Exploring the conflict between oral health and patient autonomy: A feasibility study using epistemic network analysis

Medical ethics has relied heavily on theoretical argumentation; however, addressing complex, real-world ethical issues necessitates contextual understanding and empirical research. Qualitative methods are appropriate for exploring normative and phenomenological perspectives; such data are usually coded to explore patterns therein, which can be represented in quantitative models as well. Our objective was to showcase and address the utility of epistemic network analysis (ENA) in refining existing theory. We conducted interviews with dentists and patients on ethical challenges of patient autonomy in dentistry. Utilizing a codebook of ethical constructs based on theory, we amended the codebook with guided-inductive coding, and after coding the dataset deductively, we visualized the relative co-occurrence of codes and compared groupings of data. We refined existing ethical constructs and identified novel ones to create ENA models. Using these models, we demonstrated that examining the relative co-occurrence computed for various groupings yields richer insights into the data. However, ENA has its limitations, such as creating codes for different groups, defining those groups, or not gaining meaning from codes in isolation. Operationalizing theory and creating ENA models enables the researcher to identify points of consensus and divergence in stakeholder narratives and leverage various perspectives to inform, validate, or refine theory.