Interpreting cross-sectional data on stages of change

The vast majority of studies investigating stage theories of health behavio ur such as the transtheoretical model have used a cross-sectional research design. Participants are classified into stages and compared on theoretical ly relevant variables. This paper discusses the proper interpretation of cr oss-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 s tage model. Researchers who use cross-sectional designs should specify pred ictions concerning the patterns to be expected under a stage model and unde r possible rival models, and interpret their data accordingly. Wherever pos sible, they should conduct prospective longitudinal and experimental studie s which enable stronger inferences to be drawn.