AUTHOR=Onwuegbuzie Anthony J. TITLE=On quantitizing revisited JOURNAL=Frontiers in Psychology VOLUME=15 YEAR=2025 URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2024.1421525 DOI=10.3389/fpsyg.2024.1421525 ISSN=1664-1078 ABSTRACT=

This article builds on the highly cited 2009 article authored by Professor Emerita Margarete Sandelowski and her colleagues by critically reevaluating the process of quantitizing—transforming qualitative data into quantitative forms—a technique that has surprisingly not proliferated in academic research, presumably due to a shortage of methodological exploration in this area. This article responds to this shortfall by proposing a comprehensive meta-framework using the 5W1H approach, which outlines why, when, what, where, how, and who should engage in quantitizing, thereby integrating several frameworks and models across both mixed and multiple methods research. Central to this framework is the DIME-Driven Model of Quantitizing, which categorizes quantitizing into Descriptive, Inferential, Measurement, and Exploratory types, each enhancing the utility and precision of quantitizing. This innovative model supports the article's broader advocacy for quantitizing as a crucial methodological tool across diverse research traditions. This article explores the application and value of quantitizing across qualitative, quantitative, and mixed methods research traditions, demonstrating its broad relevance and transformative potential. It discusses the variable adoption of quantitizing based on differing philosophical perspectives related to ontology, epistemology, axiology, and methodology. Despite these differences, only a few research philosophies completely reject quantitizing. The article advocates for a balanced use of quantitizing to complement qualitative analyses and to enhance research clarity and applicability without compromising the richness of qualitative data. It serves as a comprehensive resource for understanding the complexities and utility of quantitizing, aiming to inspire researchers to consider this approach to enrich their analytical tools and to enhance the depth and applicability of their research findings.