Scientific models for qualitative research: a textual thematic analysis coding system – Part II

Background Models are central to the acquisition and organisation of scientific knowledge.
They can be viewed as tools for interpretive description as well as cognitive representations of
an empirical phenomenon. However, discussions about how to develop models in qualitative
research – particularly in the literature on thematic analysis – are sparse.
Aim To discuss an approach to scientific qualitative modelling that uses the new technique
described in the first part of this article (Gildberg and Wilson 2023): the Empirical Test for
Thematic Analysis (ETTA).
Discussion The authors discuss scientific models and their inherent limitations and strengths,
so that others may assess models and their potential.
Conclusion A limitation of ETTA is the risk that excessive rigour and systematisation could
reduce creativity in the construction of models. However, on balance there is a scientific need
for qualitative researchers to improve their capability to refine and describe the techniques
they use to construct models, adequately explain the reliable generation of models, and
improve transparency regarding the epistemological and methodological basis for the
construction of models.
Implications for practice By using ETTA on qualitative data obtained from clinical practice
it becomes possible to illuminate the interconnections among themes within the data. This
approach not only assists in illustrating these connections, it also enables clinicians and
researchers to gain a comprehensive understanding of specific clinical phenomena through
the use of models. The process of developing and using these models enables the simulation
and strategic intervention development based on data that addresses the specific problem
being investigated.

doi: 10.7748/nr.2023.e1893