Using Retrospective and Real-Time Physical Activity Tracking to Predict Risk of Sunburn in Outdoor Exercisers on Strava

在 Strava 上使用回顾性实时身体活动跟踪来预测户外锻炼者晒伤的风险

• 批准号: 10057198
• 负责人: DAVID B BULLER
• 金额: $ 44.43万
• 依托单位: KLEIN BUENDEL, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-06 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10057198
• 关键词: Accelerometer; Adult; Algorithms; American; Basal Cell; Behavior Therapy; Cancer Control; Cessation of life; Colorado; Connecticut; Consent; Data; Databases; Devices; Diagnosis; Diffusion of Innovation; Electronic Mail; Exercise; Feedback; Financial Hardship; Focus Groups; Funding; Future; Goals; Health system; High Prevalence; Incidence; Individual; Intervention; Libraries; Location; Machine Learning; Malignant Neoplasms; Modeling; National Cancer Institute; Persuasive Communication; Photosensitivity; Physical activity; Population; Prevention; Principal Investigator; Protective Clothing; Published Comment; Recreation; Research; Research Personnel; Research Priority; Resort; Risk; Risk Factors; Seasons; Self Efficacy; Skin; Skin Cancer; Social Network; Software Engineering; Squamous Cell; Sun Exposure; Sunburn; Sunscreening Agents; Surgeon; Technology; Testing; The Sun; Time; UV Radiation Exposure; Ultraviolet Rays; United States; anticancer research; application programming interface; base; cancer prevention; cancer therapy; data access; data format; evidence base; experience; fitbit; forgetting; graduate student; high risk; high risk behavior; high risk population; improved; individualized prevention; innovation; interest; keratinocyte; machine learning algorithm; meetings; melanoma; melanoma biomarkers; mobile application; mobile computing; novel; open source; parallel processing; prediction algorithm; programs; prototype; randomized trial; response; safety practice; skill acquisition; skin cancer prevention; social; social cognitive theory; social media; social networking website; sun protection; sun safety; usability; web site; willingness

Skin cancer is the most common cancer in the United States. Over 5.4 million cases of keratinocyte cancers (basal and squamous cell) are diagnosed annually and incidence of melanoma has increased 3% each year for the past 30 years. In the 2014 Call to Action to Prevent Skin Cancer, the U. S. Surgeon General included strategies for coordinating messages on sun safety and physical activity, recognizing the need for sun safety among populations that engage in physical activity outdoors. Recreational UV exposure is associated with every form of skin cancer; individuals who engage in more physical activity have a higher prevalence of sunburn. Melanoma is the only cancer with which physical activity is positively correlated. Strava, a tracking app and social networking site for athletes, is one of the most popular of mobile technologies for logging physical activity and providing social feedback on activities by other Strava users. The goal of this R21 research is to test the feasibility of interfacing with the Strava website and its mobile app to develop an algorithm that a) predicts when individuals are likely to be engaged in physical activity outdoors in the sun when ultraviolet radiation is high and b) delivers sun safety advice tailored to the time, location, and personal risk (e.g., skin sun sensitivity) of the Strava users. Concept focus groups with Strava users (n=16) and non-users (n=16) will provide input on the feasibility, content, and functions in the Strava Sun (SS) intervention. The algorithm that predicts future outdoor exercise will be developed using machine learning modeling on activity data provided by Strava users (n=1000). The SS intervention will be programmed to deliver ecologically-valid sun safety advice through Strava's open-source Applications Programming Interface (API) via email and comments in the Strava interface. The sun safety advice will be tailored to location, time, season and user's personal risk, employing advice algorithms we developed for a sun safety mobile app, sunZapp, and a social media message library in our Go Sun Smart intervention for outdoor recreation resorts. SS will be tested for usability (n=30 Strava users) prior to conducting a pilot field trial to establish feasibility of SS in practice (n=226 Strava users). The project is significant and innovative. A sun protection interface for the Strava platform will provide individuals who engage in regular physical activity personalized, ecologically-valid advice to help them practice sun safety during outdoor activities. It will contain a novel machine learning algorithm that predicts future high-risk behavior, i.e., outdoor physical activity, to provide precision prevention advice. The intervention will be delivered over an established and popular technology platform with over 42 million registered users.

皮肤癌是美国最常见的癌症。超过540万例角化细胞癌