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Background: Medication nonadherence is a leading cause of late allograft loss in kidney transplantation (KT). Tacrolimus trough coefficient of variation (CV), measured using the coefficient of variation, is strongly correlated with acute rejection, graft function, and graft loss., Objective: The objective of this study was to determine if this mobile health (mHealth) intervention aimed at improving medication adherence in a nonadherent KT population would affect high intrapatient tacrolimus variability., Methods: A 6-month, prospective, parallel-arm, randomized controlled clinical trial was conducted to determine the effects of an mHealth intervention on tacrolimus CV. Intervention arm participants utilized an electronic medication tray and an mHealth app to monitor home-based adherence. Tailored motivational reinforcement messages were delivered to promote competence for adherence. Tacrolimus CV was measured using a 12-month rolling average, assessed at monthly intervals (6-month intervention period and 6 months after completion of the study); 80 were included, 40 in each arm., Results: At baseline, tacrolimus CV was similar between arms (37% ± 15% intervention, 37% ± 13% control, P = 0.894). Patients randomized to the intervention had a significant reduction in mean 12-month tacrolimus CVs ( P = 0.046) and a significant improvement in the proportion achieving low tacrolimus CV (tacrolimus CV < 40%; P = 0.001), as compared with the control arm., Conclusion and Relevance: High tacrolimus CV is a risk factor for acute rejection and graft loss; these results offer the potential promise of improved medication adherence and clinical outcomes through the use of innovative technology.

Background: Childhood obesity continues to be a global epidemic and many child-based settings (e.g. school, afterschool programs) have great potential to make a positive impact on children's health behaviors. Innovative and time-sensitive methods of gathering health behavior information for the purpose of evaluation and strategically deploying support are needed in these settings., Purpose: The aim is to (1) demonstrate the feasibility of mobile health (mHealth) for monitoring implementation of healthy eating and physical activity (HEPA) standards and, (2) illustrate the utility of mHealth for identifying areas where support is needed, within the afterschool setting., Methods: Site leaders ( N = 175) of afterschool programs (ASPs) were invited to complete an online observation checklist via a mobile web app (Healthy Eating and Physical Activity Mobile, HEPA m ) once per week during ASP operating hours. Auto-generated weekly text reminders were sent to site leaders' mobile devices during spring and fall 2015 and 2016 and spring 2017 school semesters. Data from HEPA m was separated into HEPA variables, and expressed as a percent of checklists where an item was present. A higher percentage for a given item would indicate an afterschool has higher compliance with current HEPA standards., Results: A total of 141 site leaders of ASPs completed 13,960 HEPA m checklists. The average number of checklists completed per ASP was 43 (range 1-220) for healthy eating and 50 (range 1-230) for physical activity. For healthy eating, the most common challenge for ASPs was 'Staff educating children about healthy eating', and for physical activity checklists, 'Girls only physical activity is provided at ASP'., Conclusion: HEPA m was widely used and provided valuable information that can be used to strategically deploy HEPA support to ASPs. This study gives confidence to the adoption of mHealth strategies as a means for public health practitioners to monitor compliance of an initiative or intervention.