Using Mobile Phones to Reduce Missing Data in Youth Activity Monitoring Studies

描述（由申请人提供）：青春期缺乏身体活动会增加许多严重健康状况的风险。监测，流行病学和干预研究，寻求增加体力活动和/或减少青少年久坐不动的行为，可以加强通过更翔实和准确的方法来衡量这些行为。对身体活动和久坐行为的回顾性自我报告的有效性的担忧导致越来越多地使用客观测量，例如，这些工具包括加速度计和全球定位系统（GPS）记录器，可在运动或其他关键活动后使用自发的事件相关电子生态瞬时评估（EMA），辅以主观或背景信息。无论使用何种技术，器械无磨损、设备故障和受试者无应答都会导致数据缺失和模糊，使统计分析复杂化。被招募到客观PA监测研究中的青少年将越来越多地拥有所谓的“智能手机”，这是一种内置运动传感器和定位功能的微型计算机。复杂的程序（即，“应用程序”）可以很容易地安装在手机上。该项目的总体目标是为普通移动的手机开发新软件，该软件可以减少和解释在对自由生活青少年进行客观和EMA活动监测研究期间收集的缺失数据。这项技术将补充目前已经使用的客观监测器，而增加的费用很少。我们的解决方案将有三个新的组成部分：（1）使用移动终端的内置传感器来检测移动或位置类型的主要转变的电话“应用程序”，在此之后，触发及时的上下文敏感的问题和提醒，这将减少和解释缺失或不完整的活动、位置和视事件而定的EMA数据，而不管是使用内置还是外部客观监测器，（2）第二个手机“应用程序”，具有娱乐性，游戏般的感觉，并允许青少年在一天结束时使用自动检测到的主要转变的线索来解释这些缺失的数据，和（3）服务器端软件，将远程收集数据，从这两个应用程序的实时和提供研究人员的成本-减少数据缺失和改进活动过渡特征的有效方法。该系统的可行性，可接受性和性能将进行比较，目前的最先进的一项受试者内的研究与自由生活的样本40低至中等收入，种族多样化的青少年在9- 12年级。所有软件的源代码将免费提供给其他研究人员。 公共卫生相关性：该提案的目标是提供一种低成本的方法，使用普通的移动的手机来减少和解释使用客观监测器测量青少年身体活动和久坐行为的研究中收集的缺失和模糊数据。通过提高收集数据的质量，并最大限度地减少缺失数据的数量，拟议的工作将使研究人员能够更好地测量和了解身体活动，久坐行为与代谢，心血管和其他慢性疾病风险之间的关系。.

DESCRIPTION (provided by applicant): Physical inactivity during adolescence increases risk for a number of serious health conditions. Surveillance, epidemiological, and intervention studies seeking to increase physical activity and/or decrease sedentary behaviors in adolescents could be enhanced through more informative and accurate methods of measuring these behaviors. Concerns about the validity of retrospective self report of physical activity and sedentary behavior have led to increasing use of objective measures, e.g., accelerometers and Global Positioning System (GPS) loggers, which can be complemented by subjective or contextual information using self-initiated event-contingent electronic ecological momentary assessment (EMA) after exercise or other critical activities. Regardless of the technique used, device non-wear, equipment malfunction, and participant non-response result in missing and ambiguous data that complicate statistical analysis. Adolescents recruited into objective PA monitoring studies will increasingly have so-called "smart phones," which are miniature computers with built in motion sensors and location-finding capabilities. Sophisticated programs (i.e., "apps") can be easily installed on the phones. The overall objective of this project is to develop new software for common mobile phones that can both reduce and explain missing data collected during objective and EMA activity monitoring studies with free living adolescents. This technology will supplement objective monitors already used today, with minimal additional cost. Our solution will have three novel components: (1) A phone "app" that uses the mobile device's built-in sensors to detect major transitions in type of movement or location, after which timely, context-sensitive questions and reminders are triggered that will reduce and explain missing or incomplete activity, location, and event- contingent EMA data, regardless of whether built-in or external objective monitors are used, (2) A second phone "app" that has an entertaining, game-like feel and allows adolescents to interactively "fill in gaps" in their own data at the end of the day using cues from automatically-detected major transitions to explain this missing data, and (3) Server-side software that will remotely collect data from the two apps in real-time and provide researchers with a cost-efficient way to reduce missing data and improve characterization of transition in activity. The system's feasibility, acceptability, and performance will be compared to the current state of the art in a within-subjects study with a free-living sample 40 low-to-middle income, ethnically diverse adolescents in 9-12th grade. The source code for all the software will be made freely available to other researchers. PUBLIC HEALTH RELEVANCE: The goal of this proposal is to provide a low-cost way to use common mobile phones to reduce and explain missing and ambiguous data collected in studies using objective monitors to measure physical activity and sedentary behavior in adolescents. By improving the quality of data collected, and minimizing amount of missing data, the proposed work will enable researchers to better measure and understand the relationship between physical activity, sedentary behaviors, and the risk of metabolic, cardiovascular and other chronic disease. .