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Network methods to support user involvement in qualitative data analyses: An introduction to Participatory Theme Elicitation

机译:支持用户参与定性数据分析的网络方法:“参与式主题启发”简介

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摘要

Background: While Patient and Public Involvement (PPI) is encouraged throughout the research process, engagement is typically limited to intervention design and post-analysis stages. There are few approaches to participatory data analyses within complex health interventions. Methods: Using qualitative data from a feasibility RCT, this proof of concept study tests the value of a new approach to participatory data analysis called Participatory Theme Elicitation (PTE). Forty excerpts were given to eight members of a youth advisory PPI panel to sort into piles based on their perception of related thematic content. Using algorithms to detect communities in networks, excerpts were then assigned to a thematic cluster that combined the panel members' perspectives. Network analysis techniques were also used to identify key excerpts in each grouping that were then further explored qualitatively. Results: While PTE analysis was, for the most part, consistent with the researcher led analysis, young people also identified new emerging thematic content. Conclusions: PTE appears promising for encouraging user led identification of themes arising from qualitative data collected during complex interventions. Further work is required to validate and extend this method.
机译:背景:虽然在整个研究过程中都鼓励患者和公众参与(PPI),但参与通常仅限于干预设计和分析后阶段。在复杂的健康干预措施中,很少有参与性数据分析的方法。方法:使用可行性RCT中的定性数据,此概念验证研究测试了一种称为参与式主题抽取(PTE)的参与式数据分析新方法的价值。青年咨询PPI小组的八名成员摘录了40篇摘录,根据他们对相关主题内容的理解进行分类。使用算法检测网络中的社区,然后将摘录分配给一个主题小组,该小组结合了小组成员的观点。网络分析技术还被用于识别每个分组中的关键摘录,然后对其进行定性进一步研究。结果:尽管PTE分析在很大程度上与研究人员主导的分析一致,但年轻人还发现了新出现的主题内容。结论:PTE在鼓励用户主导识别由复杂干预过程中收集的定性数据引起的主题方面似乎很有希望。需要进一步的工作来验证和扩展此方法。

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