Using moment-to-moment sensors, mobile technology, and stimulated cytokine responses to identify physical and mental health risk among Alzheimer's spousal caregivers

使用即时传感器、移动技术和刺激的细胞因子反应来识别阿尔茨海默氏症配偶照顾者的身心健康风险

• 批准号: 10305478
• 负责人: Akane Sano
• 金额: $ 14.44万
• 依托单位: RICE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-05 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10305478
• 关键词: Address; Adult; Aging; Alzheimer' s Disease; Alzheimer' s disease patient; Alzheimer' s disease related dementia; Award; Bayesian Analysis; Bayesian Modeling; Behavior; Behavioral; Biological; Biological Markers; Blood specimen; Car Phone; Cardiovascular Diseases; Caregiver Burden; Caregivers; Cellular Phone; Chronic; Circadian Rhythms; Coupling; Data; Data Analyses; Data Science; Dementia; Dementia caregivers; Development; Disease; Elderly; Engineering; Evidence based intervention; Galvanic Skin Response; Health; Health Technology; Heart Rate; Human; In Situ; Individual; Inflammation; Inflammatory; Intervention; Interview; Knowledge; Learning; Longitudinal Studies; Malignant Neoplasms; Measurement; Measures; Mental Health; Mentors; Mentorship; Methods; Monitor; Moods; Non-Insulin-Dependent Diabetes Mellitus; Osteoporosis; Outcome; Parents; Participant; Patient Self-Report; Patients; Phenotype; Physical activity; Physiological; Physiology; Population; Premature aging syndrome; Process; Production; Psychoneuroimmunology; Public Health; Quality of life; Questionnaires; Research; Research Design; Research Personnel; Research Training; Rheumatoid Arthritis; Risk; Risk Factors; Role; Science; Scientist; Sleep; Spouse Caregiver; Spouses; Stress; Stress and Coping; Structure; Symptoms; System; Testing; Time; Training; Visit; adaptive intervention; age related; base; behavioral response; biobehavior; care giving burden; career; caregiving; clinically significant; cost; cytokine; design; digital; digital mental health; disorder risk; eHealth; experience; handheld mobile device; health data; high risk; inflammatory marker; innovation; longitudinal design; mHealth; mobile computing; mortality; multilevel analysis; novel; physical conditioning; physiologic model; preference; prevent; protective factors; psychologic; research study; resilience; response; sensor; sensor technology; skills; stress reduction; technology development; therapy design; tool; wearable device; wearable sensor technology

ABSTRACT The proposed three-year K25 will launch Dr. Akane Sano’s independent research career in the field of aging and physical and mental health where she will endeavor to identify physical and mental health disease risks; understand the role of physiological and behavioral factors in physical and mental health outcomes; and leverage her engineering background to develop personalized health measurement and interventions using biobehavioral sensors and mobile technologies. In particular, Dr. Sano will address a gap in Alzheimer’s Disease (AD) research by studying how mobile sensors and technologies may help identify spousal caregivers’ health risk and reduce their stress while promoting resilience. Spousal caregivers of AD patients are a burgeoning population impacted by the stress of caretaking so much so that they are susceptible to devastating diseases, especially those related to inflammatory cytokines. Dr. Sano will attend to this public health concern via the following aims: Aim 1. Determine the relationships between caregivers’ daily moment-to-moment behaviors and physiological responses from mobile phones and wearable sensors, self-reported psychological and physiological health, and cytokine responses. Aim 2. Identify preferences, strategies, and barriers to design digital phenotyping tools and personalized mobile and/or wearable health interventions. Dr. Sano is an expert in quantitative analysis and modeling of physiological and behavioral mobile and wearable sensor data for mental health; however, she requires training to be an independent PI in biobehavioral, aging, and mobile health research to provide novel information about the mechanisms and predictors that underlie physical and mental health risks; yet, she must also procure interdisciplinary mentorship crucially in (1) understanding biobehavioral mechanisms that underlie physical and health and disease in older adulthood, including psychoneuroimmunology (PNI), (2) understanding aging and dementia, and acquiring expertise required for developing digital phenotyping and interventions for older adult dementia spousal caregivers, and (3) advanced longitudinal and Bayesian statistical/modelling methods. Coupling mentorship and her expertise, Dr. Sano proposes a study that will identify physiological and behavioral responses and content for interventions. During the award period, Dr. Sano will 1) collect data for one month via a study of 110 spousal caregivers using wearable sensors and smartphones to measure physical activity/sleep, heart rate, skin conductance, and self-reported mood and stress; 2) sample blood at baseline and post 6-month visits; and 3) conduct a qualitative interview about caregivers’ experience, needs, and stress coping strategies for a subset of the participants after the 6-month visits. Drawing on Dr. Sano’s expertise in human sensing, data analysis, and application development for health while leveraging the mentorship of a team at the forefront of aging and biobehavioral science, the proposed research and training will equip Dr. Sano with extensive knowledge of biobehavioral mechanisms in stress, physical and mental health in older adulthood, aging and dementia, and the skills to devote her career to studying biobehavioral health risks and contributing factors while developing real-time intervention strategies using mobile technologies in older adulthood and caregiving.

摘要 拟议的为期三年的K25将启动Akane Sano博士在老龄化和物理领域的独立研究生涯 和心理健康，她将努力识别身体和心理健康疾病的风险；了解 生理和行为因素对身体和精神健康的影响；并利用她的工程背景 使用生物行为传感器和移动技术开发个性化的健康测量和干预措施。在……里面 特别是，佐野博士将通过研究移动传感器和 技术可能有助于识别配偶照顾者的健康风险，并在提高韧性的同时减轻他们的压力。配偶 AD患者的照顾者是一个新兴的人群，他们受到照顾压力的影响如此之大，以至于他们 易患破坏性疾病的，尤其是与炎性细胞因子有关的疾病。佐野博士将为这位公众服务 通过以下目标关注健康： 目标1.确定照顾者日常时刻行为和生理反应之间的关系 从手机和可穿戴传感器，自我报告心理和生理健康，以及细胞因子反应。 目标2.确定偏好、策略和障碍，以设计数字表型工具和个性化移动和/或 可穿戴式健康干预。 佐野博士是生理和行为移动和可穿戴传感器的定量分析和建模专家。 心理健康数据；然而，她需要接受培训，成为生物行为、衰老和移动健康方面的独立PI 研究提供有关身体和精神健康风险背后的机制和预测因素的新信息； 然而，她还必须获得跨学科的指导，这一点至关重要：(1)理解 老年生理、健康和疾病的基础，包括心理神经免疫学，(2)理解 老龄化和痴呆症，以及获得为老年人开发数字表型和干预所需的专业知识 痴呆症配偶照料者，以及(3)先进的纵向和贝叶斯统计/建模方法。偶联 导师和她的专业知识，佐野博士建议进行一项研究，以确定生理和行为反应，并 干预内容。在获奖期间，佐野博士将通过对110名配偶的研究收集一个月的数据 护理者使用可穿戴传感器和智能手机来测量身体活动/睡眠、心率、皮肤传导性以及 自我报告的情绪和压力；2)基线和6个月访问后的血液样本；3)进行定性访谈 在为期6个月的访问后，为一部分参与者了解照顾者的经验、需求和压力应对策略。 利用佐野博士在人类感知、数据分析和健康应用程序开发方面的专业知识，同时利用 指导一个处于老龄化和生物行为科学前沿的团队，拟议的研究和培训将配备 佐野博士对老年压力、身心健康的生物行为机制有广泛的了解， 衰老和痴呆症，以及致力于研究生物行为健康风险和促成因素的技能，同时 利用移动技术在老年人和照顾者中开发实时干预策略。