A Crowd-Powered Technological Treatment for Depression and Anxiety

一种针对抑郁和焦虑的大众技术治疗方法

• 批准号: 9884815
• 负责人: Stephen Schueller
• 金额: $ 22.11万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-03-05 至 2022-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9884815
• 关键词: Accountability; Address; American; Americas; Anxiety; Area; Behavioral; Clinical Psychology; Clinical Treatment; Cognitive; Cognitive Therapy; Communities; Crowding; Data; Development; Effectiveness; Elements; Evaluation; Evidence based intervention; Focus Groups; Future; Goals; Health Technology; Human; Individual; Intelligence; Internet; Intervention; Intervention Studies; Interview; Knowledge; Learning; Mediating; Mental Depression; Mental Health; Mental Health Services; Mental disorders; Modeling; National Institute of Mental Health; Online Systems; Outcome; Population; Preventive Intervention; Public Health; Randomized; Research; Research Support; Resources; Safety; Strategic Planning; Symptoms; System; Technology; Testing; Therapeutic Intervention; Training; United States; Work; base; burden of illness; care systems; cognitive reappraisal; community organizations; computer human interaction; cost; crowdsourcing; depressive symptoms; design; digital; effective intervention; effective therapy; effectiveness trial; evidence base; experience; experimental study; field study; handheld mobile device; health care delivery; improved; informant; innovation; intervention cost; mobile application; new technology; novel; online community; patient oriented; peer; personalized strategies; pilot trial; posters; primary outcome; psychologic; response; scaffold; screening; service intervention; skills; stem; tool; treatment response; usability; web site

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.

摘要 抑郁症和焦虑症是美国最常见的心理健康疾病。 基于技术的干预措施是治疗抑郁症和焦虑症的具有成本效益的选择。一旦 除已开发的外，其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这些干预措施的参与度和有效性， 大大降低了其可扩展性和可持续性。需要制定创新的干预措施， 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、优化和评估一个群体动力干预平台， 抑郁和焦虑，并检查设置的可扩展性。群体动力工具将从证据中提取- 基于transdiagnosis治疗原则与认知行为治疗策略一致。在 目前的建议，我们将追求三个具体目标，包括：（1）发展和优化 干预平台，（2）检查潜在的社区和实践为基础的设置的可扩展性，（3）试点 在为期8周的双臂随机试点试验中，该平台的有效性。我们还将评估 该平台参与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， 整合人力支持和智能，而不依赖专业人员。这些干预措施可以是 大规模提供，解决抑郁和焦虑造成的巨大疾病负担。这 R34提案将试点该平台的有效性，并收集有关可行性的初步数据， 可接受性、可接受性、安全性以及抑郁和焦虑症状变化。我们亦会研究 可扩展性设置，以更好地指导该平台的未来部署和评估。这些数据将帮助 支持后续的R 01提案，评估更大规模的平台部署。研究团队 结合了临床心理学，人机交互和众包的跨学科专业知识。 该提案与美国心理健康协会合作，开发和提供与其 每天可达2000-3000人的筛查平台。一个有效的干预平台可以 数以百万计的人通过这个筛选平台，代表了一种接触有需要的人的新方式。 该项目预计将为心理健康治疗带来革命性的变化。一 群众驱动的平台可以在不牺牲效率的情况下扩展，有效地利用了 治疗数百万人。此外，通过该平台创建的系统信息库可以 通过强调有效的方法和新颖的解决方案，帮助指导未来的干预研究。