Validation of Meta-Synthesis Research with Emphasis on the ConQual Validation Method

Extended Abstract
 
Introduction and Objectives: In recent years, qualitative research has witnessed remarkable growth and increasing recognition among researchers across various disciplines, particularly within the humanities and social sciences. Alongside this growing interest, significant critiques and concerns have also emerged regarding the procedures, reliability, and credibility of qualitative methods. While validity and reliability have long held central importance in quantitative research, they are equally critical—albeit more challenging—to establish in qualitative inquiry.
Given that qualitative research typically provides deeper, more meaningful insights than quantitative approaches, it inherently possesses greater potential to gain the trust of its audience. This makes the evaluation of qualitative research validity all the more essential. The present study aims to design a systematic and process-oriented model for evaluating the validity and reliability of qualitative research—referred to as the ConQual (Confidence in Qualitative Research) method.
ConQual operates through a clear, structured framework beginning with a series of guiding questions used to assess the rigor of a qualitative study. The more precisely and comprehensively a study answers these questions, the higher its validity and reliability are considered to be. To demonstrate the practical implementation of this approach, the ConQual process was applied step-by-step to one form of meta-synthesis—meta-ethnography—thus allowing readers to better understand the operational logic of the ConQual method.
Methodology: This study is grounded in the interpretivist paradigm, which views social phenomena as contextually situated and meaningful. Within this paradigm, the researcher seeks to understand and interpret meaningful social actions rather than to explain them through causal generalizations.
The logic of this research is inductive, as it aims to infer a framework, pattern, or conceptual model from existing data. It follows a fundamental research orientation, seeking to generate a new evaluative model rather than to apply an existing one. The research is qualitative in nature, focusing on the understanding and interpretation of phenomena and their associated meanings.
It employs a library-based approach, utilizing documented and credible sources—books, articles, and research reports. The purpose of this study is explanatory, aiming to identify and clarify the interrelations among the components of qualitative validation. Accordingly, its main strategy is documentary analysis, meaning that research data are derived from written and archival materials. The researchers prioritized consulting primary and recent sources to accurately delineate and operationalize the ConQual process, which was then demonstrated through its application in meta-ethnographic research.
Results: ConQual provides a systematic framework for examining the factors that enhance or diminish the credibility of qualitative findings. Among the four key criteria commonly used to assess trustworthiness in qualitative research—dependability, transferability, credibility, and confirmability—this study focuses primarily on dependability and credibility.
The evaluation process begins with a pre-ranking stage, classifying qualitative studies into four levels of rigor: strong, moderate, weak, and very weak. Studies demonstrating coherent design and methodological transparency are ranked higher, whereas those presenting only ideas or narratives without methodological grounding are placed in lower categories.
After this preliminary classification, each study is assessed for dependability and credibility. Dependability is determined through a checklist of guiding questions examining the logical coherence between research objectives, processes, and results. Credibility, in the ConQual method, is evaluated by identifying the proportion of qualitative findings that fall within three interpretive levels: explicit, ambiguous, and unsupported.
This process allows for an objective, stepwise appraisal of qualitative research trustworthiness, thereby introducing a replicable method for evaluating qualitative evidence.
Discussion and Conclusion: The findings of this study underscore several key insights. First, there is a fundamental distinction between quantitative and qualitative research paradigms. Quantitative studies can often be evaluated using standardized techniques and computational methods with minimal researcher involvement. In contrast, qualitative research inherently relies on the deep engagement of the researcher with the phenomenon under study—its strength derives precisely from this involvement.
Thus, qualitative inquiry should not be assessed merely through observable structures, metrics, or positivist criteria. The study highlights that the selection of appropriate validation tools in qualitative research—based on the nature of the data and research questions—can significantly enhance both the rigor and comprehensibility of findings, facilitating more effective implementation in practice.
In quantitative research, validity and reliability are well-defined strengths; however, in qualitative research, they have often been perceived as areas of ambiguity and weakness. The present study seeks to address this gap by introducing a clear and structured validation process—ConQual—which offers a coherent approach for assessing and enhancing the credibility of qualitative studies.
By systematizing the evaluation of qualitative findings, the ConQual method contributes to strengthening methodological transparency, fostering trust in qualitative research outcomes, and promoting a more balanced integration of qualitative approaches within the broader scientific community.