Establishing an Artificially Intelligent Framework for Improving Therapeutic Alliance with Obese African American Youth and Caregivers through Multimodal Monitoring of Empathetic Accuracy and Interper

建立人工智能框架，通过共情准确性和 Interper 的多模式监测来改善肥胖非裔美国青年和护理人员的治疗联盟

• 批准号: 10710204
• 负责人: PHILLIPPE Belton CUNNINGHAM
• 金额: $ 52.26万
• 依托单位: MEDICAL UNIVERSITY OF SOUTH CAROLINA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-26 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10710204
• 关键词: Acceleration; Accounting; Address; Adolescent; Affect; African American; African American population; Age; Agreement; Applied Research; Artificial Intelligence; Basic Science; Behavior; Behavior Therapy; Caregivers; Classification; Client; Clinical; Clinical Skills; Clinical Trials; Community Health Aides; Competence; Cultural Backgrounds; Data; Deterioration; Development; Diabetes Mellitus; Discipline; Disparity; Dropout; Effectiveness; Elements; Emotional Bonds; Empathy; Ensure; Ethnic Population; Evidence based treatment; Family; Feedback; Future; Galvanic Skin Response; Gender; Geographic Locations; Goals; Health; Health Promotion; Health behavior change; Heart Rate; Influentials; Interpersonal Relations; Intervention; Intervention Trial; Laboratories; Link; Maintenance; Measures; Mediating; Methodology; Minority Groups; Modeling; Monitor; Natural Language Processing; Not Hispanic or Latino; Obesity; Outcome; Patient Self-Report; Personality; Physiological; Physiology; Prediction of Response to Therapy; Process; Process Assessment; Provider; Psychotherapy; Public Health; Race; Religion; Research; Research Design; Role; Rupture; Science; Scientist; Services; Sex Orientation; Signal Transduction; Therapeutic; Time; Time Series Analysis; Training; Treatment outcome; Voice; Wireless Technology; Work; Youth; analytical tool; behavior change; biopsychosocial; clinical encounter; clinical translation; cultural values; design; ethnic minority; ethnic minority population; heart rate variability; improved; innovation; machine learning model; minority children; multimodal data; multimodality; obesity treatment; practice setting; premature; primary caregiver; programs; racial population; randomized trial; recruit; repaired; response; skills; therapeutic development; therapy outcome; wearable device; wearable sensor technology

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. 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, by capitalizing on our recent work using innovative machine-learning (ML) models to thoroughly examine within-session therapy processes, 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. 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. 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 interventions and consistently predicts client change. 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, especially in a cross-race context, 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 a M-L classification model for differing degrees of empathy. This model could then be used to provide real-time feedback for therapists training to improve their empathic responses.

项目摘要/摘要。肥胖是所有种族/民族的一个重大公共卫生问题 群体、年龄、性别和地理区域，但某些群体比其他群体受到的影响更大。与非西班牙裔白人青少年相比，少数族裔青少年，尤其是 AA，肥胖的可能性不成比例。拟议的研究旨在改善由社区卫生工作者（CHW；治疗师）为非裔美国（AA）肥胖青少年（AAAO）提供的综合性多成分家庭行为干预（FIT Families）。该应用程序扩展了一项研究计划，该计划遵循肥胖相关行为干预试验 (ORBIT)，以开发行为治疗方法，利用我们最近的工作，使用创新的机器学习 (ML) 模型来彻底检查疗程内治疗过程，特别是在治疗 AAAO 及其主要照顾者时，CHW 同理心在治疗联盟 (TA) 的发展和维持中的作用。 TA 被认为是治疗的一个重要组成部分。 TA 由三个特征组成： 1. 治疗师与来访者之间的情感纽带； 2. 来访者与治疗师就治疗目标达成一致； 3. 就治疗任务达成一致。 TA 是一种动态、双向和协同的治疗元素，对客户和治疗师的种族、年龄和性别差异产生影响。治疗师的同理心对于建立和维持强大的TA至关重要，其结果由治疗联盟介导。同理心比具体干预措施更能解释治疗结果的差异，并且能够一致地预测来访者的变化。不幸的是，对关键的促进性人际交往技能（例如治疗师的同理心）的分析在技术上具有挑战性，因为他人行为的意图是微妙的、情境化的（例如，治疗师和客户在个性、背景、文化价值观等方面不同）和互动的（双向和协同的） ）；并且可以用多种方式表达（语气、生理学]）。为了更好地理解同理心，特别是在跨种族背景下，需要实证方法和分析工具来辨别实际临床遭遇中产生行为改变的同理心行为。我们将通过两项与同理心和治疗结果相关的措施来实施同理心：1）同理心准确性，定义为社区卫生工作者对客户状态的准确理解； 2) 人际生理同步性 (IPS)，定义为治疗师和客户 IPS 随时间变化的相关性（即心率 [HR]、HR 变异性、皮肤电反应、声音特征）。本研究使用这两种同理心测量来了解同理心、治疗联盟和治疗结果之间的关系。此外，该研究还将探讨共情效应如何根据治疗师-客户二人组的种族和性别一致性/不一致而变化。对于未来的临床翻译，收集到的音频和生理数据将用于构建不同程度共情的 M-L 分类模型。然后，该模型可以用于为治疗师培训提供实时反馈，以改善他们的共情反应。