INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of Therapeutic Evaluation of Chronic Diseases Team (METHODS), Paris, F-75014 France; Paris Descartes University, Sorbonne Paris Cité, France; Department of Health Services Research, Institute of Population Health Sciences, University of Liverpool, Liverpool L69 3GB, UK.
INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of Therapeutic Evaluation of Chronic Diseases Team (METHODS), Paris, F-75014 France; Paris Descartes University, Sorbonne Paris Cité, France; Centre d'Epidémiologie Clinique, Hôpital Hôtel Dieu, Assistance Publique des Hôpitaux de Paris, Paris, France.
J Clin Epidemiol. 2019 Jun;110:1-11. doi: 10.1016/j.jclinepi.2019.02.007. Epub 2019 Feb 14.
New forms of research involving collective intelligence (CI) of diverse individuals mobilized through crowdsourcing is successfully emerging in various fields. This scoping review aimed to describe these methods across different fields and propose a framework for implementation.
We searched seven electronic databases for reports describing projects that had mobilized CI with crowdsourcing. We used content analysis to develop themes and categories of the methods.
We identified 145 reports. CI was mobilized to generate ideas, conduct evaluations, solve problems, and create intellectual outputs. Most projects (n = 110, 76%) were open to the public without restrictions on participants' expertise. Participants contributed to projects by independent contribution (i.e., no interaction with other participants) (n = 50, 34%), collaboration (n = 41, 28%), competitions (n = 33, 23%), and playing games (n = 16, 11%). In total, 61% of articles (n = 89) reported methods to evaluate participants' contribution and decision-making process: 43% used an independent panel of experts and 18% involved end users. We identified challenges in implementation and sustainability of CI and proposed solutions.
New research methods based on CI through crowdsourcing could transform clinical research. This framework facilitates the implementation of these methods.
通过众包动员不同个体的集体智慧（CI）的新形式的研究正在各个领域成功涌现。本范围综述旨在描述这些方法在不同领域的应用，并提出实施框架。
我们在七个电子数据库中搜索了描述通过众包动员 CI 的项目的报告。我们使用内容分析来开发方法的主题和类别。
我们确定了 145 份报告。CI 被动员起来以产生想法、进行评估、解决问题和创造智力产出。大多数项目（n=110，76%）对公众开放，对参与者的专业知识没有限制。参与者通过独立贡献（即与其他参与者没有互动）（n=50，34%）、协作（n=41，28%）、竞赛（n=33，23%）和玩游戏（n=16，11%）参与项目。总的来说，61%的文章（n=89）报告了评估参与者贡献和决策过程的方法：43%使用独立的专家小组，18%涉及最终用户。我们确定了 CI 和众包实施和可持续性的挑战，并提出了解决方案。
基于 CI 通过众包的新研究方法可以改变临床研究。该框架有助于这些方法的实施。
