An Adaptive Algorithm-Based Approach to Treatment for Adolescent Depression

基于自适应算法的青少年抑郁症治疗方法

• 批准号: 9533719
• 负责人: Meredith Lyn Gunlicks-Stoessel
• 金额: $ 58.32万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9533719
• 关键词: Address; Adolescence; Adolescent; Adult; Age; Algorithms; Attitude; Characteristics; Clinic; Communities; Decision Making; Development; Disease; Dose; Effectiveness; Evaluation; Experimental Designs; Family; Guidelines; Knowledge; Mediating; Mental Depression; Mental Health; Methods; Monitor; Movement; National Institute of Mental Health; Outcome; Outpatients; Parents; Patients; Precision Medicine Initiative; Process; Psychiatric Diagnosis; Psychotherapy; Randomized; Readiness; Reporting; Research; Risk; Schedule; Selective Serotonin Reuptake Inhibitor; Specific qualifier value; Suicide; Symptoms; Time; Treatment Effectiveness; Treatment outcome; Youth; base; child depression; cost effective; cost effectiveness; depressive symptoms; effective therapy; evidence base; functional disability; implementation strategy; improved; innovation; interpersonal therapy; public health priorities; randomized trial; recruit; response; satisfaction; theories; treatment as usual; treatment effect; treatment planning; treatment responders; treatment strategy

PROJECT SUMMARY Adolescent depression is a prevalent and debilitating disorder that places youth at risk for suicidality, other psychiatric diagnoses, and functional impairment both during adolescence and into adulthood. There are a number of effective treatments; however, 30-50% of adolescents who receive these treatments do not respond. To improve response rates, practice parameters recommend routine systematic symptom assessment over the course of treatment to inform decisions regarding whether to switch or augment treatment. Research also demonstrates that regular symptom monitoring improves treatment outcomes. Unfortunately, routine symptom assessment in usual care for adolescent depression is extremely rare. In addition, for psychotherapy, which is the most frequent treatment for adolescent depression, there are currently no guidelines to direct therapists regarding how to use those symptom assessments to guide subsequent treatment decisions. Addressing this critical knowledge gap requires identifying (1) what symptoms or patient characteristics to assess, (2) when to administer those assessments, and (3) what subsequent treatment to provide, based on those assessments. Adaptive treatment strategies (ATSs) provide algorithms for guiding treatment decision making. These algorithms are based on patient characteristics and outcomes collected during the course of therapy, and they provide guidelines regarding when, how, and for whom midcourse changes in the treatment approach should be initiated. ATSs can be developed and validated within the context of an innovative experimental design called a sequential multiple assignment randomized trial (SMART). In a SMART, subjects can be randomized multiple times and these randomizations occur sequentially through time at selected critical decision points. The results of the SMART are used to define the decision rules that make up the ATS. The purpose of the current study is to evaluate the effectiveness of two ATSs for adolescent depression. The ATSs include delivery of an evidence-based psychotherapy for adolescent depression (interpersonal psychotherapy, IPT-A), systematic symptom monitoring, and an empirically-derived algorithm that specifies whether, when, and how to augment IPT-A. 200 depressed adolescents (age 12-18) will be recruited to participate in a 16-week SMART conducted in an outpatient community mental health clinic. The aims of this R01 are to (1) evaluate the effectiveness of the ATSs embedded in this trial, (2) evaluate adolescents' interpersonal functioning as a treatment target of IPT-A, (3) evaluate moderators of initial treatment and treatment augmentation strategies, and (4) conduct a process evaluation to identify barriers and facilitators that influenced ATS implementation.

项目摘要 青少年抑郁症是一种普遍存在的、使人衰弱的疾病，它使青少年处于自杀的危险之中， 精神病诊断，以及青春期和成年期的功能障碍。有 有效治疗的数量;然而，接受这些治疗的青少年中有30-50%没有 回答。为了提高应答率，实践参数推荐常规系统症状 在治疗过程中进行评估，以决定是否转换或增加 治疗研究还表明，定期监测症状可以改善治疗效果。 不幸的是，常规的症状评估在青少年抑郁症的日常护理是非常罕见的。在 此外，对于心理治疗，这是最常见的治疗青少年抑郁症，目前有 没有指导治疗师如何使用这些症状评估来指导后续治疗的指南。 治疗决定。解决这一关键的知识差距需要确定（1）什么症状或患者 评估的特征，（2）何时进行这些评估，以及（3）随后的治疗 根据这些评估结果。自适应治疗策略（ATS）提供了指导算法， 治疗决策。这些算法基于收集的患者特征和结果 在治疗过程中，他们提供了关于何时，如何以及为谁进行中期治疗的指导方针。 应开始改变治疗方法。ATS可以在 一个创新的实验设计，称为序贯多重分配随机试验 （SMART）。在SMART中，受试者可以接受多次随机化，这些随机化发生在 在选定的关键决策点按时间顺序进行。SMART的结果用于定义 决策规则组成了ATS。本研究的目的是评估两种方法的有效性。 青少年抑郁症的ATS。ATS包括提供基于证据的心理治疗， 青少年抑郁症（人际心理治疗，IPT-A），系统的症状监测，以及 指定是否、何时以及如何增强IPT-A的计算机派生算法。200抑郁症 将招募青少年（12-18岁）参加在门诊进行的16周SMART 社区心理健康诊所本R 01的目的是（1）评估ATS的有效性 嵌入在本试验中，（2）评估青少年的人际功能作为IPT-A的治疗目标，（3） 评估初始治疗和治疗增强策略的调节者，以及（4）进行一个过程 开展评价，以查明影响安非他明类兴奋剂实施的障碍和促进因素。