Clinical Trial of the Fit Families Multicomponent Obesity Intervention for African American Adolescents and Their Caregivers: Next Step from the ORBIT Initiative

项目总结/摘要。肥胖是所有种族/民族的重大公共卫生问题 群体、年龄、性别和地理区域，但有些群体比其他群体受到的影响更大。 少数民族青少年，尤其是AA，相对于非西班牙裔青少年， 白色半导体。29，30拟议的研究旨在改善一个全面的多组分系列- 社区卫生工作者（CHW;治疗师）提供的基于行为干预（FIT家庭）， 非裔美国人（AA）肥胖青少年（AAAO）。该应用程序扩展了一项研究计划， 遵循肥胖相关行为干预试验（ORBIT）开发行为治疗， 通过利用我们最近的工作，使用创新的人工智能技术， 疗程内治疗过程（即，行动机制），特别是CHW同情的作用， 在治疗AAAO及其主要照顾者的同时，发展和维持治疗联盟（TA）。 TA被认为是治疗的基本要素。32 TA由三个特征组成：1.情感纽带 治疗师和客户之间; 2。客户和治疗师之间对治疗目标的协议;和3。 在治疗任务上达成一致。33 TA是一种动态的、双向的、协同的治疗元素， 在种族，年龄和性别的客户和治疗师的差异的影响。治疗师的同理心至关重要 在建立和维持一个强大的TA，结果介导的治疗联盟。同理心 解释了治疗结果比特定干预更大的差异34，并始终预测客户 35不幸的是，对关键的促进性人际交往技能（如治疗师同情）的分析， 技术上具有挑战性，因为另一个人的行为的意图是微妙的，上下文的（例如，治疗师和客户不同 性格、背景、文化价值观等），和互动（双向和协同）;并可以 以多种方式表达（语音语调，生理学）。为了更好地理解同理心， 方法和分析工具，可以辨别移情行为在实际的临床遇到， 行为改变我们将通过两个与同理心相关的测量来操作同理心 1）移情准确性，定义为CHW对客户的准确理解 状态; 2）人际生理同步（IPS），定义为治疗师和客户之间的相关性 IPS随时间的变化（即，心率[HR]、HR变异性、皮肤电反应、语音特征）。这项研究使用这些 两个共情措施，以了解共情，治疗联盟和治疗之间的关系 结果。此外，本研究还将探讨共情如何影响基于种族和性别的变化 治疗师-来访者二元关系的一致性/不一致性。为了未来的临床翻译，音频和生理 收集到的数据将用于建立不同同理心程度的分类模型。这个模型可以 用于为治疗师培训提供实时反馈，以改善他们的移情反应。

PROJECT SUMMARY/ABSTRACT. Obesity is a significant public health concern among all racial/ethnic groups, ages, gender, and geographic areas, but some groups are more disproportionately affected than others. Ethnic minority adolescents, especially AAs, are disproportionately likely to be obese relative to non-Hispanic White adolescents.29,30 The proposed study is designed to improve a comprehensive multicomponent family- based behavioral intervention (FIT Families) delivered by Community Health Workers (CHWs; therapists) for African American (AA) adolescents with obesity (AAAO). This application expands a program of research that has followed the Obesity Related Behavioral Intervention Trials (ORBIT) for developing behavioral treatments,31 by capitalizing on our recent work using innovative artificial intelligence technologies to thoroughly examine within-session therapy processes (i.e., mechanisms of action), specifically the role of CHW empathy in the development and maintenance of the therapeutic alliance (TA) while treating AAAO and their primary caregivers. TA is considered an essential element of therapy.32 The TA is composed of three features: 1. Emotional bond between therapist and client; 2. Agreement between the client and therapist on the goals of treatment; and 3. Agreement on the tasks of therapy.33 TA is a dynamic, bidirectional, and synergistic element of therapy with implications across differences in race, age, and gender of the client and therapist. Therapist empathy is critical in establishing and maintaining a strong TA, with outcomes mediated by the therapeutic alliance. Empathy accounts for more variance in therapy outcome than specific interventions34 and consistently predicts client change.35 Unfortunately, analysis of crucial facilitative interpersonal skills such as therapist empathy is technically challenging as the intent of another's behavior is nuanced, contextual (e.g., therapists and client differ in personality, background, cultural values, etc.), and interactive (bidirectional and synergistic); and can be expressed in multiple ways (voice tone, physiology]). To better understand empathy, requires empirical approaches and analytical tools that can discern empathetic behaviors in actual clinical encounters that produce behavior change. We will operationalize empathy through two measures that are each associated with empathy and treatment outcomes: 1) Empathic accuracy, defined as the CHW's accurate understanding of the client's state; and 2) Interpersonal physiological synchrony (IPS), defined as the correlation between therapist and client IPS over time (i.e., heart rate [HR], HR variability, galvanic skin response, voice features). This study uses these two empathy measures to understand the relationship between empathy, therapeutic alliance, and treatment outcomes. Further, the study will explore how empathy effects change based on the race and gender concordance/discordance of therapist-client dyads. Toward future clinical translation, the audio and physiological data collected will be used to build classification models for differing degrees of empathy. This model could then be used to provide real-time feedback for therapists training to improve their empathic responses.