众包是“获取参与者的做法,服务,想法,或通过征求一大群人的贡献来获得内容,尤其是通过互联网。\“(Ranard等人。J.Gen.实习生。Med.29:187,2014)尽管在医疗保健研究中已采用了众包,并且最近已认识到其在分析大型数据集和获得快速反馈方面的潜力,尚未对癌症研究中的众包进行系统评价。因此,我们试图确定众包在癌症研究中的应用并探索其潜在用途.我们对2005年1月至2016年6月发表的关于癌症研究众包的文章进行了系统回顾,使用PubMed,CINAHL,Scopus,心理信息,和Embase。总结了来自12篇已确定文章的数据,但未进行统计组合。这些研究针对一系列癌症(例如,乳房,皮肤,妇科,结直肠,前列腺)。11项研究使用基于网络的平台在互联网上收集数据;一项研究使用纸笔数据收集在购物中心招募了参与者。四项研究使用AmazonMechanicalTurk进行招聘和/或数据收集。研究目标包括分类活检图像(n=6),评估癌症知识(n=3),完善决策支持系统(n=1),标准化生存护理计划(n=1),并设计临床试验(n=1)。尽管一项研究表明“人群的智慧”(NCI预算概况,2017)不能取代训练有素的专家,五项研究表明,分布式人类智能可以近似或支持训练有素的专家的工作。尽管有局限性,众包有可能提高研究的质量和速度,同时降低成本。纵向研究应该证实和完善这些发现。
Crowdsourcing is \"the practice of obtaining participants, services, ideas, or content by soliciting contributions from a large group of people, especially via the Internet.\" (Ranard et al. J. Gen. Intern. Med. 29:187, 2014) Although crowdsourcing has been adopted in healthcare research and its potential for analyzing large datasets and obtaining rapid feedback has recently been recognized, no systematic reviews of crowdsourcing in cancer research have been conducted. Therefore, we sought to identify applications of and explore potential uses for crowdsourcing in cancer research. We conducted a systematic
review of articles published between January 2005 and June 2016 on crowdsourcing in cancer research, using PubMed, CINAHL, Scopus, PsychINFO, and Embase. Data from the 12 identified articles were summarized but not combined statistically. The studies addressed a range of cancers (e.g., breast, skin, gynecologic, colorectal, prostate). Eleven studies collected data on the Internet using web-based platforms; one recruited participants in a shopping mall using paper-and-pen data collection. Four studies used Amazon Mechanical Turk for recruiting and/or data collection. Study objectives comprised categorizing biopsy images (n = 6), assessing cancer knowledge (n = 3), refining a decision support system (n = 1), standardizing survivorship care-planning (n = 1), and designing a clinical trial (n = 1). Although one study demonstrated that \"the wisdom of the crowd\" (NCI Budget Fact Book, 2017) could not replace trained experts, five studies suggest that distributed human intelligence could approximate or support the work of trained experts. Despite limitations, crowdsourcing has the potential to improve the quality and speed of research while reducing costs. Longitudinal studies should confirm and refine these findings.