我们准备好共享定性研究数据了吗?定性研究人员、IRB 成员和数据存储库管理员的知识和准备情况。

IASSIST quarterly Pub Date : 2020-01-08 DOI:10.29173/iq952
Jessica Mozersky, Heidi Walsh, Meredith Parsons, Tristan McIntosh, Kari Baldwin, James M DuBois
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引用次数: 0

摘要

数据共享能最大限度地发挥数据的价值,而收集数据需要大量的时间和资源。美国的主要资助机构,如国立卫生研究院(NIH),都要求共享数据,研究人员也经常共享去标识化的定量数据。相比之下,美国很少共享定性数据,但数据共享和开放科学的趋势日益明显,这表明未来可能需要共享定性数据。定性方法通常用于探讨敏感的健康话题,这就提出了独特的伦理挑战,即既要保护保密性,又要为二次分析保留足够的背景细节。在此,我们报告了对 30 名数据存储库管理员、30 名定性研究人员和 30 名 IRB 工作人员进行半结构式深入访谈的结果,以探讨他们在 QDS 方面的经验和知识。我们的研究结果表明,所有利益相关者群体都缺乏对 QDS 的准备。研究人员最缺乏相关知识,他们往往不熟悉在资料库中共享定性数据的概念。策展人非常支持 QDS,但并非所有策展人都有策展定性数据集的经验,他们表示希望得到专门针对 QDS 的指导和标准。IRB 成员对 QDS 不熟悉,但他们支持 QDS,只要遵循适当的法律和监管程序即可。IRB 成员和数据管理员没有准备好向研究人员提供有关法律和监管事项的建议,这可能会使知识最少的研究人员得不到指导。合乎伦理且富有成效的 QDS 需要所有利益相关群体克服障碍、制定标准并改变长期以来的做法。
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Are we ready to share qualitative research data? Knowledge and preparedness among qualitative researchers, IRB Members, and data repository curators.

Data sharing maximizes the value of data, which is time and resource intensive to collect. Major funding bodies in the United States (US), like the National Institutes of Health (NIH), require data sharing and researchers frequently share de-identified quantitative data. In contrast, qualitative data are rarely shared in the US but the increasing trend towards data sharing and open science suggest this may be required in future. Qualitative methods are often used to explore sensitive health topics raising unique ethical challenges regarding protecting confidentiality while maintaining enough contextual detail for secondary analyses. Here, we report findings from semi-structured in-depth interviews with 30 data repository curators, 30 qualitative researchers, and 30 IRB staff members to explore their experience and knowledge of QDS. Our findings indicate that all stakeholder groups lack preparedness for QDS. Researchers are the least knowledgeable and are often unfamiliar with the concept of sharing qualitative data in a repository. Curators are highly supportive of QDS, but not all have experienced curating qualitative data sets and indicated they would like guidance and standards specific to QDS. IRB members lack familiarity with QDS although they support it as long as proper legal and regulatory procedures are followed. IRB members and data curators are not prepared to advise researchers on legal and regulatory matters, potentially leaving researchers who have the least knowledge with no guidance. Ethical and productive QDS will require overcoming barriers, creating standards, and changing long held practices among all stakeholder groups.

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