Evidence map›Paper›PMID 41613987›Full record

ArticleDigital health

Using smart devices for prenatal care: Assessing the willingness among women with pregnancy-related anxiety.

Stefanie Altmannshofer, Filip Weidenthaler, Adriana Titzmann, Constanza A Pontones, Nina Danzberger, Katharina M Jaeger, Michael Nissen, Heike Leutheuser, Bjoern M Eskofier, Peter A Fasching and 2 more

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

12 authors.

Stefanie AltmannshoferDepartment of Gynecology and Obstetrics, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.ORCID https://orcid.org/0009-0009-9652-045X
Filip WeidenthalerDepartment of Gynecology and Obstetrics, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.ORCID https://orcid.org/0009-0000-0694-8722
Adriana TitzmannDepartment of Gynecology and Obstetrics, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.ORCID https://orcid.org/0009-0001-2290-5965
Constanza A PontonesDepartment of Gynecology and Obstetrics, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
Nina DanzbergerDepartment of Gynecology and Obstetrics, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
Katharina M JaegerMachine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
Michael NissenMachine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.ORCID https://orcid.org/0000-0001-5472-132X
Heike LeutheuserAmbient Assisted Living & Medical Assistance Systems, Department of Computer Science, University of Bayreuth, Bayreuth, Germany.ORCID https://orcid.org/0000-0001-9931-2271
Bjoern M EskofierMachine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.ORCID https://orcid.org/0000-0002-0417-0336
Peter A FaschingDepartment of Gynecology and Obstetrics, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.ORCID https://orcid.org/0000-0003-4885-8471
Matthias W BeckmannDepartment of Gynecology and Obstetrics, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
Hanna HuebnerDepartment of Gynecology and Obstetrics, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.ORCID https://orcid.org/0000-0001-6889-1493

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Wearables and smart devices could complement face-to-face prenatal care appointments by monitoring pregnant women's health, especially since pregnancy may be a vulnerable time when mental health issues and pregnancy-related anxiety may arise. Aim: The aim of this study was to analyze the extent whether the willingness of women to use smart devices for pregnancy care monitoring differs between those with pregnancy-related anxiety and those without. Methods: A survey was conducted to ascertain participant's general characteristics, attitudes toward smart devices, the willingness to use them, and the level of pregnancy-related anxiety (PRAQ-R2). Associations between the willingness and pregnancy-related anxiety parameters were analyzed. Results: Completed questionnaires from 210 women were included in the analysis. A significant difference between women showing high and low levels of pregnancy-related anxiety was observed in terms of their willingness to use a smartwatch (median score 4.00; interquartile range (IQR) 4.00-5.00 vs. 4.00; IQR 3.00-4.00; Conclusions: The data suggest that pregnant women are receptive to using smart devices to enhance their prenatal care, particularly those experiencing higher levels of anxiety. This study serves as an initial step in evaluating attitudes toward these devices. As a follow-up, it is recommended that acceptance and feasibility studies are conducted alongside the further development of existing and new pregnancy-specific wearables.

Indexed as

mHealthPRAQ-R2Pregnancy-related anxietyprenatal carewearables

Identifiers

PMID41613987
PMCPMC12847662

What OpenQuestion holds

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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.