# Digital Mindfulness Based Cognitive Therapy for Perinatal Depression

> **NIH NIH U19** · KAISER FOUNDATION RESEARCH INSTITUTE · 2020 · $627,934

## Abstract

An increasing number of digital mental health technologies are being developed to expand access to
mental health treatments and deliver them in a cost-effective manner. Although efficacy trials of these
technologies demonstrate improved patient outcomes, especially when combined with coaching support, there
is little evidence that such digital tools can be widely implemented and sustained in routine care settings.
 Perinatal depression is one area of significant public health concern where the role of digital mental
health technology is especially relevant. Approximately 30-40% of women with histories of depression
experience relapse during the perinatal period, a majority show poor adherence to antidepressants (ADs), the
most common prevention treatment, and a majority express a preference for non-pharmacologic treatments.
However, effective and easily accessible non-pharmacologic treatments are not widely available. Inadequate
treatment for perinatal depression poses unique risks, including potential obstetrical and neonatal
complications associated with perinatal depression itself and with fetal exposure to ADs. It is therefore
imperative to test the implementation of effective and scalable non-pharmacological treatments to reduce the
risk of depression relapse in the perinatal period.
 Mindfulness Based Cognitive Therapy (MBCT) is a promising preventive intervention for pregnant
women with recurrent depression (as well as for adults in general), demonstrating significant reductions in
rates of depressive relapse and residual depressive symptoms. MBCT is an eight-session in-person group
intervention targeting risk factors for depressive relapse through a combination of mindfulness meditation and
cognitive-behavioral strategies. Because of challenges in delivering in-person MBCT (difficulty for health
systems to scale up the intervention, barriers to access for pregnant women), we developed a mobile-first
digital adaptation of MBCT for pregnant women, Mindful Mood Balance for Moms (MMBFM).
 The critical next phase of our work is to evaluate the potential of MMBFM as an effective intervention
that can be more widely adopted, implemented and sustained across heterogeneous patient populations and
health care systems. We propose a large pragmatic hybrid type II effectiveness--implementation trial
comparing MMBFM to usual care (UC) among pregnant women at risk for recurrent depression at four MHRN
sites: KP Colorado, KP Southern California, HealthPartners, and KP Georgia to address the following aims:
 AIM 1: Test the effectiveness of MMBFM in reducing depression symptoms, reducing risk of relapse or
significant worsening, and improving perinatal outcomes when implemented in real-world health systems.
AIM 2: Evaluate the incremental cost effectiveness of MMBFM compared to UC.
AIM 3: Evaluate healthcare system's implementation of MMBFM using the RE-AIM (Reach, Effectiveness,
Adoption, Implementation, and Maintenance) model.

## Key facts

- **NIH application ID:** 10021734
- **Project number:** 5U19MH121738-02
- **Recipient organization:** KAISER FOUNDATION RESEARCH INSTITUTE
- **Principal Investigator:** Arne L. Beck
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $627,934
- **Award type:** 5
- **Project period:** 2019-09-23 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10021734

## Citation

> US National Institutes of Health, RePORTER application 10021734, Digital Mindfulness Based Cognitive Therapy for Perinatal Depression (5U19MH121738-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10021734. Licensed CC0.

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