How to conduct an integrative mixed methods meta-analysis: A tutorial for the systematic review of quantitative and qualitative evidence.

IF 7.6 1区 心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY Psychological methods Pub Date : 2024-10-03 DOI:10.1037/met0000675
Heidi M Levitt
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Abstract

This article is a guide on how to conduct mixed methods meta-analyses (sometimes called mixed methods systematic reviews, integrative meta-analyses, or integrative meta-syntheses), using an integrative approach. These aggregative methods allow researchers to synthesize qualitative and quantitative findings from a research literature in order to benefit from the strengths of both forms of analysis. The article articulates distinctions in how qualitative and quantitative methodologies work with variation to develop a coherent theoretical basis for their integration. In advancing this methodological approach to integrative mixed methods meta-analysis (IMMMA), I provide rationales for procedural decisions that support methodological integrity and address prior misconceptions that may explain why these methods have not been as commonly used as might be expected. Features of questions and subject matters that lead them to be amenable to this research approach are considered. The steps to conducting an IMMMA then are described, with illustrative examples, and in a manner open to the use of a range of qualitative and quantitative meta-analytic approaches. These steps include the development of research aims, the selection of primary research articles, the generation of units for analysis, and the development of themes and findings. The tutorial provides guidance on how to develop IMMMA findings that have methodological integrity and are based upon the appreciation of the distinctive approaches to modeling variation in quantitative and qualitative methodologies. The article concludes with guidance for report writing and developing principles for practice. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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如何进行综合混合方法荟萃分析:定量和定性证据的系统回顾教程。
本文介绍了如何使用整合方法进行混合方法荟萃分析(有时也称为混合方法系统综述、整合荟萃分析或整合荟萃合成)。这些综合方法允许研究人员综合研究文献中的定性和定量结果,以便从两种分析形式的优势中获益。文章阐明了定性和定量方法论如何通过变异来为其整合奠定连贯的理论基础。在推进这种综合混合方法荟萃分析(IMMMA)的方法论过程中,我为支持方法论完整性的程序性决策提供了理论依据,并解决了之前的误解,这些误解可能解释了为什么这些方法没有像预期的那样得到普遍使用。我还考虑了问题和主题的特点,这些特点使它们适合采用这种研究方法。然后,通过举例说明,以开放的方式介绍了进行 IMMMA 的步骤,并介绍了一系列定性和定量荟萃分析方法的使用。这些步骤包括制定研究目标、选择主要研究文章、生成分析单元以及制定主题和研究结果。教程就如何开发具有方法论完整性的 IMMMA 研究结果提供了指导,这些研究结果建立在对定量和定性方法中差异建模的独特方法的理解之上。文章最后对报告撰写和实践原则的制定提供了指导。(PsycInfo 数据库记录 (c) 2024 APA,保留所有权利)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Psychological methods
Psychological methods PSYCHOLOGY, MULTIDISCIPLINARY-
CiteScore
13.10
自引率
7.10%
发文量
159
期刊介绍: Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.
期刊最新文献
Simulation studies for methodological research in psychology: A standardized template for planning, preregistration, and reporting. How to conduct an integrative mixed methods meta-analysis: A tutorial for the systematic review of quantitative and qualitative evidence. Updated guidelines on selecting an intraclass correlation coefficient for interrater reliability, with applications to incomplete observational designs. Data-driven covariate selection for confounding adjustment by focusing on the stability of the effect estimator. Estimating and investigating multiple constructs multiple indicators social relations models with and without roles within the traditional structural equation modeling framework: A tutorial.
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