Computer-Based Qualitative Content Analysis as an Instrument for Qualitative Meta-Analysis. The Case of the Local Agenda 21

Julia Schnepf, Norbert Groeben

Abstract


We explore the concept of qualitative meta-analysis as an unconventional tool of analyzing and summarizing empirical findings of previous studies. In contrast to statistical meta-analyses and the use of meta-syntheses or systematic reviews, using qualitative content analysis for meta-analytic purposes provides an adaptable method of generating meta-knowledge about relevant relationships between the concepts and variables under research. A main advantage of qualitative content analysis as an instrument for qualitative meta-analysis is that it enables researchers to include and analyze quantitative as well as qualitative research articles. This aim can be achieved by integrating the typical sequences of quantitative and qualitative content analysis. As scientific publications are expressions of explicit and communicable knowledge, qualitative meta-analysis implies that coding units are specified on the dimension of meanings prior to the generation of the coding frame. Furthermore, the method allows for combining deductive and inductive strategies in generating the coding frame, depending on the underlying research question. We explore and demonstrate how qualitative content analysis can be adapted towards conducting a qualitative meta-analysis by exploring exogenous and endogenous factors influencing the implementation and realization of local sustainability projects. Based on this analysis we show that the meta-analyzed studies do indeed allow for statistical analysis. On the methodological level, we provide a practical example of how to conduct a qualitative content analysis for the purpose of a qualitative meta-analysis.


Keywords


qualitative meta-analysis; meta-synthesis; qualitative content analysis; evaluation research; sequential steps



DOI: http://dx.doi.org/10.17169/fqs-20.3.3313

Copyright (c) 2019 Julia Schnepf, Norbert Groeben

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This work is licensed under a Creative Commons Attribution 4.0 International License.