Evidence map›Paper›PMID 33534854›Full record

ArticlePloS one2021

Pregnant women's daily patterns of well-being before and during the COVID-19 pandemic in Finland: Longitudinal monitoring through smartwatch technology.

Hannakaisa Niela-Vilén, Jennifer Auxier, Eeva Ekholm, Fatemeh Sarhaddi, Milad Asgari Mehrabadi, Aysan Mahmoudzadeh, Iman Azimi, Pasi Liljeberg, Amir M Rahmani, Anna Axelin

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 3 pooled it
8.8field-weighted citation impact, top 2% of its field
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

27 citing papers in PubMed, 3 syntheses or guidelines pooled it, 48 citations in OpenAlex.

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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 at 2 institutions in 2 countries.

Hannakaisa Niela-VilénDepartment of Nursing Science, University of Turku, Turku, Finland.ORCID 0000-0002-8646-6551
Jennifer AuxierDepartment of Nursing Science, University of Turku, Turku, Finland.
Eeva EkholmDepartment of Obstetrics and Gynaecology, Turku University Hospital and Faculty of Medicine, University of Turku, Turku, Finland.
Fatemeh SarhaddiDepartment of Future Technologies, University of Turku, Turku, Finland.ORCID 0000-0002-5750-5793
Milad Asgari MehrabadiDepartment of Electrical Engineering and Computer Science, University of California Irvine, Irvine, California, United States of America.
Aysan MahmoudzadehDepartment of Future Technologies, University of Turku, Turku, Finland.
Iman AzimiDepartment of Future Technologies, University of Turku, Turku, Finland.
Pasi LiljebergDepartment of Future Technologies, University of Turku, Turku, Finland.
Amir M RahmaniDepartment of Electrical Engineering and Computer Science, University of California Irvine, Irvine, California, United States of America.
Anna AxelinDepartment of Nursing Science, University of Turku, Turku, Finland.
University of Turku · FIUniversity of California, Irvine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTechnology enables the continuous monitoring of personal health parameter data during pregnancy regardless of the disruption of normal daily life patterns. Our research group has established a project investigating the usefulness of an Internet of Things-based system and smartwatch technology for monitoring women during pregnancy to explore variations in stress, physical activity and sleep. The aim of this study was to examine daily patterns of well-being in pregnant women before and during the national stay-at-home restrictions related to the COVID-19 pandemic in Finland.

methodsA longitudinal cohort study design was used to monitor pregnant women in their everyday settings. Two cohorts of pregnant women were recruited. In the first wave in January-December 2019, pregnant women with histories of preterm births (gestational weeks 22-36) or late miscarriages (gestational weeks 12-21); and in the second wave between October 2019 and March 2020, pregnant women with histories of full-term births (gestational weeks 37-42) and no pregnancy losses were recruited. The final sample size for this study was 38 pregnant women. The participants continuously used the Samsung Gear Sport smartwatch and their heart rate variability, and physical activity and sleep data were collected. Subjective stress, activity and sleep reports were collected using a smartphone application developed for this study. Data between February 12 to April 8, 2020 were included to cover four-week periods before and during the national stay-at-home restrictions. Hierarchical linear mixed models were exploited to analyze the trends in the outcome variables.

resultsThe pandemic-related restrictions were associated with changes in heart rate variability: the standard deviation of all normal inter-beat intervals (p = 0.034), low-frequency power (p = 0.040) and the low-frequency/high-frequency ratio (p = 0.013) increased compared with the weeks before the restrictions. Women's subjectively evaluated stress levels also increased significantly. Physical activity decreased when the restrictions were set and as pregnancy proceeded. The total sleep time also decreased as pregnancy proceeded, but pandemic-related restrictions were not associated with sleep. Daily rhythms changed in that the participants overall started to sleep later and woke up later.

conclusionsThe findings showed that Finnish pregnant women coped well with the pandemic-related restrictions and lockdown environment in terms of stress, physical activity and sleep.

Indexed as

Life StylePregnant PeopleAbortion, SpontaneousAdultCOVID-19ExerciseFemaleFinlandHeart RateHumansLongitudinal StudiesPregnancyPremature BirthSARS-CoV-2SleepSmartphone

Identifiers

PMID33534854
PMCPMC7857616
OpenAlexW3128817403

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.