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Following the example of Heller et al��s analysis of patient activation [13], low-activated respondents were classified as giving a response of 1, 2, or 3 to each of the 4 measures of activation. Scores of 4 and 5 designated activated patients. Surveys with complete responses were analyzed with no adjustments for the responses. Data Analysis Data were analyzed with a mixed design with 1 within-subjects factor (pre-post) and 1 between-group factor (persona). The general linear model with repeated measures in SPSS version 21 (IBM Corp, Armonk, NY, USA) was used for the analysis [26]. Since the JQ1 pre-post dependent measures were significantly correlated with each other (P=.05), the multivariate results for Pillai��s trace (V) and related statistics are reported [27]. The assumption of equality of covariance matrices of the dependent measures was tested with Box��s test of equality of covariance matrices. In no instance was a significant difference (Pselleck products was obtained a second time with users responding to the question, ��Do you agree to the use of your survey responses as noted above?�� Results A total of 398 participants were recruited (249 women and 149 men). In all, 86.7% (345/398) of the participants were white/non-Hispanic; 7.0% (28/398) of the sample was African-American, and the rest were Native American, Asian, or multiracial (25/398). Of the sample, 89.9% (358/398) had completed at least some college coursework. Overall, participants tended to be middle-age and older with 5.0% (20/398) in the 18 to 24 age range, 15.1% (60/398) in the 25 to 34 age range, 39.9% (159/398) in the 35 E-64 to 54 age range, and 39.9% (159/398) in the 55-years-and-older category. Potential associations between the sociodemographic variables and course selected were of interest for understanding the user experience. There was a significant association between age and course used (��2 15=72.5, P