It is common for notions of health and behaviour to be multidimensional. Structural equation modelling (SEM) incorporates ideas from regression, path-analysis and factor analysis. SEM allows the original predictors and outcomes summarised by underlying latent variables while also accounting for relationships between the latent variables. A Bayesian approach to SEM enables models that are easy to interpret and supported by data, while also portraying research hypotheses. The development and application of Bayesian approach to SEM is presented.