权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Mentoring and research in applying digital technologies to prevent chronic Illnesses

应用数字技术预防慢性病的指导和研究

基本信息

批准号：
9297123
负责人：
YOSHIMI FUKUOKA
金额：
$ 18.61万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-01 至 2020-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9297123
关键词：
Accelerometer Address Adherence Adult Algorithms Area Award Back Behavior Behavioral California Car Phone Cardiovascular Diseases Cardiovascular system Cellular Phone Chronic Disease Clip Complex Data Data Analyses Data Collection Development Diabetes Mellitus Diabetes prevention Discipline Electronic Mail Emerging Technologies Environment Epidemic Evaluation Failure Feedback Frequencies Funding Future Goals Guidelines Individual International Intervention Intervention Trial Leadership Link Machine Learning Measures Mentors Mentorship Methods Mid-Career Clinical Scientist Award (K24)Midcareer Investigator Award in Patient-Oriented Research Modeling Monitor Non-Insulin-Dependent Diabetes Mellitus Obesity Participant Patient Self-Report Physical activity Primary Prevention Principal Investigator Randomized Controlled Clinical Trials Recommendation Research Research Design Research Personnel Role Running Sample Size San Francisco School Nursing Secure Specific qualifier value Technology Testing Text Thinness Time To specify Training Treatment Failure Treatment Protocols United States United States National Institutes of Health Universities Visit Wireless Technology base career cost cost effective design diaries digital improved individualized medicine innovation lifestyle intervention mobile application mobile computing patient oriented research physical model prediction algorithm prevent programs public health relevance skills social media tool training opportunity

项目摘要

DESCRIPTION (provided by applicant): For this K24 midcareer investigator award in patient-oriented research (POR) award, my goals are: 1) to become an international leader in the primary prevention of type 2 diabetes and cardiovascular diseases by applying emerging digital technologies and social media; 2) to conduct high-impact research in testing innovative, cost-effective lifestyle interventions (physical activity) using machine leaning; and 3) to provide a hih quality mentorship and training environment that supports the conduct of high POR impact research in cardiovascular and diabetes prevention. This K24 award will allow me to take on a broader and more formal mentorship role not only in the School of Nursing but also throughout the University of California, San Francisco campus. The overall goals of the new research in this application are to develop decision rule algorithms and quantitative models to optimize real-time predictions of future physical activity intervention adherences and to pilot test these algorithms and models in an intervention trial. The specific aims are: 1) to determine the extent to which baseline factors can predict adherence in self-monitoring (using mobile apps and wearing advanced accelerometers); 2) to determine the extent to which early app-based self-monitoring and evaluation (e.g., advanced accelerometers and diary use, and step counts in the first few weeks) can be optimized to make real-time predictions of future treatment failures; 3) to assess the feasibility of the "Physical Activity Plus" intervention using developed real-time prediction models (developed in Aim 2), compared to a "regular physical activity" intervention, for changes in total daily steps and duration of moderate and intensive physical activity over a three-month period. To tailor intervention intensity, we will evaluate the frequency of study visits and real-time feedback to minimize treatment failures and maximize adherence. Junior investigators in the POR have adapted digital mobile technologies as part of their research tools and have generated large volumes of continuous data. However, only a few training opportunities are available in this research area; in particular, for methods to rigorously and fully utilize the richness of the data collected. Therefore, the proposed K24 application will also meet these mentees' urgent needs across disciplines.