Dance4Healing: a feasibility study to reduce health disparity and increase engagement of an intergenerational telehealth program for minority diabetes patients and their care partners.

项目总结/摘要 34.2 M美国糖尿病患者（DM）在2018年花费了327 B美元1-2。68%的人将死于心血管疾病3。疾病控制中心报告说，糖尿病对少数群体的影响不成比例。Palaniappan博士是糖尿病患者健康差异和运动/舞蹈干预研究的先驱，这项创新将扩大研究领域，并对少数民族健康产生更广泛的影响。目前，缺乏关于正常体重糖尿病患者（NWD）有效生活方式建议的数据，占1/5的II型糖尿病患者。NWD在亚洲人群和老年人中尤其普遍，其死亡率高于肥胖糖尿病患者4。研究表明，舞蹈可以改善糖尿病，并将心血管死亡率降低46%。五、然而，这些干预措施只能亲自提供。有许多锻炼计划和实时视频工具，但它们很少满足个人的移动性和无障碍需求。因此，存在对易于采用的远程医疗平台的未满足的需求，该平台吸引患者在家跳舞。在NIMHD少数民族健康和健康差异研究框架的指导下，该项目将研究多个种族/民族因素对健康行为的影响，并使用创意艺术疗法（CAT：音乐，舞蹈，艺术）开发一种文化敏感的新型习惯建立算法，用于远程活动参与系统，具有多级跟踪和有效的行为提示。Dance 4 Healing（D4 H）专有的个性化服务将根据用户的需求/愿望进行定制，并找到兼容的伙伴，通过预先录制的视频课程和现场视频课程建立持久的习惯（想想YouTube + Zoom + eHarmony的健康伙伴）。这项可行性研究将与斯坦福大学教授和老龄化研究所合作，开发一个突破性的智能平台，集成生物传感器和远程医疗实时视频平台（TLVP）。我们在糖尿病和心血管健康、生物追踪、行为科学、舞蹈疗法和数据/人工智能科学方面的多学科专家团队将追求以下目标：目标1：针对不同的移动性、可访问性需求、潜在的语言障碍、整合文化意识和识别有效的行为提示定制D4 H TLVP的用户研究。里程碑：12个定性的1小时用户访谈，以获得对当前程序和UI设计的反馈。目标2：通过为期8周的正念运动远程医疗计划构建和测试生物传感器集成（Garmin vivosmart® 4，Omron Scale）的可行性。成功率：至少80%的参与者成功使用平台生物传感器。目标3：开发一种与NIMHD研究框架保持一致的新型AI算法，并进行多级跟踪，并测试其在个性化推荐和根据偏好，能力和需求量身定制的好友匹配中的可行性。主要任务：1）开发偏好数据、自报数据与EHR数据的数据收集和整合方法。2)根据这些数据开发AI算法。该项目的成功将为美国心脏协会的多中心试验的第二阶段奠定基础，并改善3420万糖尿病美国人的生活质量，进一步推动D4 H成为连接艺术和健康的经验领导者的愿景。

PROJECT SUMMARY/ABSTRACT 34.2 M Americans with Diabetes Mellitus (DM) cost $327 B in 2018 1-2 . 68% of them will die from cardiovascular disease 3 . CDC reported that DM disproportionately affects minorities. Partnering with Dr. Palaniappan, who has pioneered research on health disparities and exercise/dance intervention for DM patients, this innovation will expand the research field and have a broader impact on minority health. Currently, there is a lack of data on effective lifestyle recommendations for normal-weight diabetics (NWD), accounting for 1 in 5 Type II DM patients. NWD is especially prevalent in Asian populations and the elderly, facing higher mortality rates than obese diabetics 4 . Research shows dance improves DM and reduces cardiovascular deaths by 46%. 5 . These interventions, however, are only available in person. There are many exercise programs and live video tools, but they rarely cater to an individual’s mobility and accessibility needs. Hence, there is an unmet need for an easy-to-adopt telehealth platform enticing patients to dance from home. Guided by The NIMHD Minority Health and Health Disparities Research Framework, this project will study the effects of multiple races/ethnicities factors on health behaviors, and develop a culturally sensitive novel habit-building algorithm using Creative Arts Therapy (CAT: Music, Dance, Arts) for remote activity engagement systems with multilevel tracking and effective behavior prompts. Dance4Healing’s (D4H) proprietary personalization will tailor to users’ needs/desires, and find compatible buddies to build lasting habits with pre-recorded and live video classes (think YouTube + Zoom + eHarmony for health buddies). This feasibility study will partner with Stanford professors and the Institute on Aging to develop a groundbreaking smart platform integrating biosensors and a Telehealth Live Video Platform (TLVP). Our multidisciplinary team of experts in diabetes and cardiovascular health, biotracking, behavioral sciences, dance therapy, and data/AI science will pursue the following aims: AIM 1: User research on tailoring D4H TLVP to varied mobility, accessibility needs, potential language barriers, integrating cultural awareness, and identifying effective behavior prompts. Milestones: 12 qualitative 1-hour user interviews for feedback on the current program and UI design. AIM 2: Build and test the feasibility of biosensor integration (Garmin vivosmart® 4, Omron Scale) through an 8-week Mindful Movement telehealth program. Milestones: Successful use of platform biosensors by at least 80% of participants. AIM 3: Develop a novel AI algorithm aligned with NIMHD Research Framework with multilevel tracking and test its feasibility in personalized recommendations and buddy matching tailored to preferences, abilities, and needs. Milestones: 1) Develop data collection and integration methods for preference data, self-reported data with EHR data. 2) Develop an AI algorithm based on this data. Success of this project will lay the groundwork for Phase II for a multicenter trial with American Heart Association, and improve QoL for 34.2 M diabetic Americans, furthering D4H’s vision to become an experience leader bridging art and health.