A GUIDE TO QUALITATIVE META-SYNTHESIS

A Guide to Qualitative Meta-synthesis provides accessible guidelines for conducting all phases of theory-generating meta-synthesis research, including data collection, analysis, and theory generation. It is a research methodology that is designed to generate evidence-based theory by extracting, anal...

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Bibliographic Details
Main Author: Finfgeld-Connett, Deborah (Author)
Format: Book
Language:English
Published: New York Routledge Taylor & Francis Group 2018
Subjects:
Online Access:Click Here to View Status and Holdings.
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520 # # |a A Guide to Qualitative Meta-synthesis provides accessible guidelines for conducting all phases of theory-generating meta-synthesis research, including data collection, analysis, and theory generation. It is a research methodology that is designed to generate evidence-based theory by extracting, analyzing, and synthesizing qualitative findings from across published investigations. These theories provide scaffolding that can be used by health-care providers and other professionals to make context-based decisions and implement situation-specific actions. Theory-generating meta-synthesis methods stem from the qualitative research paradigm, especially grounded theory. Systematic and rigorous methods are used to identify topically related research reports that provide qualitative findings for analysis. The subsequent analysis of the data goes beyond merely reorganizing and recategorizing research findings. Newly synthesized concepts are developed, and the dynamic relationships among them are fully articulated. The validity of the resultant theory is ensured based on theoretical, methodological, and researcher triangulation; unbiased data collection and sampling strategies; inductive-deductive data analysis and synthesis strategies; and continuous reflexivity. Meta-synthesis-generated theories are highly important in environments where the use of normalized algorithms, guidelines, and protocols are on the rise. The types of theories discussed in this book will help service providers customize standardized tools so that the most effective evidence-based, yet individualized, interventions can be implemented. 
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