Digital Mental Health Service for Non-Treatment Seeking Young Adults

为不寻求治疗的年轻人提供数字心理健康服务

• 批准号: 10461855
• 负责人: DAVID CURTIS MOHR
• 金额: $ 28.29万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-04 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10461855
• 关键词: Address; Adherence; Adult; Affect; Americas; Anxiety; Anxiety Disorders; Attitude; Behavioral; Characteristics; Chronic; Complex; Coping Skills; Development; Dropout; Early treatment; Effectiveness; Feeling suicidal; Future; Goals; Health Services Accessibility; Human; Individual; Intervention; Investigational Therapies; Learning; Length; Life; Link; Machine Learning; Major Depressive Disorder; Measures; Mediating; Mental Depression; Mental Health; Mental Health Services; Methods; Modeling; Motivation; Online Systems; Outcome; Participant; Patient Recruitments; Persons; Pharmaceutical Preparations; Pharmacotherapy; Process; Psychiatric therapeutic procedure; Psychotherapy; Randomized; Randomized Controlled Trials; Research; Risk; Self Management; Services; Severities; Symptoms; Technology; Telephone; Text Messaging; Time; United States; Voice; Waiting Lists; Work; adaptive intervention; advocacy organizations; age group; aged; anxiety symptoms; base; community setting; depressive symptoms; design; diagnostic criteria; digital; digital mental health; effectiveness evaluation; experience; feasibility trial; health literacy; human model; improved; interest; iterative design; online community; preference; preventive intervention; psychoeducational; psychologic; psychological distress; psychological outcomes; psychological symptom; reduce symptoms; screening; secondary outcome; self reliance; skills; social stigma; symptom self management; text messaging intervention; therapy design; treatment duration; treatment trial; web site; young adult

PROJECT SUMMARY Young adults aged 18-24 experience higher levels of mental health problems than any other adult age group. Over one quarter of all young adults living in the United States suffer from a mental health condition. Unfortunately, they are the adult age group who are least likely to seek or receive traditional face-to-face treatments such as in-person psychotherapy or pharmacotherapy. There is evidence that they are, however, interested in using digital mental health interventions (DMHIs), such as mobile and web-based apps, to support symptom self-management and skill building. While evidence suggests mental health apps can effectively reduce symptom severity, they require motivation from the user to open and use the app, which contributes to the high dropout rates. The primary method of addressing dropout has been the use of human coaching, which boosts engagement. SMS text messages arrive through the most commonly used app on the phone, and are therefore likely to be viewed. Initial work in text message interventions suggests good adherence, as effort is low, but effectiveness has been inconsistent. Messages can be perceived as off-target or impersonal, and it is difficult to convey more complex information. This project aims to address these problems by developing and piloting a personalized text messaging platform that uses machine learning to tailor SMS messages to an individual’s needs and preferences, and URL links to provide access to psychoeducational content to contextualize messages, when the length of that content exceeds the limitations of messages. This project will include a partnership with Mental Health America, the nation’s largest mental health advocacy organization. The primary goals of the project are to: (1) Develop an adaptive messaging service for young adults that personalizes messages and psychoeducational content to the needs and preferences of an individual, (2) Conduct a feasibility trial using a sequential multiple assignment randomized treatment (SMART) design, which will evalutate (a) the effectiveness of an adaptive, personalized messaging intervention in reducing engagement relative to a static version; and (b) whether human coaching results in greater symptom reduction and engagement, relative an unguided implementation. This project will, in the near term, allow us to determine the feasibility of this intervention, including whether our adaptive intervention affects treatment psychological and engagement targets, and reduces psychological distress. It will also provide preliminary information on the feasibility of a scalable model of targeted, low- intensity coaching for users who may require additional support above and beyond a fully automated intervention. This will prepare us for our longer-term goal of conducting a fully-powered randomized controlled trial of our adaptive intervention in an online community setting.

项目摘要 年龄在18-24岁的年轻人经历的心理健康问题水平高于任何其他成年年龄 团体。居住在美国的所有年轻人中有四分之一以上患有精神健康状况。 不幸的是，他们是成年年龄段，他们最不可能寻求或接受传统的面对面 诸如面对面心理治疗或药物治疗之类的治疗方法。有证据表明他们是 有兴趣使用数字心理健康干预措施（DMHIS），例如移动和基于Web的应用程序，以支持 症状自我管理和技能建设。虽然证据表明心理健康应用程序可以有效 减轻症状严重程度，他们需要用户的动机打开和使用该应用程序，这有助于 高辍学率。解决辍学的主要方法是使用人类教练，这是 提高参与度。 SMS短信通过电话上最常用的应用程序到达，因此很可能 被查看。文本消息干预措施中的初始工作表明良好的依从性，因为努力很低，但是 有效性是不一致的。消息可以被视为脱离目标或非个人化，这很困难 传达更复杂的信息。该项目旨在通过开发和试行一个来解决这些问题 个性化的文本消息平台，该平台使用机器学习将SMS消息量身定制到个人的 需求和偏好以及URL链接，以提供对心理教育内容的访问权 消息，当该内容的长度超过消息的限制时。该项目将包括一个 与美国最大的心理健康倡导组织美国心理健康的合作伙伴关系。 该项目的主要目标是：（1）为年轻人开发自适应消息服务 个性化信息和心理教育内容满足个人的需求和偏好，（2） 使用顺序多个分配随机治疗（智能）设计进行可行性试验，该设计 将评估（a）自适应，个性化的消息干预措施减少的有效性 相对于静态版本的参与度； （b）人类教练是否会导致更大的症状减轻 和参与，相对无指导的实施。 该项目将在短期内允许我们确定此干预的可行性，包括是否是否 我们的适应性干预会影响治疗心理和参与目标，并减少心理 困扰。它还将提供有关针对性，低 - 的可伸缩模型可行性的初步信息 强度指导可能需要超过完全自动化的用户，可能需要额外的支持 干涉。这将使我们为进行完全供电的随机控制的长期目标做好准备 在在线社区环境中对我们的适应性干预进行试验。