Meta-integration for synthesizing data in a systematic mixed studies review: insights from research on autism spectrum disorder

Meta-integration for synthesizing data in a systematic mixed studies review: insights from... Systematic reviews conducted using either meta-analysis or meta-synthesis are well established methodological procedures for combining data and results across different quantitative or qualitative studies. Recently, a third option for systematic reviews has emerged. Systematic mixed studies reviews combine data and results across quantitative, qualitative and mixed method studies. An important challenge is how to integrate the quantitative, qualitative and mixed method studies. Here, we introduce the concept of “meta-integration”. Our overarching aim is to define and illustrate the novel concept of meta-integration as applied to convergent systematic mixed studies reviews using examples from our research on parental self-perception and autism spectrum disorder. Specifically, we present a typology for meta-integration procedures at two levels, both basic and advanced meta-integration. Three models, namely, basic convergent meta-integration, basic convergent qualitative meta-integration, and basic convergent quantitative meta-integration, combine quantitative and qualitative studies. Three additional models, namely, advanced convergent qualitative meta-integration, advanced convergent qualitative meta-integration, and advanced convergent quantitative meta-integration, combine quantitative, qualitative and mixed method studies. The models generally follow six steps: (1) categorize data sources; (2) transform the data; (3) conduct intra-method synthesis; (4) conduct inter-method synthesis and/or integration; (5) organize results and assess fit; and (6) draw final conclusions. One basic and one advanced model do not involve data transformation. These models for conducting convergent meta-integration in systematic mixed studies reviews provide guidance for researchers to apply rigorous and coherent methodology. Following these procedures can substantively improve the quality of systematic reviews seeking to use quantitative, qualitative and mixed method studies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Meta-integration for synthesizing data in a systematic mixed studies review: insights from research on autism spectrum disorder

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Publisher
Springer Netherlands
Copyright
Copyright © 2015 by Springer Science+Business Media Dordrecht
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-015-0261-6
Publisher site
See Article on Publisher Site

Abstract

Systematic reviews conducted using either meta-analysis or meta-synthesis are well established methodological procedures for combining data and results across different quantitative or qualitative studies. Recently, a third option for systematic reviews has emerged. Systematic mixed studies reviews combine data and results across quantitative, qualitative and mixed method studies. An important challenge is how to integrate the quantitative, qualitative and mixed method studies. Here, we introduce the concept of “meta-integration”. Our overarching aim is to define and illustrate the novel concept of meta-integration as applied to convergent systematic mixed studies reviews using examples from our research on parental self-perception and autism spectrum disorder. Specifically, we present a typology for meta-integration procedures at two levels, both basic and advanced meta-integration. Three models, namely, basic convergent meta-integration, basic convergent qualitative meta-integration, and basic convergent quantitative meta-integration, combine quantitative and qualitative studies. Three additional models, namely, advanced convergent qualitative meta-integration, advanced convergent qualitative meta-integration, and advanced convergent quantitative meta-integration, combine quantitative, qualitative and mixed method studies. The models generally follow six steps: (1) categorize data sources; (2) transform the data; (3) conduct intra-method synthesis; (4) conduct inter-method synthesis and/or integration; (5) organize results and assess fit; and (6) draw final conclusions. One basic and one advanced model do not involve data transformation. These models for conducting convergent meta-integration in systematic mixed studies reviews provide guidance for researchers to apply rigorous and coherent methodology. Following these procedures can substantively improve the quality of systematic reviews seeking to use quantitative, qualitative and mixed method studies.

Journal

Quality & QuantitySpringer Journals

Published: Aug 30, 2015

References

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