Depression and anxiety during and after pregnancy are common medical complications contributing to a rising maternal mortality rate. Home visiting programs can offer evidence-based interventions to improve mental health outcomes for a vulnerable pregnant population; however, barriers remain to achieving the full potential of these interventions. Our work will explore the impact of context on the implementation of a mental health intervention to provide action-based and impactful data that focuses on the lived experiences of the diverse populations served by home visiting programs in Iowa and Indiana.

Perinatal mental health conditions are the most common complication of pregnancy and childbirth (1 in 8 women). When left untreated, perinatal depression and anxiety adversely affect the entire family with pregnancy complications and negative outcomes including preterm birth, impaired mother-infant bonding, impaired lactation, substance abuse, divorce, suicide, and infanticide. Despite this, significant gaps persist in the diagnosis and treatment of perinatal depression and anxiety. Preliminary research with stakeholders including community advisory boards, groups underreceiving mental health services, and state departments of health, demonstrates the importance of social support as a mechanism for improving perinatal depression, particularly in rural geographies. Home visiting programs (HVPs) can provide the social support needed to improve mental health outcomes in pregnant and postpartum women.

Using the strategy of implementation facilitation, our proposed study will engage multilevel stakeholders (e.g., policymakers, front-line implementers, and intervention recipients) to adapt facilitation to integrate a maternal mental health intervention across two midwestern, rural states (Iowa and Indiana) with multiple HVP models. Given the complexity and heterogeneity of the contexts in which Mothers and Babies will be integrated, a three variable hybrid implementation-effectiveness-context trial will test the adapted facilitation strategy compared with implementation as usual (i.e., standard education) and will assess contextual factors related to the outcomes. Using an evidence-based implementation strategy that tailors implementation delivery to the needs of the specific populations and context may improve fidelity and adoption, particularly in rural states where residents have limited access to care.

The immediate impact of this research will be to show whether adapted facilitation can improve the uptake and fidelity of a maternal mental health intervention like Mothers and Babies across multiple HVP models and thus positively affect depressive symptoms and perceived stress of recipients. Further, our implementation protocol can be used by other states to better integrate other evidence-based interventions into public health programs, leading to further improvements in maternal mental health, better access, and further reductions in adverse outcomes for mothers, children, and families.

Inclusion criteria:

• Affiliated as staff or volunteer with a home visiting program in Iowa or Indiana at the time of enrollment
• Aged 18 years or older

Exclusion criteria:

- No exclusion criteria.

Coded interview/focus group transcript data will be both preserved and shared through relevant publications or other dissemination (e.g., conference presentations). Interview/focus group/observation transcript data will be deposited with NIMH Data Archive (NDA), located within a broad-use permission group where data will only be accessible to researchers who submit a Data Use Certification (DUC) and who meet the NDA's criteria to request access. The DUC includes terms that prohibit the attempt of reidentification.

Survey responses will be both preserved and shared. Aggregate data and codebooks will be shared with relevant publications or by the end of the project period. Aggregate data is a dataset comprised of the consolidation of data relating to multiple survey participants, and therefore cannot be traced back to a specific participant. Respondent identifiers will not be shared. De-identified survey data will also be deposited with NDA.

As approved by the NDA

Data will only be accessible to researchers who submit a Data Use Certification (DUC) and who meet the NDA's criteria to request access.