# An implementation science approach to optimizing evidence-based treatments for posttraumatic stress disorder (PTSD) for non-specialty settings

> **NIH NIH K23** · BOSTON MEDICAL CENTER · 2020 · $185,759

## Abstract

PROJECT SUMMARY
Background: An estimated 33-46% of clients seen in urban low-income primary care or behavioral health
clinics have a current diagnosis of posttraumatic stress disorder (PTSD), yet only 13% receive PTSD
treatment. Further, only 57% of those who access care for PTSD receive a minimally adequate dose of
therapy. The shortage of trained mental health specialists has led to concerning inequities in access to and
quality of care in low-income community settings. To address workforce shortages, as well as client
preferences, leaders in the field have advocated for the development of stepped care approaches that begin
with brief, patient-centered interventions before progressing to intensive treatments. Despite promise, stepped
approaches have not been developed for adults with PTSD. Specific Aims: This current study applies the
Replicating Effective Programs Framework to guide the refinement and pre-implementation of a “Step 1”
evidence-based treatment (EBT) for PTSD in primary care. A full stepped care approach will be tested in a
future R01 (Step 1: brief, low intensity EBT in a non-specialty setting; Step 2: high intensity EBT in a specialty
setting). Aim 1: To conduct a mixed-methods formative evaluation based on surveys and semi-structured
interviews (N=25; 10 social worker and community health worker interventionists; 15 primary care
stakeholders) to characterize the local integrated primary care setting and identify the need for augmentation to
the intervention, protocol, or implementation blueprint. Aim 2: To optimize the intervention and operational
procedures and to finalize the formal implementation blueprint (based on Aim 1 findings and consultation with
the community advisory board [CAB]; N=10). Aim 3: To conduct a nonrandomized hybrid type 1
implementation-effectiveness pilot (N=60 clients) to assess the feasibility, effectiveness, and implementation of
the adapted PTSD intervention (v. treatment as usual) in a primary care clinic. Candidate: This Mentored
Patient-Oriented Research Career Development Award (K23) builds upon the candidate’s previous
experiences in clinical research focused on psychological adjustment following exposure to violence or
discrimination among multiple minority populations. The candidate’s long-term goal is to be an independent
implementation scientist focused on optimizing EBTs and care delivery models for PTSD. Training
Objectives: (1) The development of implementation packages for delivery of EBTs in non-specialty settings;
(2) Advanced training in pragmatic clinical trial design and mixed-methods data analysis and integration; and
(3) Integrated primary care and stepped care models for mental health service delivery. Training Activities:
Training will be achieved through mentorship by experts (Drs. A. Rani Elwy, Lisa Fortuna, Marylene Cloitre,
Alisa Lincoln, Mark Bauer, Margarita Alegria, and Bindu Kalesan), formal coursework at Boston University
School of Public Health, seminars, trainings, c...

## Key facts

- **NIH application ID:** 9971578
- **Project number:** 5K23MH117221-03
- **Recipient organization:** BOSTON MEDICAL CENTER
- **Principal Investigator:** Sarah E Valentine
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $185,759
- **Award type:** 5
- **Project period:** 2018-07-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9971578

## Citation

> US National Institutes of Health, RePORTER application 9971578, An implementation science approach to optimizing evidence-based treatments for posttraumatic stress disorder (PTSD) for non-specialty settings (5K23MH117221-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9971578. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*
