@Article{信息:doi 10.2196 / / jmir。3421，作者=“Min, Yul Ha和Lee, Jong Won和Shin, Yong-Wook和Jo, Min- woo和Sohn, Guiyun和Lee, Jae-Ho和Lee, Guna和Jung, Kyung Hae和Sung, jhon和Ko, Beom Seok和Yu, Jong- han和Kim, Hee Jeong和Son, Byung Ho和Ahn, Sei Hyun”，标题=“通过智能手机应用程序每日收集自我报告的乳腺癌化疗患者睡眠障碍数据:，期刊=“J Med Internet Res”，年=“2014”，月=“5”，日=“23”，卷=“16”，数=“5”，页=“e135”，关键词=“移动应用;自我报告;合规;背景:移动通信技术的改进使临床医生能够更频繁地收集患者报告的结果(PRO)数据，但迄今为止，关于通过智能手机应用程序(app)收集接受化疗的乳腺癌患者的PRO数据的频率，证据有限。目的:本研究的主要目的是确定一款应用程序的可行性，用于收集接受化疗的乳腺癌患者的睡眠障碍相关数据。第二个目标是确定与更好的依从性相关的变量，以确定未来基于智能手机的干预研究中纳入的最佳亚组。方法:在2013年3月至2013年7月期间，计划在峨山医疗中心接受乳腺癌新辅助化疗的患者在化疗开始前注册，并要求他们在90天的研究期间每天通过智能手机应用程序自我报告他们的睡眠模式、焦虑严重程度和情绪状态。每日上午九时及晚上七时向参加者发送推送通知。 Data regarding the patients' demographics, interval from enrollment to first self-report, baseline Beck's Depression Inventory (BDI) score, and health-related quality of life score (as assessed using the EuroQol Five Dimensional [EQ5D-3L] questionnaire) were collected to ascertain the factors associated with compliance with the self-reporting process. Results: A total of 30 participants (mean age 45 years, SD 6; range 35-65 years) were analyzed in this study. In total, 2700 daily push notifications were sent to these 30 participants over the 90-day study period via their smartphones, resulting in the collection of 1215 self-reporting sleep-disturbance data items (overall compliance rate=45.0{\%}, 1215/2700). The median value of individual patient-level reporting rates was 41.1{\%} (range 6.7-95.6{\%}). The longitudinal day-level compliance curve fell to 50.0{\%} at day 34 and reached a nadir of 13.3{\%} at day 90. The cumulative longitudinal compliance curve exhibited a steady decrease by about 50{\%} at day 70 and continued to fall to 45{\%} on day 90. Women without any form of employment exhibited the higher compliance rate. There was no association between any of the other patient characteristics (ie, demographics, and BDI and EQ5D-3L scores) and compliance. The mean individual patient-level reporting rate was higher for the subgroup with a 1-day lag time, defined as starting to self-report on the day immediately after enrollment, than for those with a lag of 2 or more days (51.6{\%}, SD 24.0 and 29.6{\%}, SD 25.3, respectively; P=.03). Conclusions: The 90-day longitudinal collection of daily self-reporting sleep-disturbance data via a smartphone app was found to be feasible. Further research should focus on how to sustain compliance with this self-reporting for a longer time and select subpopulations with higher rates of compliance for mobile health care. ", issn="1438-8871", doi="10.2196/jmir.3421", url="//www.mybigtv.com/2014/5/e135/", url="https://doi.org/10.2196/jmir.3421", url="http://www.ncbi.nlm.nih.gov/pubmed/24860070" }