SBIR/STTR Research Award

Improving adherence and outcomes in evidence-based treatment for OCD: Type I Effectiveness-Implementation RCT and Scaled Development of OC-Go, a crowdsourced interactive patient-provider tool

Award identifier 455c93b2ec9baa93931f5ca5999a0210b69620fe7d9bdcd21aa07c09da2e7705Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$449,958

Program and phase

STTR · Phase I

Award year

2025

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
VirtuallyBetter Health LLC
Proposal award date
2025-09-12
Contract end date
2026-08-31
UEI
GJUEBV9WHDG5
Solicitation number
PA24-248
Topic code
104

Research abstract

PROJECT SUMMARY/ABSTRACT The long-term goals of this proposal are to improve treatment adherence and clinical outcomes in evidence- based treatment (EBT) for obsessive compulsive disorder (OCD), a high base rate disorder and leading cause of disability worldwide. Guidelines uniformly recommend exposure and response prevention (ERP) as the front- line treatment. Meta-analyses consistently find large ERP effects, with about half of treatment completers attaining complete remission. Yet, up to 40% of patients do not fully respond. Patient adherence to treatment tasks between sessions, i.e., homework adherence, is by far the strongest predictor of treatment outcomes. Thus, improving such adherence will likely produce greater OCD reductions. The literature indicates that a lack of real- time support for patients between sessions and a lack of support for therapists after initial ERP trainings to learn how to prioritize homework assignments in practice both contribute to poor ERP outcomes. Yet, standards to support homework rely on pen-and-paper tracking methods, which have not changed in 40 years. Thus, new solutions are needed to enhance adherence and improve clinical outcomes, in line with NIMH Strategic Objectives 3.2, 3.3B, 4.2, and 4.3. OC-Go is a novel interactive digital health tool designed to improve ERP adherence by leveraging the empirical predictors of adherence. The platform allows therapists to create and push tailored multimedia behaviorally interactive assignments to patient mobile devices, providing step-by-step real- time interactive guidance and homework support, facilitating a means for clinicians and experts to “appify” behavioral health protocols without having to know how to code, and a means to share created activities to a curated and searchable public library for other therapists to learn from and use. Thus, OC-Go facilitates experiential support in practice for both patients and clinicians, leveraging mHealth, asynchronous telehealth, and crowdsourcing for a new paradigm of high-fidelity CBT implementation. Early prototype testing in a small RCT pilot demonstrated that OC-Go increased adherence by 22% and doubled the modeled treatment effect. The platform also scored high on usability measures, however next-stage development of critical features is required to support at scale crowdsourcing and commercialization. Phase I aims of this Fast-Track proposal are to develop and test those required functions using a national sample of 105 ERP therapists to provide staged feedback for agile development. Phase II aims are to: 1) test the effectiveness of OC-Go for improving homework adherence and clinical outcomes, and 2) identify and address implementation barriers via a hybrid Type I effectiveness- implementation RCT (N = 160 patients, 60 therapists) in the OCD & Anxiety Center (OAC) outpatient network. The proposal is supported by NIMH recommendations for tools to improve EBT adherence and for peer-to-peer learning tools in networks, a well-specified commercialization plan, OAC intention of contracting given positive results, and interest from over 100 clinicians, dozens of mental health institutions, an exceptional assembly of thought leaders and developers of 16 EBTs, and Oxford University Press, the leading publisher of EBT manuals.

Technology keywords

Not reported

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Agency intelligence

Department of Health and Human Services

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