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

基本信息

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
项目类别：
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

项目摘要

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 万例角质形成细胞癌病例（基底细胞和鳞状细胞）每年都会被诊断出来，黑色素瘤的发病率每年增加 3% 过去30年。在 2014 年预防皮肤癌的行动呼吁中，美国外科医生包括协调有关阳光安全和身体活动的信息的策略，认识到阳光安全的必要性从事户外体育活动的人群。休闲紫外线暴露与每个人都有关系皮肤癌的形式；从事更多体力活动的人晒伤的发生率更高。黑色素瘤是唯一与体力活动呈正相关的癌症。 Strava，一款追踪应用程序和运动员社交网站是最流行的记录体能的移动技术之一活动并提供有关其他 Strava 用户活动的社交反馈。 R21 研究的目标是测试与 Strava 网站及其移动应用程序交互来开发算法的可行性：a) 预测当个人可能在阳光下进行户外体力活动时，当紫外线辐射高和 b) 提供根据时间、地点和个人风险（例如皮肤阳光敏感性）量身定制的防晒安全建议 Strava 用户的数量。 Strava 用户 (n=16) 和非用户 (n=16) 的概念焦点小组将提供以下方面的意见： Strava Sun (SS) 干预的可行性、内容和功能。预测未来的算法将使用 Strava 用户提供的活动数据的机器学习模型来开发户外锻炼（n=1000）。 SS 干预措施将通过以下方式提供生态有效的阳光安全建议： Strava 的开源应用程序编程接口 (API) 通过电子邮件和 Strava 中的评论界面。阳光安全建议将根据地点、时间、季节和用户的个人风险量身定制，采用我们为太阳安全移动应用程序 sunZapp 和社交媒体消息库开发了建议算法我们针对户外休闲度假村的 Go Sun 智能干预措施。 SS 将进行可用性测试（n=30 Strava 用户），然后进行试点现场试验，以确定 SS 在实践中的可行性（n = 226 个 Strava 用户）。这项目意义重大、创新。 Strava 平台的防晒界面将为个人提供定期参加体育活动的人个性化、生态有效的建议，帮助他们实践防晒安全户外活动时。它将包含一种新颖的机器学习算法，可以预测未来的高风险行为，即户外体育活动，提供精准的预防建议。干预措施将是通过拥有超过 4200 万注册用户的成熟且流行的技术平台进行交付。