Evidence map›Paper›PMID 33007020›Full record

ArticlePloS one2020

Impact of the COVID-19 epidemic on patterns of pregnant women's perception of threat and its relationship to mental state: A latent class analysis.

Mengsha Qi, Xiaozhe Li, Shuyun Liu, Yonghong Li, Wei Huang

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  8. Latent COVID-19 Clusters in Patients with Opioid Misuse.Studies in health technology and informatics · 2022
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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

5 authors.

Mengsha QiWenjiang District People's Hospital, Chengdu, China.ORCID 0000-0002-9304-2183
Xiaozhe LiThe College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu, China.
Shuyun LiuWenjiang District People's Hospital, Chengdu, China.
Yonghong LiWenjiang District People's Hospital, Chengdu, China.
Wei HuangDepartment of Management, Chengdu University of Traditional Chinese Medicine, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe objective of this study was to define the threatened perception types of pregnant women during the COVID-19 pandemic and determine the correlations between the perception types and their demographic factors, their preventive knowledge of COVID-19 and their mental status in order to provide suggestions for pregnant women during pandemic.

methodsLatent class analysis were used to explore the optimal numbers of clusters. Multinomial logistic regression and multiple correspondence analysis were used to analyze the demographic variables of the latent categories. MANOVA was used to analyze the difference of knowledge of COVID-19 obtained among clusters and their psychological status, and chi-square test was used determine the relationship between the latent clusters and the participant's COVID-19 worry level.

resultsFive clusters were found: the first cluster (n = 120, 39%) was unthreatened and confident. Cluster 2(n = 84, 28%) was unthreatened but not confident. Cluster 3 (n = 49, 17%) was threatened but confident. Cluster 4 (n = 25, 9%) was threaten, not confident and knowledgeable, and Cluster 5 (n = 20, 7%) was threatened, not confident and lacking knowledge. Three demographic variables were shown an effect on the classification, they were support from work, family support and intrapartum and postpartum complications.

conclusionThis study can help assess the mental health risks of pregnant women during an epidemic. The results could be helpful for families, work units, communities and medical institutions to make targeted intervention decisions for pregnant women.

Indexed as

Mental HealthAdultAnxietyCoronavirus InfectionsCOVID-19FemaleHumansLatent Class AnalysisMiddle AgedPandemicsPneumonia, ViralPregnancyPregnancy Complications, InfectiousPregnant PeopleSocioeconomic FactorsSurveys and Questionnaires

Identifiers

PMID33007020
PMCPMC7531823

What OpenQuestion holds

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LicenceCC BY
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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.