Evidence map›Paper›PMID 34845174›Full record

ArticleMCN. The American journal of maternal child nursing

Perinatal Experiences of Asian American Women During COVID-19.

Deepika Goyal, Meekyung Han, Talia Feldman-Schwartz, Huynh-Nhu Le

Abstract read
In one paragraph

Article in MCN. The American journal of maternal child nursing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

4 authors.

Deepika Goyal
Meekyung Han
Talia Feldman-Schwartz
Huynh-Nhu Le

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo explore the wellbeing, pregnancy, childbirth, and postpartum experiences of Asian American women who gave birth during the COVID-19 pandemic. STUDY

designQualitative exploratory design.

methodsUsing convenience and snowball sampling, we recruited Asian American women who gave birth during the COVID-19 pandemic via social media. Participants completed sociodemographic and depressive symptom questionnaires and took part in a virtual semistructured interview where they were asked to describe their pregnancy, birth, and postpartum experiences in the midst of the COVID-19 pandemic. Qualitative content analysis methods were used to identify themes from participant narratives.

resultsThirty-eight Asian American women representing several racial ethnic subgroups (Asian Indian, Chinese, Filipino, Hmong, Laotian, Vietnamese) participated in our study. Participants were on average 34 (SD = 3.5) years of age; the majority were married and lived in California. At the time of data collection, participants were 3.7 (SD = 2.07) months postpartum and 5.3 to 10.5 months into the COVID-19 pandemic. Qualitative content analysis revealed two main themes: 1) unexpected perinatal journey, and 2) the emotional and psychological consequences of COVID-19. CLINICAL IMPLICATIONS: Our findings are not unique to Asian American women, but they offer insight for nurses taking care of all childbearing women. Nurses can provide individually tailored anticipatory guidance to help women navigate perinatal changes and manage expectations during future public health crises. Nurses can also encourage and help perinatal women identify ways to increase their own social support networks during the pregnancy and postpartum period.

Indexed as

COVID-19AsianFemaleHumansPandemicsParturitionPregnancySARS-CoV-2

Identifiers

PMID34845174
PMCPMC8865031

What OpenQuestion holds

Textmetadata
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.