medical center. OUTCOME MEASURES: The main outcomes measured were the proportion of participants who received training for HBPM, and the proportion interested in using mHealth applications for communication with providers related to managing HDP.

resultsOf the 103 participants, 41 (39.8%) used HBPM. Of those who did HBPM, 36.6% received training from their healthcare providers. Training more often included instructions on positioning and how to perform HBPM, and rarely included advice on validated HBPM devices. Nearly all participants (98.1%) owned a smartphone, and 19.4% had a smartwatch. A significant majority expressed interest in using a secure mobile app for communication with providers (78.6%), and 88.3% were interested in wearing a smartwatch for remote monitoring. There were no significant differences in interest levels based on race, age, residence, or education, while there was higher interest (100% vs. 67%) in mobile apps for communication among those with HDP vs. risk factors for HDP.

conclusionsDespite a low level of training for HBPM, there was high interest in using mHealth applications. Leveraging mHealth technology could help overcome the challenges of providing training for HBPM.

Indexed as

Blood Pressure Monitoring, AmbulatoryHypertension, Pregnancy-InducedMobile ApplicationsAdultCross-Sectional StudiesFemaleHumansPregnancyRisk FactorsSmartphoneTelemedicineYoung AdultHome blood pressure monitoringHypertensive disordersmHealthPregnancySmartphonesTraining

Identifiers

PMID39892162
PMCPMC12431275

What Socratic holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.