Evidence map›Paper›PMID 32956168›Full record

ArticleMCN. The American journal of maternal child nursing

Pain and Depression Symptoms During the Third Trimester of Pregnancy.

Julie Vignato, Yelena Perkhounkova, Ann Marie McCarthy, Lisa S Segre

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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

6 citing papers in PubMed.

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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

4 authors.

Julie Vignato
Yelena Perkhounkova
Ann Marie McCarthy
Lisa S Segre

Funding

Pain and Associated Symptoms: Nurse Research TrainingT32NR011147 · NINR · UNIVERSITY OF IOWA · PI HERR, KEELA A, MCCARTHY, ANN MARIE · 2010 to 2020
$1.9M
NINR NIH HHS T32 NR011147
6 · The paper itself

Abstract

purposeTo assess the association between depression symptoms and pain characteristics, including pain intensity, location, and effectiveness of pain management strategies, among women in their third trimester of pregnancy.

designDescriptive, exploratory cross-sectional study.

settingMobile health pregnancy application (app).

participantsA convenience sample of women in their third trimester of pregnancy from across the United States.

methodsWomen completed demographic questionnaires, the Brief Pain Inventory, and Edinburgh Postnatal Depression Scale (EPDS) through an online Web site.

resultsN = 132 women participated. The sample was demographically diverse. . Women ranged in age from 18 to 39 years (M 28.1 ± SD 5.2). Most women were Caucasian (68%), with smaller percentages of Hispanic (12%) and African American (11%) women. Most had commercial insurance (59%) and a partner (85%). Of the 132 women, 79.6% reported moderate-to-severe pain. Approximately 93% experienced back and pelvic pain, whereas 27% experienced moderate-to-severe depression symptoms. Bivariate and linear regression analyses revealed that higher EPDS depression scores were associated with higher levels of pain (p < .01). Other variables significantly associated with higher EPDS scores were White race (p = .04), marital status (p = .05), and headache (p < .01). CLINICAL IMPLICATIONS: In the third trimester of pregnancy, pain affects more than two-thirds of women and may occur with and without depression symptoms. Although the value of universal depression screening during pregnancy is widely recognized, our findings suggest clinical outcomes for pregnant women would improve with a standardized, multidimensional screen for both pain and depression symptoms. Nurses are ideally positioned to assess and advocate for the combined treatment of pain and depression.

Indexed as

AdolescentAdultDepressionFemaleHumansPainPain ManagementPregnancyPregnancy Trimester, ThirdPregnant PeoplePsychiatric Status Rating ScalesPsychometricsSurveys and Questionnaires

Identifiers

PMID32956168
PMCPMC13317161

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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.