# Implementing to sustain: Determining the minimum necessary intervention to maintain a postpartum depression prevention program (ROSE) in clinics providing prenatal services to low-income women

> **NIH NIH R01** · MICHIGAN STATE UNIVERSITY · 2022 · $678,154

## Abstract

A recent expert consensus report concluded that, “Little is known about how well or under what
conditions health innovations are sustained and their gains maintained once they are put into practice.”1 This
report placed high priority on conducting return on investment (ROI) studies to determine how much is gained
when effective programs are sustained, and cost-benefit trade-offs for effort required to sustain.
 Postpartum depression (PPD) is common and can have lasting consequences for mother and child.
Outpatient clinics offering prenatal care are an opportune place to deliver PPD prevention services because
most women visit while pregnant. ROSE is a group intervention to prevent PPD, delivered during pregnancy in
outpatient prenatal settings. ROSE has been found to significantly reduce cases of PPD in multiple randomized
trials in community prenatal settings with racially and ethnically diverse low-income pregnant women.
Requests for ROSE training and recent policy changes supporting payment for comprehensive perinatal
services to underserved populations suggest a context ripe for embedding ROSE in prenatal clinics long-term.
 Given the need for ROI studies about sustainment efforts and that ROSE is well-positioned for sustain-
ment research, we propose a Sequential Multiple Assignment Randomized (SMART) Trial of the effectiveness
and cost-effectiveness of a stepwise approach to sustainment of ROSE in 90 outpatient clinics providing
prenatal care to pregnant women on public assistance in MI, NY, RI, PA, MA, and FL. In Year 1, all clinics will
receive enhanced implementation as usual (EIAU; initial training + tools for sustainment). At the first time at
which a clinic is determined to be at risk for failure to sustain (i.e., at 3, 6, 9, 12, 15 months), that clinic will be
randomized to receive either: (1) no additional implementation support (i.e., EIAU only), or (2) low-intensity
coaching and feedback (LICF). If clinics receiving LICF are still found to be at risk at subsequent assessments,
they will be randomized to either (1) EIAU + LICF only, or (2) high-intensity coaching and feedback (HICF).
Additional study follow-up interviews will occur at 18, 24, and 30 months, but no implementa-tion intervention
will occur after 18 months. Outcomes include: 1. Sustainment of core program elements at each time point and
total length of time ROSE services were provided and were provided with at least moderate fidelity. 2. Health
impact (PPD rates over time at each clinic) and reach. 3. ROI (costs, cost-offsets, and cost-effectiveness) of
each sustainment step. Hypothesized mechanisms include sustainment of clinical and organizational capacity
to deliver core elements, and engagement/ownership. The study will also examine predictors, tailoring
variables, and implementation processes to determine which kinds of clinics need which level of sustainment
support and when. To our knowledge, this study will be the first randomized trial evaluating the ROI of a
...

## Key facts

- **NIH application ID:** 10335232
- **Project number:** 5R01MH114883-05
- **Recipient organization:** MICHIGAN STATE UNIVERSITY
- **Principal Investigator:** JENNIFER E JOHNSON
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $678,154
- **Award type:** 5
- **Project period:** 2018-01-01 → 2023-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10335232

## Citation

> US National Institutes of Health, RePORTER application 10335232, Implementing to sustain: Determining the minimum necessary intervention to maintain a postpartum depression prevention program (ROSE) in clinics providing prenatal services to low-income women (5R01MH114883-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10335232. Licensed CC0.

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