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Updated: May 2, 2026

Using a Murine Model of Psychosocial Stress in Pregnancy as a Translationally Relevant Paradigm for Psychiatric Disorders in Mothers and Infants

Using a Murine Model of Psychosocial Stress in Pregnancy as a Translationally Relevant Paradigm for Psychiatric Disorders in Mothers and Infants

Published on: June 13, 2021

Beyond Linear Risk: A Machine Learning Approach to Understanding Perinatal Depression in Context.

Phillip Sherlock¹, Maxwell Mansolf², Julie Hofheimer³

¹Anita Zucker Center for Excellence in Early Childhood Studies, College of Education, University of Florida, Gainesville, FL, USA.

Multivariate Behavioral Research

|May 1, 2026

Summary

This summary is machine-generated.

Prenatal depression (PND) and postpartum depression (PPD) risks vary significantly by context. Understanding these specific maternal life contexts is crucial for identifying effective interventions for perinatal depression.

Keywords:

Postpartum depression conditional inference recursive partitioning regression

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Using Chronic Social Stress to Model Postpartum Depression in Lactating Rodents

Using Chronic Social Stress to Model Postpartum Depression in Lactating Rodents

Published on: June 10, 2013

Area of Science:

Perinatal mental health
Reproductive psychiatry
Public health

Background:

Prenatal depression (PND) and postpartum depression (PPD) are significant maternal health concerns.
Existing research often overlooks the contextual factors influencing PND and PPD.
A deeper understanding of these contexts is needed for effective intervention.

Purpose of the Study:

To investigate the contextual nature of PND and PPD.
To identify specific contexts and characteristics associated with PND and PPD.
To explore how risk factors for perinatal depression vary across different maternal subgroups.

Main Methods:

Utilized nonrandomly clustered data from 8,936 mothers across 16 Environmental influences on Child Health Outcomes (ECHO) Cohort cohorts.
Employed a recursive partitioning algorithm (ctree) to analyze predictor and effect heterogeneity.
Identified contexts and their associated characteristics linked to PND and PPD.

Main Results:

Risk factors for PND and PPD were found to be heterogeneously and synergistically present within specific contexts.
The same variables did not consistently act as risk factors across all maternal groups.
Medical and sociodemographic risks do not have simple, universal associations with perinatal depression.

Conclusions:

No single variable reliably predicts PND or PPD in isolation; context is paramount.
The study supports Bronfenbrenner's bioecological systems framework regarding environmental influences.
Future research should focus on identifying specific contexts and subgroups where risks contribute to perinatal depression, rather than universal risk factors.