Depression and anxiety are the most common mental health disorders in the United States. Technology-based interventions are cost-effective treatment options for depression and anxiety. Once developed, the remaining costs stem from human support during the course of the intervention. Although human support typically boosts the engagement with and efficacy of such interventions, the additional costs substantially reduce their scalability and sustainability. Innovative interventions need to be developed that can achieve similar outcomes without the use of professionals. The current proposal aims to develop, optimize, and evaluate a crowd-powered intervention platform for depression and anxiety and examine settings for scalability. The crowd-powered tools will draw from evidence- based transdiagnostic treatment principles consistent with strategies in cognitive-behavioral therapy. In the current proposal, we will pursue three specific aims including: (1) development and optimization of the intervention platform, (2) examine potential community- and practice-based settings for scalability, (3) pilot the effective of the platform in an eight-week two-armed randomized pilot trial. We will also evaluate the extent to which the platform engages putative targets consistent with our conceptual model including personal relevance, accountability, skills use and skills mastery. The long-term goal of this research is to aid the creation of technology-based interventions that integrate human support and intelligence without relying on professionals. Such interventions could be provided at scale and address the substantial burden of disease resulting from depression and anxiety. This R34 proposal will pilot the effectiveness of this platform and gather preliminary data regarding feasibility, acceptability, acceptability, safety, and changes in symptom of depression and anxiety. We will also examine settings for scalability to better guide future deployments and evaluations of this platform. This data will help support a subsequent R01 proposal evaluating a larger deployment of the platform. The research team combines interdisciplinary expertise in clinical psychology, human-computer interaction, and crowdsourcing. This proposal partners with Mental Health America to develop and provide the platform in connection with their screening platform which reaches 2000-3000 people per day. An effective intervention platform could reach millions through that screening platform and represent a novel way to reach those in need. This proposed project is expected to present a revolutionary change in mental health treatment. A crowd-powered platform could be scaled without sacrificing efficacy, effectively harnessing the wisdom of millions to treat millions. Furthermore, the corpora of systematic information created through this platform could help guide future intervention research by highlighting effective approaches and novel solutions.

Public Health Relevance

Nearly 70 million Americans each year will experience depression or anxiety. Current treatments are insufficient to meet this need, as nearly 80% of people with a diagnosable mental disorder receive no treatment whatsoever. This project develops and evaluates a novel, technology-based intervention that uses crowd sourcing to help provide evidence-based intervention strategies to people at scale.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Planning Grant (R34)
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Special Emphasis Panel (ZMH1)
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Haim, Adam
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University of California Irvine
Schools of Arts and Sciences
United States
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