Evidence map›Paper›PMID 39233896›Full record

ArticleDigital health

Digital health utilization during pregnancy and the likelihood of preterm birth.

Alison K Brinson, Hannah R Jahnke, Natalie Henrich, Smriti Karwa, Christa Moss, Neel Shah

Abstract read
In one paragraph

Article in Digital health. 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

6 authors.

Alison K BrinsonDepartment of Anthropology, University of North Carolina at Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0002-5191-1336
Hannah R JahnkeMaven Clinic, New York, NY, USA.
Natalie HenrichMaven Clinic, New York, NY, USA.ORCID https://orcid.org/0000-0002-0293-1859
Smriti KarwaMaven Clinic, New York, NY, USA.
Christa MossMaven Clinic, New York, NY, USA.
Neel ShahMaven Clinic, New York, NY, USA.

Funding

From Biological to Social Processes: Interdisciplinary Training in Life Course ResearchT32HD091058 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ROBERT A HUMMER, Amanda L Thompson · 2017 to 2026
$4.3M
NICHD NIH HHS T32 HD091058
6 · The paper itself

Abstract

Objective: Given the complex nature of preterm birth, interventions to reduce rates of preterm birth should be multifaceted. This analysis aimed to explore the association between the duration of using Maven, a digital health platform for women's and family health, and the odds of preterm birth. Methods: Data came from 3326 pregnant, nulliparous Maven users who enrolled in Maven during their pregnancy between January 2020 and September 2022. Chi-square and Fisher's exact tests compared characteristics between users who developed gestational conditions and users who did not. This retrospective cohort study used logistic regression models to estimate the association between the duration of Maven use and odds of preterm birth, stratified by the presence of gestational conditions. Results: Compared to those without gestational conditions, individuals who developed gestational conditions were more likely to have a preterm birth (8.7% vs. 3.4%; Conclusion: Among those who developed gestational conditions, use of a digital health platform was associated with a decreased likelihood of preterm birth.

Indexed as

Digital healthpregnancypreterm birthreproductive healthwomen's health

Identifiers

PMID39233896
PMCPMC11372763

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.