@Article{信息:doi 10.2196 / / jmir。2253，作者=“Namba, Hideyuki and Yamaguchi, Yukio and Yamada, Yosuke and Tokushima, Satoru and Hatamoto, Yoichi and Sagayama, Hiroyuki and Kimura, Misaka and Higaki, Yasuki and Tanaka, Hiroaki”，标题=“基于web的体育活动测量系统使用双标签水的验证”，期刊=“J Med Internet Res”，年=“2012”，月=“Sep”，日=“25”，卷=“14”，数=“5”，页=“e123”，关键词=“体育活动;能量消耗;双标水;背景:在线或基于web的测量系统已被提出作为收集体育活动数据的方便方法。我们开发了两个基于Web的体育活动系统——24小时体育活动记录Web (24hPAR Web)和7天回忆Web (7daysRecall Web)。目的:检验两种基于网络的双标记水(DLW)体力活动测量系统的有效性。方法:我们评估了20名年龄在25至61岁的个体的24hPAR WEB和7daysRecall WEB的有效性。电子邮件分发的顺序和随后完成的两个基于web的测量系统是随机的。每种测量工具都使用了一周。 The participants' activity energy expenditure (AEE) and total energy expenditure (TEE) were assessed over each week using the DLW method and compared with the respective energy expenditures estimated using the Web-based systems. Results: The mean AEE was 3.90 (SD 1.43) MJ estimated using the 24hPAR WEB and 3.67 (SD 1.48) MJ measured by the DLW method. The Pearson correlation for AEE between the two methods was r = .679 (P < .001). The Bland-Altman 95{\%} limits of agreement ranged from --2.10 to 2.57 MJ between the two methods. The Pearson correlation for TEE between the two methods was r = .874 (P < .001). The mean AEE was 4.29 (SD 1.94) MJ using the 7daysRecall WEB and 3.80 (SD 1.36) MJ by the DLW method. The Pearson correlation for AEE between the two methods was r = .144 (P = .54). The Bland-Altman 95{\%} limits of agreement ranged from --3.83 to 4.81 MJ between the two methods. The Pearson correlation for TEE between the two methods was r = .590 (P = .006). The average input times using terminal devices were 8 minutes and 10 seconds for the 24hPAR WEB and 6 minutes and 38 seconds for the 7daysRecall WEB. Conclusions: Both Web-based systems were found to be effective methods for collecting physical activity data and are appropriate for use in epidemiological studies. Because the measurement accuracy of the 24hPAR WEB was moderate to high, it could be suitable for evaluating the effect of interventions on individuals as well as for examining physical activity behavior. ", issn="1438-8871", doi="10.2196/jmir.2253", url="//www.mybigtv.com/2012/5/e123/", url="https://doi.org/10.2196/jmir.2253", url="http://www.ncbi.nlm.nih.gov/pubmed/23010345" }