Maternal Depressive Symptoms Predict General Liability in Child Psychopathology

ABSTRACT

Objective: The current study examines how maternal depressive symptoms relate to child psychopathology when structured via the latent bifactor model of psychopathology, a new organizational structure of psychopathological symptoms consisting of a general common psychopathology factor (p-factor) and internalizing- and externalizing-specific risk.

Method: Maternal report of depressive symptoms (Beck Depression Inventory – II) and child psychopathological symptoms (Child Behavior Checklist and Children’s Behavior Questionnaire) were provided by 554 mother-child pairs. Children in the sample were 7.7 years old on average (SD = 1.35, range = 5–11 years), and were 49.8% female, 46% Latinx, and 67% White, 6% Black, 5% Asian/Pacific Islander, and 21% multiracial.

Results: Maternal depressive symptoms were positively associated with the child p-factor but not with the internalizing- or externalizing-specific factors. We did not find evidence of sex/gender or race/ethnicity moderation when using latent factors of psychopathology. Consistent with past research, maternal depressive symptoms were positively associated with internalizing and externalizing composite scores on the Child Behavior Checklist.

Conclusions: Findings suggest that maternal depressive symptoms are associated with transdiagnostic risk for broad child psychopathology (p-factor). Whereas the traditional Achenbach-style approach of psychopathological assessment suggests that maternal depressive symptoms are associated with both child internalizing and externalizing problems, the latent bifactor model suggests that these associations may be accounted for by risk pathways related to the p-factor rather than internalizing or externalizing specific risk. We discuss clinical and research implications of using a latent bifactor structure of psychopathology to understand how maternal depression may impact children’s mental health.

Acknowledgments

The assistance of Megan Faulkner, Kendra Leak, Natalie Hernandez, Christina Canino, and Cheryl Crippen is gratefully acknowledged. We also thank Tobias Koch for helpful guidance on implementing the residual approach for estimating unbiased associations with the bifactor model factors, as well as the families who participated in our studies.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental material for this article can be accessed online at https://doi.org/10.1080/15374416.2020.1723598.

Additional information

Funding

This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development [R01 HD050662, R01 HD51852]; National Institute of Mental Health [P50 MH096889, R01 MH109662]; National Institute of Neurological Disorders and Stroke [R01 NS041298].