Deductive Qualitative Analysis: Evaluating, Expanding, and Refining Theory

Abstract

Although qualitative research is often equated with inductive analysis, researchers may also use deductive qualitative approaches for certain types of research questions and purposes. Deductive qualitative research allows researchers to use existing theory to examine meanings, processes, and narratives of interpersonal and intrapersonal phenomena. Deductive qualitative analysis (DQA; Gilgun, 2005, 2019) is one form of deductive qualitative research that is suited to theory application, testing, and refinement. Within DQA, researchers combine deductive and inductive analysis to examine supporting, contradicting, refining, and expanding evidence for the theory or conceptual model being examined, resulting in a theory that better fits the present sample and accounts for increased diversity in the phenomenon being studied. This paper acts as a primer on DQA and presents two worked examples of DQA studies. Our discussion focuses on the five primary components of DQA: selecting a research question and guiding theory, operationalizing theory, collecting a purposive sample, coding and analyzing data, and theorizing. We highlight different ways of operationalizing theory as sensitizing constructs or as working hypotheses and discuss common pitfalls in theory operationalization. We divide the coding and analyzing process into two sections for parsimony: early analysis, focused on familiarity with the data, code generation, and identification of negative cases, and middle analysis, focused on developing a thorough understanding of evidence related to the guiding theory and negative cases that depart from the guiding theory. Theorizing occurs throughout as researchers consider ways in which the theory being examined is supported, refuted, refined, or expanded. We also discuss strengths and limitations of DQA and potential difficulties researchers may experience when utilizing this methodology.