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: 10602775
• 负责人: Stephen Voida
• 金额: $ 32.63万
• 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/10602775
• 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; Cells; Chronic; Clinical; Cognitive; Collaborations; Consumption; 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; Problem Solving; Psyche structure; Psychology; Public Health; Public Health Informatics; Qualitative Research; Questionnaires; Research; Risk; Role; Self Management; Self-Help Devices; Series; Statistical Models; Stress; Structure; Surveys; System; Techniques; Technology; Testing; Time; Trust; Work; Workload; aged; analog; autoimmune pathogenesis; base; blood glucose regulation; cognitive load; computer human interaction; cyber physical; decision making algorithm; design; diabetes self-management; experience; glucose monitor; glycemic control; handheld mobile device; improved; mathematical model; mental state; monitoring device; mortality risk; multi-component intervention; multidisciplinary; next generation; novel; person centered; pre-clinical; programs; psychologic; psychosocial; research study; response; sensor technology; 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

我们提出了一个以人为中心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提供自动胰岛素输注。所提出的方法 将通过“智能轻推”的方式增强现有的AP设备， 持续的活动，认知负荷和心理社会措施，如情绪和压力。这些推动将有助于 1型糖尿病患者会调整自己的行为，如饮食、体力活动和胰岛素注射 为了将他们的血糖水平维持在严格的“血糖正常”范围内， 避免与极低和极高血糖水平相关的不良事件。我们的候选人- 中心人工胰腺（PCAP）方法将增强现有的控制系统，以反映更多 对用户的生理、认知、心理和行为状态的细微理解和支持 使用者与辅助设备持续合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）; 来自用户与设备交互的行为数据;以及认知负荷、压力、注意力 通过精心设计的简短问卷获得信任，PCAP将建立全人模型 跟踪心理状态，包括情境意识、认知负荷、注意力和压力， 预测未来的行为决策算法将使用这些模型来确定 参数，包括内容，重要性和频率。我们的多学科团队还将 调查用户界面的设计，以提供这些推动和跟踪用户的反应， 他们为了评估，提出了一系列涉及青少年的可行性/临床前用户研究 的正确性，可靠性和有效性的建议PCAP系统。重要的长期问题 将仔细调查周围的信任和隐私，以告知PCAP的设计。拟议 多成分认知模型将融合包括人机交互在内的各个领域的思想 交互、心理学、移动的系统、概率建模、推理、学习和控制， 特别注重建立有效的患者“轻推”，以改善糖尿病自我的经验基础， 在不增加工作量或不引起对患者状况的过度关注的情况下进行管理。而 该项目的重点是1型糖尿病的治疗，提出的基本技术将扩大 涉及其他慢性病的管理，其中可穿戴传感器和移动的 作为多组分干预措施的一部分，设备也可以指导采用和维持健康的 行为。拟议的研究还将调查用户隐私和道德的重要方面 考虑到这些设备推断的可能性， 用户生活的私密细节 相关性（参见说明）： 项目的总体目标是满足对战略的迫切需要， 血糖监测仪，可以改善青少年和年轻成人1型糖尿病患者的血糖控制的设备 糖尿病，但往往没有使用到最佳程度。教育和行为干预策略 在这个项目是相关的公共卫生，试图改善整个人的糖尿病自我- 管理和血糖控制在努力实现目标血糖控制的人群中， 降低短期和长期风险