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Intensive Triangulation of Qualitative Research and Quantitative Data to Improve Recruitment to Randomized Trials: The QuinteT Approach

机译:定性研究和定量数据的密集三角测量,改善招聘对随机试验:五餐方法

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Randomized controlled trials (RCTs) can provide high quality evidence about the comparative effectiveness of health care interventions, but many RCTs struggle with or fail to complete recruitment. RCTs are built on the principles of the experimental method, but their planning, conduct, and interpretation can depend on complex social, behavioral, and cultural factors that may be best understood through qualitative research. Most qualitative studies undertaken alongside RCTs involve interviews that produce data that are used in a supportive or supplicatory role, but there is potential for qualitative research to be more influential. In this article, we describe the research methods underpinning the “QuinteT” (Qualitative Research Integrated Within Trials) approach to understand and address RCT recruitment difficulties. The QuinteT Recruitment Intervention (QRI) brings together multiple qualitative strategies and quantitative data and uses triangulation to understand recruitment issues rapidly. These nuanced understandings are used to inform the implementation of collaborative actions to improve recruitment.
机译:随机对照试验(RCT)可以为医疗干预措施的比较有效性提供高质量的证据,但许多RCT与或未能完全招聘。 RCT是基于实验方法的原则,但他们的规划,行为和解释可以取决于通过定性研究可以最好地理解的复杂的社会,行为和文化因素。与RCT一起进行的大多数定性研究涉及采访,这些研究会产生用于支持性或可感知作用的数据,但有可能进行定性研究的可能性。在本文中,我们描述了基于“Quintet”(综合试验中的定性研究)方法的研究方法,了解和解决RCT招聘困难的方法。 Quintet招聘干预(QRI)汇集了多种定性策略和定量数据,并使用三角测量快速了解招聘问题。这些细微的理解用于告知实施协作行动以改善招聘。

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