nominal group technique

标称成组技术
  • 文章类型: Journal Article
    在回顾性二级数据分析研究中,研究人员经常寻求机构审查委员会(IRB)的同意,并通过使用复杂的软件将风险降至最低。然而,对IRB专家对这些方法的看法知之甚少。为了使用软件促进有关风险缓解策略的有效沟通,我们与IRB专家进行了两项研究,目的是在向IRB描述软件时共同创建适当的语言.
    我们与IRB专家进行了结构化的焦点小组,以征求有关福利问题的意见,风险,和信息需求。基于这些结果,我们使用隐私增强软件为一项通用研究开发了IRB应用模板和响应模板.然后,我们进行了三轮Delphi研究,以完善模板IRB应用程序和基于专家小组反馈的模板响应。为了方便与会者的审议,我们在每一轮Delphi中分享了修订和参与者反馈的摘要。
    两个焦点小组的11位专家提出了13种关于风险的想法,好处,和信息需求。17名专家参加了Delphi研究,其中13人完成了所有回合。大多数人同意隐私增强软件将风险降至最低,但不管所有次要数据研究都有意外披露的固有风险。大多数(84.6%)指出,回顾性二级数据研究中的受试者经历的风险并不比现代数字社会中日常生活中经历的风险更大。因此,所有不与受试者接触的仅有回顾性数据的研究都是最低风险研究.
    首先,我们发现一些IRB专家在二级数据研究中如何看待风险方面存在根本性分歧.这种分歧是后果性的,因为它们会影响确定结果,并可能表明不同机构的IRB可能会得出关于类似研究方案的不同结论。第二,在我们的研究中,隐私增强软件的最高风险和收益是社会风险,而不是个人风险。排名最高的好处是促进更多的研究和促进负责任的数据治理实践。排名最高的风险是系统用户错误或错误算法导致无效结果的风险。这些社会考虑通常是公共卫生伦理的特征,而不是研究伦理的生物伦理方法,可能反映了应用生物伦理方法的困难(例如,知情同意)在二级数据研究中。最后,用于二级数据研究的隐私增强技术的发展取决于隐私专家和技术开发人员之间的有效沟通和协作。隐私是一个复杂的问题,需要一个整体的方法,最好通过设计隐私原则来解决。隐私专家的参与很重要,但在此设计过程中经常被忽略。这项研究提出了最佳实践策略,可以通过参与式设计共同开发软件的配套文档来吸引隐私社区,以促进透明度和沟通。在这个案例研究中,我们使用开源软件发布的最终模板IRB应用程序和响应可以由研究人员轻松调整,以便在使用该软件时更好地与他们的IRB进行沟通.当许多软件开发人员不是研究伦理专家时,这可以帮助增加负责任的数据治理实践。
    UNASSIGNED: In retrospective secondary data analysis studies, researchers often seek waiver of consent from institutional Review Boards (IRB) and minimize risk by utilizing complex software. Yet, little is known about the perspectives of IRB experts on these approaches. To facilitate effective communication about risk mitigation strategies using software, we conducted two studies with IRB experts to co-create appropriate language when describing a software to IRBs.
    UNASSIGNED: We conducted structured focus groups with IRB experts to solicit ideas on questions regarding benefits, risks, and informational needs. Based on these results, we developed a template IRB application and template responses for a generic study using privacy-enhancing software. We then conducted a three-round Delphi study to refine the template IRB application and the template responses based on expert panel feedback. To facilitate participants\' deliberation, we shared the revisions and a summary of participants\' feedback during each Delphi round.
    UNASSIGNED: 11 experts in two focus groups generated 13 ideas on risks, benefits, and informational needs. 17 experts participated in the Delphi study with 13 completing all rounds. Most agreed that privacy-enhancing software will minimize risk, but regardless all secondary data studies have an inherent risk of unexpected disclosures. The majority (84.6%) noted that subjects in retrospective secondary data studies experience no greater risks than the risks experienced in ordinary life in the modern digital society. Hence, all retrospective data-only studies with no contact with subjects would be minimal risk studies.
    UNASSIGNED: First, we found fundamental disagreements in how some IRB experts view risks in secondary data research. Such disagreements are consequential because they can affect determination outcomes and might suggest IRBs at different institutions might come to different conclusions regarding similar study protocols. Second, the highest ranked risks and benefits of privacy-enhancing software in our study were societal rather than individual. The highest ranked benefits were facilitating more research and promoting responsible data governance practices. The highest ranked risks were risk of invalid results from systematic user error or erroneous algorithms. These societal considerations are typically more characteristic of public health ethics as opposed to the bioethical approach of research ethics, possibly reflecting the difficulty applying a bioethical approach (eg, informed consent) in secondary data studies. Finally, the development of privacy-enhancing technology for secondary data research depends on effective communication and collaboration between the privacy experts and technology developers. Privacy is a complex issue that requires a holistic approach that is best addressed through privacy-by-design principles. Privacy expert participation is important yet often neglected in this design process. This study suggests best practice strategies for engaging the privacy community through co-developing companion documents for software through participatory design to facilitate transparency and communication. In this case study, the final template IRB application and responses we released with the open-source software can be easily adapted by researchers to better communicate with their IRB when using the software. This can help increase responsible data governance practices when many software developers are not research ethics experts.
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