NIDA - National Institute on Drug Abuse
PROJECT SUMMARY/ABSTRACT The perinatal period is marked by heightened vulnerability to mental health challenges, with perinatal substance use (PSU) and perinatal depression (PD) presenting significant concerns for maternal well-being and child development. PSU and PD often co-occur and pose bidirectional risks that exacerbate caregiving challenges. Despite evidence of their influence and overlap, research has yet to investigate how the interplay between PSU and PD impacts infant hippocampal development. Prior work in this area has been limited by assuming uniform impacts across the perinatal period and neglecting to evaluate these dynamic and bidirectional risk factors within the same model. Moreover, insights into how characteristics of PSU and PD (e.g., intensity, comorbidity, chronicity) may modify risk for development remains highly debated. To address these gaps, this study will be the first to model the longitudinal interplay between PSU, PD, and their combined impact on infant brain development. We hypothesize that utilizing person-centered, longitudinal, data-driven trajectories, rather than relying on static global reference values or clinical cutoffs, will provide more clinically valuable metrics for intervention, fostering intergenerational benefits. This study aims to (1) Characterize the interplay between PSU and PD and their reciprocal unfolding over the perinatal period. Specifically, testing whether within- or between-subjects models better capture the bidirectional interplay and change between PSU and PD across time to identify key windows and metrics of risk. (2a) Examine the impact of PSU/PD comorbidity on infant hippocampal volume and growth and test whether within- or between-subjects models better capture risk for offspring neurodevelopment. (2b) Compare models informed by developmental theory (Mismatch vs. Cumulative Stress vs. Mood Entropy) to evaluate which best characterizes the impact of PSU/PD on neurodevelopment in the first year of life. This research is responsive to the goals of NIDA’s 2022-2026 strategic plan to leverage data science to understand real-world complexity—including how comorbid mental health conditions and risk and protective factors interact to influence drug-related outcomes. Findings have the potential to refine screening practices, optimizing their timing and content to identify at-risk individuals more effectively. This work could ultimately enhance the capacity of healthcare systems to deliver timely and targeted interventions, improving health outcomes for families impacted by PSU and PD and reducing intergenerational consequences.
Up to $107K
2028-02-14
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