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Opening windows of opportunities: Evidence for interventions to prevent or treat depression in pregnant women being associated with changes in offspring's developmental trajectories of psychopathology risk

Published online by Cambridge University Press:  02 August 2018

Sherryl H. Goodman*
Affiliation:
Emory University
Katherine A. Cullum
Affiliation:
Emory University
Sona Dimidjian
Affiliation:
University of Colorado at Boulder
Laura M. River
Affiliation:
University of Denver
Christine Youngwon Kim
Affiliation:
Emory University
*
Address correspondence and reprint requests to: Sherryl Goodman, Department of Psychology, Emory University, Atlanta, GA 30322; E-mail: sherryl.goodman@emory.edu.

Abstract

Although animal models and correlational studies support a model of fetal programming as a mechanism in the transmission of risk for psychopathology from parents to children, the experimental studies that are required to empirically test the model with the human prenatal dyad are scarce. With a systematic review and meta-analysis of the literature, we critically examined the evidence regarding the neurobiological and behavioral changes in infants as a function of randomized clinical trials to prevent or reduce maternal depression during pregnancy, treating randomized clinical trials as experiments testing the fetal programming model. Based on 25 articles that met inclusion criteria, we found support for interventions designed to change maternal prenatal mood being associated with changes in offspring functioning, but with a very small effect size. Effect sizes ranged broadly, and were higher for younger children. The findings enhance understanding of putative mechanisms in the transmission of risk from women's prenatal depression to infants’ vulnerabilities to, and early signs of, the development of psychopathology. We note limitations of the literature and suggest solutions to advance understanding of how preventing or treating depression in pregnant women might disrupt the transmission of risk to the infants.

Type
Special Issue Articles
Copyright
Copyright © Cambridge University Press 2018 

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Footnotes

Michael Borenstein provided valuable assistance with the approaches to analyses using the Comprehensive Meta-Analysis (CMA) software. The authors gratefully acknowledge his prompt and thorough responsiveness to our questions. Claire Coles generously offered her time to review and provide a reliability check on categories of child functioning. Hannah Simon provided initial guidance to the authors on the CMA software. The authors thank Scout for his supportive presence.

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