Evidence map›Paper›PMID 42172638›Full record

ArticleJMIR research protocols2026

Protocol for Monitoring Postpartum Hypertension Outcomes via a Smartphone App (MOMitor): Ecological Momentary Assessment.

Chidimma Doris Azubuike, Jungjun Bae, Deepthi S Varma, Tony Wen, Kay Roussos-Ross, Amie Goodin

Abstract read
In one paragraph

Article in JMIR research protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

6 authors.

Chidimma Doris AzubuikeDepartment of Pharmaceutical Outcomes and Policy, University of Florida, DSIT Building, 6th Floor, 1889 Museum Road, Gainesville, FL, 32611-0496, United States, 1 3522948829.ORCID 0009-0007-7352-9609
Jungjun BaeDepartment of Pharmaceutical Outcomes and Policy, University of Florida, DSIT Building, 6th Floor, 1889 Museum Road, Gainesville, FL, 32611-0496, United States, 1 3522948829.ORCID 0000-0002-8975-4073
Deepthi S VarmaDepartment of Pharmaceutical Outcomes and Policy, University of Florida, DSIT Building, 6th Floor, 1889 Museum Road, Gainesville, FL, 32611-0496, United States, 1 3522948829.ORCID 0000-0003-1163-0377
Tony WenDepartment of Pharmaceutical Outcomes and Policy, University of Florida, DSIT Building, 6th Floor, 1889 Museum Road, Gainesville, FL, 32611-0496, United States, 1 3522948829.ORCID 0000-0003-1638-0186
Kay Roussos-RossDepartment of Pharmaceutical Outcomes and Policy, University of Florida, DSIT Building, 6th Floor, 1889 Museum Road, Gainesville, FL, 32611-0496, United States, 1 3522948829.ORCID 0000-0003-2283-2441
Amie GoodinDepartment of Pharmaceutical Outcomes and Policy, University of Florida, DSIT Building, 6th Floor, 1889 Museum Road, Gainesville, FL, 32611-0496, United States, 1 3522948829.ORCID 0000-0002-0020-8720

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Postpartum hypertension defined as elevated blood pressure after childbirth, affects approximately 20% of women after delivery. Digital health interventions that include remote monitoring therefore, present an important opportunity to facilitate regular blood pressure assessment in this high-risk population. Objective: The primary objective is to assess within- and between-person changes in hypertension status over the first 6 weeks postpartum using a smartphone-based ecological momentary assessment protocol. The secondary objective is to characterize the trajectory of hypertension indicators across the 6-week period and to compare hypertension screening results from week one and week six within participants. Methods: This study uses a time-series design using data from prospectively enrolled patients within a large health system. Patients eligible for recruitment were women aged 18 years or older who spoke English, owned a smartphone, had a liveborn neonate, and were willing to download an app and respond to survey questions within the app. Throughout the study period, all participants received hypertension screening items that asked whether their blood pressure was greater than 140/90 mm Hg and whether they felt dizzy or lightheaded, short of breath, or had a severe headache. A subset of participants were additionally asked to report their blood pressure readings. We estimate within- and between-participant effects using a generalized linear mixed model for a positive hypertension screen during weeks one through six. The model includes both fixed and random effects, controlling for age, race, marital status, education, insurance status, mode of delivery, total number of pregnancies, and history of diabetes mellitus. Results: The study was funded July 2021 and data collection was initiated in November 2021. Data collection for this study, per protocol, was completed in June 2025, though other participants continue to be enrolled in the ongoing parent study. Data analysis is expected to be completed by Spring 2026 with publication planned for Summer 2026. Conclusions: The study findings will provide insight into trajectories of hypertension outcomes in postpartum women and the utility for smartphone app-based remote blood pressure monitoring among postpartum women whose blood pressure was regularly tracked. Findings will provide evidence to support whether widespread implementation of this digital health surveillance approach to improve outcomes in maternal health, especially in the postpartum period, is clinically warranted.

Indexed as

Ecological Momentary AssessmentHypertensionMobile ApplicationsAdultBlood Pressure DeterminationFemaleHumansPostpartum PeriodPregnancyProspective StudiesSmartphonedigital healthhypertensionmaternal healthpostpartumpregnancy

Identifiers

PMID42172638
PMCPMC13197109

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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 OpenQuestion graph.