How to construct a theoretical framework through qualitative data analysis?

Constructing a theoretical framework through qualitative data analysis involves inductively developing an explanatory structure grounded in the data itself. This process is entirely feasible when employing established qualitative methodologies focused on theory building. This approach requires systematic data collection (e.g., interviews, observations) and rigorous analytical techniques. Central principles include constant comparative analysis, iterative coding (open, axial, selective), and theoretical sampling to refine emerging concepts. Maintaining reflexivity throughout the research process is crucial to minimize bias. The goal is to achieve theoretical saturation, where new data ceases to provide additional insights into the core categories and their relationships. This method is particularly suited for exploratory research aiming to explain complex phenomena lacking pre-existing comprehensive theories. Implementation begins with meticulous immersion in the data, leading to initial coding to identify core concepts and their properties. Subsequent axial coding explores relationships between these concepts, forming tentative categories. Selective coding integrates these categories into a coherent storyline, ultimately developing the core category that explains the central phenomenon. The resulting framework provides novel explanatory power, advances understanding within the field, and can guide future quantitative testing or practical interventions. Its primary value lies in generating contextually rich, empirically grounded theory.