Background: Epistemic Network Analysis (ENA) is a unified, quantitative - qualitative method aiming to draw from both methodological worlds by leveraging a data set containing raw and quantified qualitative data, as well as metadata about data providers or the data itself. ENA generates network models depicting the relative frequencies of co-occurrences for each unique pair of codes in designated segments of qualitative data.Methods: This step-by-step tutorial demonstrates how to model qualitative data with ENA through its quantification via coding and segmentation. Data was curated with the Reproducible Open Coding Kit (ROCK), a human- and machine-readable standard for representing coded qualitative data, enabling researchers to document their workflow, as well as organize their data in a format that is agnostic to software of any kind.Results: ENA allows researchers to obtain insights otherwise unavailable by depicting relative code frequencies and cooccurrence patterns, facilitating a comparison of those patterns between groups and individual data providers.Conclusions: ENA aids reflexivity, moves beyond code frequencies to depict their interactions, allows researchers to easily create posthoc groupings of data providers for various comparisons, and enables conveying complex results in a visualization that caters to both qualitative and quantitative sensibilities.
|Number of pages||22|
|Journal||Health Psychology and Behavioral Medicine|
|Publication status||Published - 31 Dec 2023|
- Epistemic Network Analysis (ENA)
- Reproducible Open Coding Kit (ROCK)
- data visualization