Optimal design software has been used to make a preliminary determination that 100 or more participants in a randomized quadratic growth individual change model will achieve a power of .80 to .95 for a study expecting an effect size of between 0.6 to .80, respectively (0.62 is premised upon meta-analysis for CES undertaken by Klawansky, et al., 1995 and .8 is considered a large effect by Cohen, 1988). We will employ power analysis again once sample size is confirmed following recruitment of participants and expect upwards of 150 or more participants. Missing data will be explained using an intent-to-treat analysis whereby we employ redundant analysis procedures (i.e., survival analysis) to understand and context the true treatment effect.