Evidence map›Paper›PMID 34782924›Full record

ArticleArchives of gynecology and obstetrics2022

Dimensions of depressive symptomatology in mothers derived from factor analyses.

Kathryn S Saldaña, Jonathan A Shaffer, Kevin D Everhart, Susan L Kim, Peter S Kaplan

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Article in Archives of gynecology and obstetrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Peripartum Depression: What's New?Current psychiatry reports · 2025
    Review
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.

Kathryn S SaldañaUniversity of Colorado Denver, 1201 Larimer Street, Campus Box 173, Denver, CO, 80204, USA. Kathryn.saldana@ucdenver.edu.ORCID 0000-0001-8457-6581
Jonathan A ShafferUniversity of Colorado Denver, 1201 Larimer Street, Campus Box 173, Denver, CO, 80204, USA.
Kevin D EverhartUniversity of Colorado Denver, 1201 Larimer Street, Campus Box 173, Denver, CO, 80204, USA.
Susan L KimUniversity of Colorado Denver, 1201 Larimer Street, Campus Box 173, Denver, CO, 80204, USA.
Peter S KaplanUniversity of Colorado Denver, 1201 Larimer Street, Campus Box 173, Denver, CO, 80204, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeSubtypes of depression have been under studied in women during the peripartum period and the year after childbirth and delivery. Due to heterogeneity of depression, researchers have attempted to identify phenotypes of maternal and postpartum depression based on key symptoms that may represent underlying genes and biological etiology (Leuchter et al. Dialog Clinic Neurosci 16(4):525, 2014).

methodsThe current study collected self-report data from 587 women and utilized exploratory and confirmatory factor analyses (CFA) to identify subtypes of depression symptoms across two measures.

resultsFindings of the study showed that: (1) using the Beck Depression Inventory (BDI-II) and the Postpartum Depression Screening Scale (PDSS), a five-factor solution best fit the data in our sample of mothers with infants aged 4-14 months. The factors included: anxiety/thought disorder; cognitive depression; suicide; somatic/neurovegetative; and sleep [χ

conclusionsFuture research could assess the clinical benefits of screening for maternal mood disorders.

Indexed as

Depression, PostpartumMothersFactor Analysis, StatisticalFemaleHumansPsychiatric Status Rating ScalesPsychometricsReproducibility of ResultsSelf ReportSurveys and QuestionnairesDepressive subtypesMaternal depressionMaternal mood disordersPeripartum mood disordersSymptomatology

Identifiers

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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.