Enhancing Clinical Decision-Making in Modular Youth Psychotherapy

增强模块化青少年心理治疗的临床决策

• 批准号: 10750872
• 负责人: Katherine Elizabeth Venturo-Conerly
• 金额: $ 4.02万
• 依托单位: HARVARD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10750872
• 关键词: Age; Agreement; Anxiety; Characteristics; Child; Client; Clinical; Clinical Trials; Code; Cognitive; Complex; Consultations; Data; Data Aggregation; Decision Making; Disease; Effectiveness; Elements; Family; Family Characteristics; Future; Goals; Growth; Individual; Intervention; Interview; Judgment; Length; Literature; Mental Depression; Mental Health; Mental Health Services; Meta-Analysis; Methods; Modeling; National Institute of Mental Health; Outcome; Patients; Persons; Provider; Psychotherapy; Randomized; Randomized, Controlled Trials; Recommendation; Research; Research Personnel; Sampling; Selection for Treatments; Series; Standardization; Statistical Models; Structure; Symptoms; Testing; Therapeutic; Trauma; Treatment Effectiveness; Treatment outcome; Work; Youth; archived data; career; clinical decision-making; clinical development; clinical practice; cognitive reappraisal; conduct problem; data-driven model; evidence base; flexibility; improved; improved outcome; individualized medicine; personalized medicine; predictive modeling; randomized trial; satisfaction; statistical learning; systematic review; tool; treatment as usual; virtual

Project Summary. Youths receiving mental healthcare often have multiple disorders, distinctive treatment- relevant personal and family characteristics, and problems that may shift during treatment. For these youths, modular psychotherapies, in which providers select from a menu of therapeutic elements to build personalized treatments, may be especially appropriate. One well-studied modular youth psychotherapy is Modular Approach to Therapy for Children with Anxiety, Depression, Trauma, or Conduct Problems (MATCH). In some trials with intensive, one-on-one expert support for element selection, MATCH significantly outperformed usual care and evidence-based standardized psychotherapies; but in trials with less intensive (more practically feasible) support, MATCH did not outperform usual care. This discrepancy highlights a key challenge of MATCH and other modular psychotherapies: selection of treatment elements. Because MATCH allows any number of sessions implemented in any order, a virtually unlimited array of treatment element sequences could be selected. This flexibility supports personalization but may also impact the effectiveness of MATCH and other modular psychotherapies, because it can be unclear which modules should be used when. As in other modular therapies, clinicians using MATCH are asked to use clinical judgment and are provided with decision- making guidance based on past literature and client weekly assessments. But research has shown that statistical decision-making models using archival data very often outperform clinician judgment. Currently, no modular youth psychotherapies employ data-driven statistical models to inform decision-making. This is understandable: no such models are currently available. The proposed study will be an initial step toward filling this gap; it will use statistical models of archival treatment data to provide decision-making guidance in modular youth psychotherapy, aimed at enhancing its efficiency and effectiveness. Per NIMH Priority 3.2, the proposed project will inform “tailoring existing interventions to optimize outcomes” by “reanalyzing… aggregated clinical trials” using “computational approaches… to facilitate clinical decision-making”. Specifically, the project will aggregate data from six MATCH trials (N=602, ages 6-15), to: model short-term between-person and within- person associations between use of each treatment element and subsequent symptom change at different stages of treatment (Aim 1); use statistical learning to identify moderators of these associations between elements and subsequent symptoms (Aim 2); and, in a holdout sample, test whether agreement between the model recommendations and youths’ treatment course predicts long-term treatment outcomes (Aim 3). To inform future development of clinical decision guidance tools (after the F31), clinicians will be interviewed about how model-based findings might be used in clinical practice (Exploratory Aim 4). Ultimately, consistent with NIMH priorities, this work may inform clinical decision making in youth psychotherapy in several data-driven ways, with the goal of eventually enhancing the efficiency and effectiveness of modular youth psychotherapies.

项目摘要。接受心理保健的年轻人通常患有多种疾病，独特的治疗 - 相关的个人和家庭特征，以及在治疗过程中可能会发生变化的问题。对于这些年轻人， 模块化心理治疗，其中提供商从治疗元素菜单中选择以建立个性化的元素 治疗可能特别合适。一个良好的模块化青年心理治疗是模块化的 焦虑，抑郁，创伤或进行问题的儿童治疗方法（匹配）。在某些人中 对元素选择的密集，一对一的专家支持的试验，匹配的表现明显优于常规 护理和基于证据的标准化心理治疗；但是在较少密集的试验中（实际上 可行的）支持，比赛并没有表现均超过通常的护理。这种差异突出了一个关键挑战 匹配和其他模块化心理治疗：治疗元素的选择。因为匹配允许任何 按任何顺序实施的会话数，几乎无限的治疗元素序列可以 被选中。这种灵活性支持个性化，但也可能影响匹配的有效性和 其他模块化心理治疗，因为尚不清楚应使用哪些模块。就像其他 模块化疗法，要求使用匹配的临床医生使用临床法官，并提供决定 - 根据过去的文献和客户每周评估进行指导。但是研究表明 使用档案数据的统计决策模型通常超过临床法官。目前，没有 模块化青年心理治疗员工数据驱动的统计模型，以告知决策。这是 可以理解的：目前没有此类模型可用。拟议的研究将是填补的第一步 这个差距；它将使用档案处理数据的统计模型来提供模块化的决策指导 青年心理疗法，旨在增强其效力和有效性。根据NIMH优先级3.2，提议 项目将通过“重新分析……聚合临床”来告知“定制现有干预措施，以优化结果” 使用“计算方法……促进临床决策”的试验。 来自六项匹配试验（n = 602，6-15岁）的汇总数据 每个治疗元素的使用与随后的症状在不​​同的情况之间的关联 治疗阶段（目标1）；使用统计学习来识别这些关联的主持人 元素和随后的症状（AIM 2）；并且，在保留样本中，测试是否达成共识 模型建议和青年的治疗课程预测长期治疗结果（AIM 3）。到 告知临床决策指导工具的未来开发（F31之后），将对临床医生进行采访 如何在临床实践中使用基于模型的发现（探索性目的4）。最终，与 NIMH优先事项，这项工作可能会在几个数据驱动的青年心理治疗中为临床决策提供信息 方式，目的是最终提高模块化青年心理治疗的效率和有效性。