Interpreting discordant results in mixed-method research: data triangulation, participant voices, and epistemic issues in health research.

IF 2.6 3区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
Janet Page-Reeves, Megan Rivera, Evelyn Lozano, Lidia Regino, Maria Tellez, Pachely Mendivil-Aguayo, Marina Moore, Daniel Perez Rodriguez, Andrea Kalvesmaki, Rebecca Crocker, Alejandro Aragon, Camille Vasquez, Jackie Perez, Reuben J Thomas, Elaine L Bearer, Cristina Murray-Krezan
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引用次数: 0

Abstract

In this article, we discuss unexpected methodological challenges revealed during interim analysis of data from a mixed-methods study with female Mexican immigrants. 'Tertulias' was a randomized controlled trial of an innovative peer support group model for reducing social isolation and depression among women immigrants from Mexico using a Community-Driven, Community-Engaged Research (CD-CEnR) approach. We describe discordant data obtained using different methods and how we went about triangulating and integrating analyses. In the process, we identified cultural, contextual, and methodological factors that influenced the nature and content of the data, and issues of power and epistemic justice in the broader research enterprise. Based on this experience, we offer insights for data integration to improve both scientific rigor and epistemic justice in health disparities research.

解释混合方法研究中的不一致结果:数据三角测量、参与者声音和健康研究中的认知问题。
在本文中,我们讨论了在对墨西哥女性移民的混合方法研究数据进行中期分析时发现的意想不到的方法挑战。“Tertulias”是一项采用社区驱动、社区参与研究(CD-CEnR)方法的创新同伴支持小组模型的随机对照试验,该模型旨在减少来自墨西哥的女性移民的社会孤立和抑郁。我们描述了使用不同方法获得的不一致数据,以及我们如何进行三角测量和整合分析。在此过程中,我们确定了影响数据性质和内容的文化、背景和方法因素,以及更广泛的研究企业中的权力和认识正义问题。基于这一经验,我们提出了数据整合的见解,以提高健康差异研究的科学严谨性和认识公正。
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来源期刊
International Journal of Social Research Methodology
International Journal of Social Research Methodology SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
7.90
自引率
3.00%
发文量
52
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