Theorydriven

Theory-driven is an approach in research and analysis in which theoretical frameworks guide the formulation of research questions, hypotheses, study design, and interpretation of findings. In a theory-driven approach, existing theories propose relationships among variables, which researchers operationalize as measurable constructs and test with data. This stands in contrast to data-driven or exploratory approaches that emphasize discovering patterns in the data with minimal prior theory. Theory-driven research emphasizes deductive reasoning, where hypotheses are derived from theory and subjected to falsification.

In practice, a theory-driven study begins with a theoretical model or framework that specifies constructs and the expected relations among them. Researchers define variables to represent those constructs, select or develop measures, and specify statistical or analytical models that test the proposed relationships. The analysis is typically judged by how well the results align with the theoretical predictions, rather than by how many novel patterns emerge.

Theory-driven perspectives are common across the social sciences, psychology, economics, health sciences, and information systems. Examples include testing established theories such as the Theory of Planned Behavior, applying structural equation modeling to assess a proposed causal path, or using domain-specific theories to guide intervention design. Theory-driven work often emphasizes transparency, preregistration, and cumulative knowledge formation.

Criticism centers on potential bias toward existing theories, the risk of constraining discovery, and the possibility that empirical data may be misfit to a theory. Proponents argue that theory-driven research provides falsifiable hypotheses and interpretive coherence, enabling cumulative advancement. The term is commonly written as theory-driven, though some sources also use the closed form theorydriven.