Virtual Reality Cognitive Therapy forAlzheimer's Disease

摘要 阿尔茨海默病(AD)和阿尔茨海默病相关痴呆症(ADRD)目前影响着超过5.8人 百万美国人，2020年治疗和管理成本为3050亿美元，并导致以下不良结果 由于丧失了独立性，生活质量低，对养老院的要求。考虑到减少的规模 与健康相关的生活质量，需要无创、可定制的认知障碍(CI)靶向方法 帮助AD患者势在必行。非常需要有效的个性化数字干预措施 在新冠肺炎大流行的情况下，AD患者可以与社会保持距离。 Claritytek建议开发一种基于证据的、非侵入性的、针对个体认知老化的新型工具 以改善AD/ADRD患者的生活质量。虚拟现实认知疗法(VRCT)利用四个 三管齐下：评估、教育、治疗和跟踪。VR是身临其境的，将患者与周围环境隔离 分心--对任何CI干预都至关重要。对阿尔茨海默病的认知干预应考虑认知的各个方面 缺陷，特别是影响日常生活活动(ADL)和工具性ADL(工具性ADL)的技能。VRCT的目标是 治疗影响AD患者的IADL障碍。VRCT培训活动旨在模拟真实情况， 量身定做，在发生情景中参与、适应、挑战和模拟逼真的CI生成场景。 利用VRCT，通过游戏循环反复暴露于CI场景中，逐步培训患者有用的 技能：预约医疗、服药、购物、记住名字、面孔和方向 地方--维护和提高功能独立性。我们的系统将包括一个可选模式 无需面对面接触的异步在线治疗师咨询，在新冠肺炎隔离期间很有价值。 我们将扩大、调整和建立我们的团队之前成功的工作，阿尔茨海默氏症患者的CI，排名 在国际数字健康大赛上，世界上排名前五的创新之一。 我们将与HealthPartners阿尔茨海默氏症研究神经科学中心的专家合作 领导试验并帮助设计、开发和优化VRCT。我们将结合利益相关者的反馈来创建 一种以患者为中心的干预措施，针对与IADL相关的四个特定的优先顺序的“CI”，利用 数字治疗发展框架。为了指导该项目，我们将创建一个多学科的专家焦点 组(EFG)。 在目标1中，我们将评估VRCT在36例轻度AD/ADRD患者中的可行性、可用性和可接受性 在七周内缓解脑梗塞。我们将进行三个试验，每个试验有n=12个队列，总共n=36个 参与者。除了患者对治疗的反应外，评估的重点将是认知 耐受性，作为目标患者有CI。每次试验的结果将在目标2中迭代应用以进行修订 在下一次试验前进行VRCT，产生最可接受的CI干预。 在目标2中，我们将基于患者的反馈反复重新设计、开发、单元测试和优化VRCT 试验和EFG分析。我们希望确定VRCT将是可行的、可用的和可接受的 可用性规模成功率达到90%，用户满意度达到80%。

ABSTRACT Alzheimer's disease (AD) and Alzheimer's disease-related Dementias (ADRD) currently affect more than 5.8 million Americans, costing $305 billion for treatment and management in 2020 and causing poor outcomes such as loss of independence, low quality of life, and nursing home requirements. Given the scale of diminished health-related quality of life, the need for non-invasive customizable cognitive impairment (CI) targeting methods to assist AD patients is imperative. There is a significant need for effective individualized digital interventions for AD patients accessible with social distancing in the COVID-19 pandemic situation. Claritytek proposes to develop an evidence-based, non-invasive, novel tool targeting individual aging cognitive deficits to improve AD/ADRD patients' quality of life. Virtual Reality Cognitive Therapy (VRCT) utilizes a four- pronged approach: Assess, Educate, Treat, and Track. VR is immersive, isolating the patient from surrounding distractions -- crucial for any CI intervention. Cognitive Interventions for AD should consider all facets of cognitive deficits, especially skills impacting activities of daily living (ADL) and IADL (instrumental ADL). VRCT aims to treat IADL disabilities impacting AD patients. VRCT training activities are designed to imitate real-life situations, tailored to engage, adapt, challenge, simulating lifelike CI-producing scenarios in contexts where they occur. Utilizing VRCT, repeated exposures to CI scenarios through game loops to gradually train patients in useful skills: medical appointments, taking medications, shopping, and remembering names, faces, and directions to places – to preserve and improve functional independence. Our system will include an optional mode for asynchronous online therapist consultations without face-to-face contact, valuable during COVID-19 isolations. We will expand, adapt, and build on our team’s prior successful work for Alzheimer’s patients with CI, ranked among the top 5 innovations in the world at an international digital health competition. We will partner with specialists at the HealthPartners Neuroscience Center for Alzheimer’s Research to lead the trial and help design, develop, and optimize VRCT. We will incorporate stakeholder feedback to create a patient-centric intervention targeting four specific prioritized "CI" related to IADL, utilizing guidelines of the digital therapy development frameworks. To guide the project, we will create a multidisciplinary Expert Focus Group (EFG). In Aim 1, we will evaluate the feasibility, usability, and acceptability of VRCT on 36 AD/ADRD patients with mild to moderate CI over seven weeks. We will conduct three trials, each trial with a cohort of n=12, total of n=36 participants. In addition to the patient’s responses to the therapy, a focus of the evaluation will be cognitive tolerability, as the target patients have CI. The results from each trial will be applied iteratively in Aim 2 to revise the VRCT before the next trial, producing the most acceptable CI intervention. In Aim 2, we will iteratively redesign, develop, unit test, and optimize VRCT based on patients’ feedback from the trials and EFG analysis. We expect to establish that VRCT will be feasible, usable, and acceptable with a Usability Scale success rate of 90%, and user satisfaction of 80%.