Mediation Analyses for Carbohydrate Counting
As participants in the intervention condition showed significant improvement over time for carbohydrate counting, a mediation analysis (Hayes, 2013) was conducted to assess whether the integrated model variables mediated the impact of the intervention on carbohydrate counting. In addition to pre-intervention carbohydrate counting behavior, all potential mediators, along with Condition, were entered into the model. The direct effect of Condition on behavior was significant, B=0.54, SE=0.14, p<0.01 . Bootstrapping analyses resulted in the total significant mediated (indirect) effect as B=0.26, SE=0.12, CI=0.01 to 0.51 . The indirect effect was significant only via planning, B=0.10, SE=0.06, CI=0.01 to 0.26 . Further, inspection revealed that, after the inclusion of potential mediators (integrated model variables), the direct effect of the intervention on carbohydrate counting behaviour remained significant, B=0.37, SE=0.16, CI=0.03 to 0.71,indicating a partial mediation effect.