SCH: Striking a Balance: Trust and Privacy in Using Adolescents' Data for Diabetes Self-Management

SCH：取得平衡：使用青少年数据进行糖尿病自我管理的信任和隐私

• 批准号: 10707359
• 负责人: Stephen Voida
• 金额: $ 28.6万
• 依托单位: UNIVERSITY OF COLORADO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-20 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10707359
• 关键词: Address; Adherence; Adolescent; Adolescent and Young Adult; Adoption; Adverse event; Affect; Algorithms; Artificial Pancreas; Attention; Awareness; Behavior; Behavior Therapy; Behavioral; Behavioral Model; Blood Glucose; Bolus Infusion; Cells; Chronic; Clinical; Cognitive; Collaborations; Consumption; Continuous Glucose Monitor; Data; Development; Devices; Diabetes Mellitus; Educational Intervention; Educational workshop; Equilibrium; Ethics; Evaluation; Exhibits; Frequencies; Friction; Future; Goals; Health; Heart Rate; Hybrids; Individual; Infusion procedures; Instruction; Insulin; Insulin-Dependent Diabetes Mellitus; Intervention; Interview; Learning; Link; Longevity; Maintenance; Measures; Medical Device; Medical Technology; Modeling; Moods; Outcome; Pancreas; Participant; Patients; Persons; Physical activity; Physiological; Population; Privacy; Privatization; Psyche structure; Psychology; Public Health; Public Health Informatics; Qualitative Research; Questionnaires; Research; Risk Reduction; Role; Self Management; Self-Help Devices; Series; Statistical Models; Stress; Structure; Surveys; System; Techniques; Technology; Testing; Time; Trust; Work; Workload; aged; analog; autoimmune pathogenesis; blood glucose regulation; cognitive load; computer human interaction; correctional system; cyber physical; decision making algorithm; design; diabetes self-management; euglycemia; experience; glucose monitor; glycemic control; handheld mobile device; improved; mathematical model; mental state; mortality risk; multi-component intervention; multidisciplinary; next generation; novel; person centered; pre-clinical; programs; psychologic; psychosocial; research study; response; sensor technology; technology development; wearable sensor technology

We propose a whole person-centered approach for the development of artificial pancreas devices (AP) that automates insulin delivery for adolescents and young adults with type-1 diabetes. The proposed approach will enhance existing AP devices by means of "smart nudges" based on real-time indicators of planned and ongoing activity, cognitive load, and psychosocial measures like mood and stress. These nudges will help individuals with type 1 diabetes adapt their behaviors such as meals, physical activity and insulin bolusing to the AP device in order to maintain their blood glucose levels inside a tight "euglycemic" range while avoiding adverse events linked to extremely low and high blood glucose levels. Our proposed person- centered artificial pancreas (PCAP) approach will enhance existing control systems to reflect more nuanced understandings of users’ physiological, cognitive, psychosocial, and behavioral states and support users’ lived experiences of managing chronic conditions in continuous collaboration with assistive devices. Using real-time data on the physiological state (blood glucose, heart-rate, physical activity, and illness); behavioral data from user interactions with the device; and measures of cognitive load, stress, attention and trust obtained through carefully designed short questionnaires, PCAP will build whole person models that track mental states including situational awareness, cognitive load, attention, and stress in order to predict future behaviors. These models will be used by a decision-making algorithm to determine the parameters for a nudge, including content, importance and frequency. Our multidiscplinary team will also investigate the design of a user-interface for delivering these nudges and tracking the user response to them. A series of feasibility/preclinical user studies involving adolescents are proposed in order to evaluate the correctness, reliability, and efficacy of the proposed PCAP system. Important longer-term issues surrounding trust and privacy will be carefully investigated to inform the design of PCAP. The proposed multicomponent cognitive models will incorporate ideas from a variety of fields including human–computer interaction, psychology, mobile systems, probabilistic modeling, inference, learning and control, with a particular focus on establishing an empirical basis for effective patient "nudging" to improve diabetes self- management without increasing workload or drawing undue attention to the patient’s condition. While the focus of the project is on the treatment of type-1 diabetes, the proposed fundamental techniques will extend to the management of other chronic conditions where the integration of wearable sensors and mobile devices as part of multicomponent interventions can also guide the adoption and maintenance of healthy behaviors. The proposed research will also investigate important aspects of user privacy and ethical considerations in assistive medical devices like PCAP, given the possibility of these devices to infer intimate private details about their users’ lives. RELEVANCE (See instructions): The overall project goal is to address the critical need for strategies to optimize the use of continuous glucose monitors, devices that can improve glycemic control in adolescents and young adults with type 1 diabetes, but are often not used to optimal degree. The educational and behavioral intervention strategies in this project are relevant to public health by attempting to improve whole person diabetes self- management and glycemic control in a population who struggles to achieve target glycemic control, reducing risk of short- and long-term

我们提出了一种以人为本的方法来开发人工胰腺装置（AP）， 为患有 1 型糖尿病的青少年和年轻人实现胰岛素输送自动化。 将通过基于计划和计划的实时指标的“智能推动”来增强现有的接入点设备 持续的活动、认知负荷以及情绪和压力等心理社会指标都会有所帮助。 1 型糖尿病患者会调整自己的行为，例如进餐、体力活动和注射胰岛素 AP 设备，以便将血糖水平维持在严格的“正常血糖”范围内，同时 避免与极低和高血糖水平相关的不良事件。 以中心为中心的人工胰腺（PCAP）方法将增强现有的控制系统，以反映更多 对用户生理、认知、心理和行为状态的细致理解和支持 用户与辅助设备持续协作管理慢性病的生活经验。 使用生理状态的实时数据（血糖、心率、体力活动和疾病）； 用户与设备交互的行为数据；以及认知负荷、压力、注意力的测量 并通过精心设计的简短问卷获得信任，PCAP将构建全人模型 跟踪心理状态，包括情境意识、认知负荷、注意力和压力，以便 决策算法将使用这些模型来预测未来的行为。 我们的多学科团队还将制定推动的参数，包括内容、重要性和频率。 研究用于提供这些推动并跟踪用户响应的用户界面的设计 为了评估它们，提出了一系列涉及青少年的可行性/临床前用户研究。 所提议的 PCAP 系统的正确性、可靠性和有效性。 将仔细调查围绕信任和隐私的问题，为 PCAP 的设计提供信息。 多成分认知模型将融合来自各个领域的想法，包括人机交互 交互、心理学、移动系统、概率建模、推理、学习和控制， 特别注重为有效“推动”患者建立经验基础，以改善糖尿病患者的自我意识。 在不增加工作量或过度关注患者病情的情况下进行管理。 该项目的重点是 1 型糖尿病的治疗，拟议的基本技术将扩展 到其他慢性病的管理，其中可穿戴传感器和移动设备的集成 作为多成分干预措施一部分的设备还可以指导健康的采用和维护 拟议的研究还将调查用户隐私和道德的重要方面。 鉴于 PCAP 等辅助医疗设备有可能推断出这些设备的注意事项 有关用户生活的私密细节。 相关性（参见说明）： 总体项目目标是满足优化持续使用策略的关键需求 血糖监测仪，可以改善 1 型青少年和年轻人血糖控制的设备 糖尿病，但通常没有使用最佳的教育和行为干预策略。 在这个项目中，通过尝试改善整个人的糖尿病自我意识，与公共健康相关。 对努力实现目标血糖控制的人群进行管理和血糖控制， 降低短期和长期风险