Scientific models for qualitative research: a textual thematic analysis coding system - Part 1

Area of Science:

• Qualitative Research Methods
• Scientific Modeling
• Thematic Analysis

Background:

• Models are crucial for scientific knowledge acquisition and organization.
• Developing models in qualitative research, especially thematic analysis, lacks clear methodologies.
• This gap hinders the systematic construction of qualitative models.

Purpose of the Study:

• To introduce a novel technique for scientific qualitative modeling: Empirical Testing Thematic Analysis (ETTA).
• To provide a detailed description of the ETTA model and its application.
• To offer a structured approach for researchers aiming to build models from qualitative data.

Main Methods:

• The study describes the Empirical Testing Thematic Analysis (ETTA) technique.
• ETTA involves a sequential process accounting for taxonomic analysis, functionality, preconditioning items, cascade directories, and modulation factors.
• The method emphasizes authenticity markings and semantic analysis.

Main Results:

• ETTA generates a semantic structure comprising theme-code, content, and functionality.
• The technique highlights the significance of authenticity markings and both taxonomical and functional semantic analysis.
• ETTA ensures a sound and systematic development of qualitative models.

Conclusions:

• Empirical Testing Thematic Analysis (ETTA) offers a rigorous framework for qualitative model development.
• The method is particularly beneficial for nurse researchers seeking to build models from their qualitative investigations.
• This article presents a step-by-step guide for researchers to construct models derived from qualitative research.