Modeling Professional Attitudes and Teaching Humanistic Communication to Remedy Implicit Bias and Promote Cultural Humility in Healthcare (MPathic-IBCH).

内隐偏见(IB)对黑人患者的医疗保健和健康结果产生负面影响。 医生IB损害了医患沟通的质量，侵蚀了信任和 信心，损害治疗决策和坚持，并造成患者伤害。研究 显示，平均而言，非黑人医生对黑人患者的IB水平适中。 由于大多数黑人患者看的是非黑人医生，这意味着大多数黑人患者会看到 拥有IB的内科医生。IB的沟通和加强的主要方式是 通过副声部行为(即，人们如何表达语音，如音调、音调、音量)和非 言语行为(即人们如何使用身体，如眼睛凝视、手势和身体 学习)，而不是在互动中的言语行为(即，人们所说的话)。当前IB 培训是无效的，因为他们依赖于相对简短的干预，这些干预只寻求在- 提高医生对他们患有IB的认识。虽然这是必要的第一步，但本身 这是不够的。IB培训还必须向学员展示他们在不知不觉中表现出的行为 并向他们传授具体的补救策略。 MCI在这笔赠款下的工作将产生有史以来第一个有效的IB培训系统。MPathic- IBCH是一种基于人工智能的新技术，它将使用Adapable增强双向通信 虚拟人(VH)交互，并提供详细、可操作的个性化反馈 学习者在不知不觉中表现出消极的非言语和副语言行为。要认识到Se- 与学习者IB相关的选定面部表情，MCI将实施专有系统 基于情绪面部动作编码系统(EMFACS)，该系统分析了 用于实时情绪状态分析的面部动作单元。我们会进一步加强响应能力- VHS的Ness具有与检测设计平行的基于EMFACS的面部索具设计。 此SBIR FastTrack将通过以下方式实现这一点：(PH1-1)识别密钥旁路和非路由- 系统地与亲白/反黑IB相关的BAL交流行为。(PH1-2) 开发和评估MPathic-IBCH原型以捕获关键通信行为- 在先前的研究中确定的IOR，并根据他们的种族IB水平区分医学生； (PH2-1)将MPathic-IBCH开发并集成到混合IB/文化谦逊曲线中- Lum；(PH2-2)将MPathic-IBCH构建为功能齐全、可在Web上部署的应用程序， 证明了非语言和语音韵律检测、人工智能、3个完整场景，并将其集成到 学习环境；以及(PH2-3)部署混合课程与MPathic-IBCH和VALUU- 评估对学生学习、交流行为和态度的影响，通过 SP绩效评级、MPathic-IBCH中的分数以及自我反思和体验。

Implicit bias (IB) negatively impacts the medical care and health outcomes of Black patients. Physician IB compromises the quality of patient-physician communication, eroding trust and confidence, impairing treatment decisions and adherence, and causing patient harm. Studies show that non-Black physicians, on average, have moderate levels of IB toward Black patients. Since most Black patients see non-Black physicians, this means that most Black patients see physicians with IB towards them. The main way in which IB is communicated and reinforced is via paraverbal behaviors (i.e., how people deliver speech, such as tone, pitch, volume) and non- verbal behaviors (i.e., how people use their body, such as eye gaze, hand gestures, and body leaning), as opposed to verbal behaviors (i.e., what people say) during interactions. Current IB training is ineffective because they rely on relatively brief interventions that seek only to in- crease physicians’ awareness about their having IB. While this is a necessary first step, by itself it is insufficient. IB training must also show learners the behaviors they unwittingly display due to their IB, and teach them concrete remediation strategies. MCI’s work under this grant will produce the first-ever effective IB training system. MPathic- IBCH is a new AI-based technology that will enhance two-way communication using adaptable virtual human (VH) interactions, and present detailed, actionable, personalized feedback on learners’ unwitting display of negative nonverbal and paraverbal behaviors. To recognize se- lected facial expressions associated with learner IB, MCI will implement a proprietary system based on the Emotion Facial Action Coding System (EMFACS) which analyzes combinations of facial action units for real-time emotional state analysis. We will further enhance the responsive- ness of VHs with an EMFACS-based facial rigging design that parallels the detection design. This SBIR FastTrack will accomplish this by: (Ph1-1) Identifying key paraverbal and nonver- bal communication behaviors systematically associated with pro-White/anti-Black IB. (PH1-2) Developing and evaluating an MPathic-IBCH prototype to capture a key communication behav- ior identified in prior research and to differentiate medical students based on their race IB levels; (Ph2-1) Developing and integrating MPathic-IBCH into a blended IB/Cultural Humility curricu- lum; (Ph2-2) Building MPathic-IBCH into a fully-featured, web-deployable application with im- proved nonverbal and speech prosody detection, AI, 3 full scenarios, and integrating it into a learning environment; and, (Ph2-3) Deploying blended curriculum with MPathic-IBCH and evalu- ating the effects on student learning, communication behaviors, and attitudes as measured by SP performance ratings, scores within MPathic-IBCH, and self-reflections and experiences.