PAD: a graphical and numerical enhancement of structural coding to facilitate thematic analysis of a literature corpus
This provides a tool for researchers in qualitative analysis to better handle causality in structural coding, though it is incremental as it builds on existing coding practices.
The authors tackled the challenge of enhancing structural coding for thematic analysis by integrating causal relationships, graph theory, and statistics, resulting in a method that represents categories as nodes and causality as links in a directed acyclic graph to enable frequency analysis.
We suggest an enhancement to structural coding through the use of (a) causally bound codes, (b) basic constructs of graph theory and (c) statistics. As is the norm with structural coding, the codes are collected into categories. The categories are represented by nodes (graph theory). The causality is illustrated through links (graph theory) between the nodes and the entire set of linked nodes is collected into a single directed acyclic graph. The number of occurrences of the nodes and the links provide the input required to analyze relative frequency of occurrence, as well as opening a scope for further statistical analysis. While our raw data was a corpus of literature from a specific discipline, this enhancement is accessible to any qualitative analysis that recognizes causality in its structural codes.