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

我们为开发人造胰腺设备（AP）提出了一种以人为中心的方法 为青少年和1型糖尿病的年轻人自动化胰岛素 将根据计划的实时指标和 这些轻推将有所帮助。 患有1型糖尿病的人会适应其行为，例如饭菜，体育锻炼和胰岛素增压 到AP设备，以维持其在紧密的“ Euglycemic”范围内的血糖水平，而 避免了与我们的支撑者相关的优势。 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 对用户的生理，认知，心理社会和行为状态和支持的细微差别理解 用户在与辅助设备持续合作中管理慢性条件的生活经验。 使用有关生理状态的实时数据（血糖，心脏比率，身体活动和疾病）； 用户与设备互动的行为数据； 信任获得了精心设计的简短调查表，PCAP将建立整个人模型 跟踪心理意识，包括情境意识，认知负担，及格和压力，以便 预测未来的行为。 推动内容，重要性和自由度的参数。 调查用户界面的设计，用于删除轻推并跟踪用户响应 他们。 支撑PCAP系统的正确性，可靠性和功效。 周围的信任和隐私将经过仔细的调查，以告知PCAP的设计 多组分认知模型将结合各种领域的想法，包括人类计算机 互动，心理学，移动系统，概率建模，地狱，学习和控制， 特别着重于建立有效的牙性皮质“ nuding”以改善糖尿病自我的经验基础 在没有增加工作量的情况下，在您的情况下绘制了过度的情况 该项目的重点是1型糖尿病的装饰，建议的技术将扩展 管理可穿戴传感器和移动的其他慢性条件的管理 设备作为多组分干预措施的一部分也可以采用和维护健康 行为。 考虑到这些设备可以推断的辅助医疗设备等辅助医疗设备的审议 有关用户生活的亲密私人细节。 相关性（请参阅教学）： 总体项目目标是解决对优化连续使用的策略的关键需求 葡萄糖监测器，可以改善青少年血糖控制的设备，而年轻人则具有1型 糖尿病，但通常不用于最佳教育和行为干预策略 在这个项目中，通过试图改善整个人的糖尿病来与公共卫生有关 在努力靶向血糖控制的人群中的管理和血糖控制， 降低短期和长期的风险