Interpreting cross-sectional data on stages of change

Abstract

The vast majority of studies investigating stage theories of health behaviour such as the transtheoretical model have used a cross-sectional research design. Participants are classified into stages and compared on theoretically relevant variables. This paper discusses the proper interpretation of cross-sectional data on stages of change. Linear patterns are not consistent with the stage model assumption that different causal factors are important at different stages but discontinuity patterns (patterns that do not show consistent increments or decrements across stages) can be diagnostic of a stage model. Researchers who use cross-sectional designs should specify predictions concerning the patterns to be expected under a stage model and under possible rival models, and interpret their data accordingly. Wherever possible, they should conduct prospective longitudinal and experimental studies which enable stronger inferences to be drawn.