@Article{信息:doi 10.2196 / /移动医疗。4669，作者=“Modave, Fran{\c{c}}ois和Bian, Jiang和Leavitt, Trevor和Bromwell, Jennifer和Harris III, Charles和Vincent, Heather”，标题=“低质量的免费教练应用程序与美国运动医学学院指南:当前移动应用程序的回顾”，期刊=“JMIR mHealth uHealth”，年=“2015”，月=“7月”，日=“24”，卷=“3”，数=“3”，页=“e77”，关键词=“应用程序;健身;移动健康;移动训练;肥胖;质量;背景:低体力活动水平是慢性疾病、体重失调和死亡率的重要因素。将近70%的美国人超重，35%的人肥胖。据估计，肥胖每年在医疗保健方面花费1470亿美元，消耗9500万年的生命。 Although poor nutritional habits remain the major culprit, lack of physical activity significantly contributes to the obesity epidemic and related lifestyle diseases. Objective: Over the past 10 years, mobile devices have become ubiquitous, and there is an ever-increasing number of mobile apps that are being developed to facilitate physical activity, particularly for active people. However, no systematic assessment has been performed about their quality with respect to following the parameters of sound fitness principles and scientific evidence, or suitability for a variety of fitness levels. The aim of this paper is to fill this gap and assess the quality of mobile coaching apps on iOS mobile devices. Methods: A set of 30 popular mobile apps pertaining to physical activity programming was identified and reviewed on an iPhone device. These apps met the inclusion criteria and provided specific prescriptive fitness and exercise programming content. The content of these apps was compared against the current guidelines and fitness principles established by the American College of Sports Medicine (ACSM). A weighted scoring method based on the recommendations of the ACSM was developed to generate subscores for quality of programming content for aerobic (0-6 scale), resistance (0-6 scale), and flexibility (0-2 scale) components using the frequency, intensity, time, and type (FITT) principle. An overall score (0-14 scale) was generated from the subscores to represent the overall quality of a fitness coaching app. Results: Only 3 apps scored above 50{\%} on the aerobic component (mean 0.7514, SD 1.2150, maximum 4.1636), 4 scored above 50{\%} on the resistance/strength component (mean 1.4525, SD 1.2101, maximum 4.1094), and no app scored above 50{\%} on the flexibility component (mean 0.1118, SD 0.2679, maximum 0.9816). Finally, only 1 app had an overall score (64.3{\%}) above 50{\%} (mean 2.3158, SD 1.911, maximum 9.0072). Conclusions: There are over 100,000 health-related apps. When looking at popular free apps related to physical activity, we observe that very few of them are evidence based, and respect the guidelines for aerobic activity, strength/resistance training, and flexibility, set forth by the ACSM. Users should exercise caution when adopting a new app for physical activity purposes. This study also clearly identifies a gap in evidence-based apps that can be used safely and effectively to start a physical routine program, develop fitness, and lose weight. App developers have an exciting opportunity to improve mobile coaching app quality by addressing these gaps. ", issn="2291-5222", doi="10.2196/mhealth.4669", url="http://mhealth.www.mybigtv.com/2015/3/e77/", url="https://doi.org/10.2196/mhealth.4669", url="http://www.ncbi.nlm.nih.gov/pubmed/26209109" }