A Crowd-Powered Technological Treatment for Depression and Anxiety

摘要 抑郁和焦虑是美国最常见的精神健康障碍。 以技术为基础的干预是治疗抑郁症和焦虑症的具有成本效益的治疗选择。一次 虽然已开发，但剩余费用来自干预过程中的人力支助。虽然 人力支持通常会提高此类干预的参与度和有效性，但额外的成本 大大降低了它们的可扩展性和可持续性。需要开发创新的干预措施，以 在不使用专业人员的情况下实现类似的结果。 目前的提案旨在开发、优化和评估一个以人群为动力的干预平台 抑郁和焦虑，并检查可伸缩性的设置。这些大众驱动的工具将从证据中提取- 基于与认知行为治疗策略一致的跨诊断治疗原则。在 目前的建议，我们会追求三个具体目标，包括：(1)发展和优化 干预平台，(2)检查潜在的基于社区和实践的可扩展性设置，(3)试点 在为期八周的双臂随机试点试验中，该平台的有效性。我们还将评估以下方面的程度 平台使用与我们的概念模型一致的假定目标，包括个人 相关性、问责制、技能使用和技能掌握。 这项研究的长期目标是帮助创建基于技术的干预措施， 在不依赖专业人员的情况下整合人力支持和智能。这样的干预可能是 在规模上提供，并解决由抑郁和焦虑引起的疾病的实质性负担。这 R34提案将对该平台的有效性进行试点，并收集有关可行性的初步数据， 抑郁和焦虑症状的可接受性、可接受性、安全性和变化。我们还将检查 可伸缩性设置，以更好地指导此平台的未来部署和评估。这些数据将对我们有所帮助 支持评估更大规模的平台部署的后续R01提案。研究团队 结合临床心理学、人机交互和众包方面的跨学科专业知识。 该计划与美国心理健康组织合作，共同开发和提供与他们的 每天达到2000-3000人的筛查平台。一个有效的干预平台可以到达 数百万人通过该筛查平台，并代表了一种接触有需要的人的新方式。 这一拟议的项目有望为心理健康治疗带来革命性的变化。一个 大众支持的平台可以在不牺牲效率的情况下进行扩展，有效地利用 数百万人用来治疗数百万人。此外，通过该平台创建的系统信息语料库可以 通过强调有效的方法和新的解决方案，帮助指导未来的干预研究。

Abstract 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.