%0期刊文章%@ 1438-8871 %I JMIR出版物%V 20%卡塔尔世界杯8强波胆分析 N 12% P e11924 %T数字健康中已注册随机临床试验的未发表率和特征:横断面分析%A Al-Durra,Mustafa %A Nolan,Robert P %A Seto,Emily %A Cafazzo,Joseph A %A Eysenbach，冈瑟全球电子健康创新中心，Techna研究所，大学卫生网，多伦多总医院，R Fraser Elliott大楼，4楼，多伦多伊丽莎白街190号，ON, M5G 2C4，加拿大，1 416 340 4800 ext 4765，aldurra_mustafa@yahoo.ca %K临床协议%K临床试验%K eHealth %K mHealth %K移动健康%K出版物%K出版物偏差%K随机对照试验%K注册%K远程健康%K远程医疗%D 2018 %7 18.12.2018 %9原始论文%J J医学互联网Res %G英文%X背景:临床试验是推进循证医学研究的关键。医学研究文献已经确定了发表偏倚在临床试验中的影响。选择性发表积极结果或不发表消极结果可能会误导后续研究，导致文献综述倾向于积极结果。数字健康试验面临着具体的挑战，包括高流失率、可用性问题和形成性研究不足。这些质疑可能导致试验结果不发表。据我们所知，迄今为止还没有研究报告过数字健康试验的未发表率。目的:主要研究目的是评估在ClinicalTrials.gov上注册的数字健康随机临床试验的未发表率。我们的第二个研究目标是确定行业资助是否有助于数字健康试验的不发表。 Methods: To identify digital health trials, a list of 47 search terms was developed through an iterative process and applied to the “Title,” “Interventions,” and “Outcome Measures” fields of registered trials with completion dates between April 1, 2010, and April 1, 2013. The search was based on the full dataset exported from the ClinlicalTrials.gov database, with 265,657 trials entries downloaded on February 10, 2018, to allow publication of studies within 5 years of trial completion. We identified publications related to the results of the trials through a comprehensive approach that included an automated and manual publication-identification process. Results: In total, 6717 articles matched the a priori search terms, of which 803 trials matched our latest completion date criteria. After screening, 556 trials were included in this study. We found that 150 (27%) of all included trials remained unpublished 5 years after their completion date. In bivariate analyses, we observed statistically significant differences in trial characteristics between published and unpublished trials in terms of the intervention target condition, country, trial size, trial phases, recruitment, and prospective trial registration. In multivariate analyses, differences in trial characteristics between published and unpublished trials remained statistically significant for the intervention target condition, country, trial size, trial phases, and recruitment; the odds of publication for non-US–based trials were significant, and these trials were 3.3 (95% CI 1.845-5.964) times more likely to be published than US–based trials. We observed a trend of 1.5 times higher nonpublication rates for industry-funded trials. However, the trend was not statistically significant. Conclusions: In the domain of digital health, 27% of registered clinical trials results are unpublished, which is lower than nonpublication rates in other fields. There are substantial differences in nonpublication rates between trials funded by industry and nonindustry sponsors. Further research is required to define the determinants and reasons for nonpublication and, more importantly, to articulate the impact and risk of publication bias in the field of digital health trials. %M 30485832 %R 10.2196/11924 %U //www.mybigtv.com/2018/12/e11924/ %U https://doi.org/10.2196/11924 %U http://www.ncbi.nlm.nih.gov/pubmed/30485832