Life With and Without Coding: Two Methods for Early-Stage Data Analysis in Qualitative Research Aiming at Causal Explanations

TLDR

Qualitative research seeking mechanismic explanations must integrate theory with data patterns, and coding as a stand‑alone method produces an indexed text. The study compares coding and qualitative content analysis for the initial cleaning and organization of qualitative data. Coding generates an indexed text that is further analyzed, while content analysis extracts and processes only the relevant information, separating it from the original text. Both methods yield a category‑structured information base for pattern searching and theory‑embedded explanations; content analysis is preferable when the question is theory‑driven and form/position need not be considered, whereas coding is advantageous when later analysis requires such contextual details.

Abstract

Qualitative research aimed at mechanismic explanations poses specific challenges to qualitative data analysis because it must integrate existing theory with patterns identified in the data. We explore the utilization of two methods—coding and qualitative content analysis—for the first steps in the data analysis process, namely cleaning and organizing qualitative data. Both methods produce an information base that is structured by categories and can be used in the subsequent search for patterns in the data and integration of these patterns into a systematic, theoretically embedded explanation. Used as a stand-alone method outside the grounded theory approach, coding leads to an indexed text, i.e. both the original text and the index (the system of codes describing the content of text segments) are subjected to further analysis. Qualitative content analysis extracts the relevant information, i.e. separates it from the original text, and processes only this information. We suggest that qualitative content analysis has advantages compared to coding whenever the research question is embedded in prior theory and can be answered without processing knowledge about the form of statements and their position in the text, which usually is the case in the search for mechanismic explanations. Coding outperforms qualitative content analysis in research that needs this information in later stages of the analysis, e.g. the exploration of meaning or the study of the construction of narratives.