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Record W4409670496 · doi:10.1016/j.jadr.2025.100926

The impact of prenatal maternal depression, during the COVID-19 pandemic on maternal postpartum depression: A prospective cohort study within the conception study

2025· article· en· W4409670496 on OpenAlexafffundabout
Vanina Tchuente, Jessica Gorgui, Sarah Lippé, Anick Bérard

Bibliographic record

VenueJournal of Affective Disorders Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersFaculté de pharmacie, Université de Montréal
KeywordsPandemicDepression (economics)Coronavirus disease 2019 (COVID-19)Prospective cohort studyMedicineCohort study2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PregnancyCohortPsychiatryObstetricsVirologyInternal medicineDiseaseOutbreakBiology

Abstract

fetched live from OpenAlex

• >40 % of participants reported possible to probable prenatal depression. • Almost 40 % of participants reported possible to probable postpartum depression. • Risk of postpartum depression increased with the severity of prenatal depression. • Risk of postpartum depression increased with prenatal stress and being nulliparous. The COVID-19 pandemic introduced unprecedented disruptions impacting perinatal mental health. We aimed to quantify the association between prenatal depression (PD) and postpartum depression (PPD), within this context. Data were collected from Canadian pregnant individuals (aged≥18) through web-based questionnaires. Individuals who completed both a baseline questionnaire (06/2020 to 12/2021) and the 2-month postpartum follow-up, were included. PD was assessed with the Edinburgh Postnatal Depression Scale (EPDS), categorized as unlikely (EPDS 0–8), possible (9–11), highly possible (12–13), and probable (EPDS≥14). PPD was assessed at 2 months postpartum also using EPDS, and categorized as unlikely (EPDS 0–8), possible to probable (EPDS≥9). Self-reported data on sociodemographics, comorbidities, gestational age, anxiety (General Anxiety Disorder-7), stress, maternal hardship (CONCEPTION Assessment of Stress from COVID-19) were collected. We used a multivariate Poisson regression model to calculate relative risks (RRs) with 95 % confidence interval (CI) to assess the risk of PPD associated with PD. Among 1247 participants, 57.9 % had unlikely PD, 17.1 % possible PD, 9.3 % highly possible PD, 15.7 % probable PD. The overall prevalence of PPD was 39.5 %. Possible PD increased PPD risk (aRR 1.56, 95 % CI 1.18 – 2.05); Highly possible PD further heightened the risk (aRR: 2.24, 95 % CI 1.65 – 3.04); and the highest risk for probable PD (aRR 2.29, 95 % CI 1.66 – 3.15). PPD risk also increased with prenatal stress (aRR 1.07; 95 % CI 1.01 – 1.13) and nulliparity (aRR 1.26, 95 % CI 1.04 – 1.54). Addressing prenatal depression, especially during crises, is crucial to reduce PPD risk and improve maternal and child health.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.638

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.345
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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