Analytic methods: For Aim 1, in the context of repeated measures ANOVA, using t-tests within arm to detect change from baseline to 12-months (Follow-up 3), power exceeds 0.99 for all primary outcomes. For Aim 2, six analyses will assess heterogeneity of treatment effects by evaluating the interaction of each key, dichotomized, baseline characteristic with treatment arm, estimating means and standard errors of six subclasses, and within each characteristic (e.g. low or high health literacy) testing for differences between TM and HC, TM and EC, and HC and TM. Analyses for Aim 3 will be conducted as described above for Aim 1. With the proposed sample sizes differences can be detected within either the rural or urban setting on two-sided tests at alpha of 0.05 with power of 0.953, 0.779 and 0.829, respectively. Thus, both the rural and urban subgroups will have adequate power to detect a meaningful difference in effectiveness between each active arm and the EC arm. If the arms are combined, ignoring rural and urban setting, the combined active arms will have > .999, .972, and .985 respectively.