ObjectivesTo determine the effect on weight of two Mobile technology-based (mHealth) behavioral weight loss interventions in young adults.MethodsRandomized, controlled comparative effectiveness trial in 18–35 year olds with BMI ≥ 25 kg/m2 (overweight/obese), with participants randomized to 24 months of mHealth intervention delivered by interactive smartphone application on a cell phone (CP); personal coaching enhanced by smartphone self-monitoring (PC); or Control.ResultsThe 365 randomized participants had mean baseline BMI of 35 kg/m2. Final weight was measured in 86% of participants. CP was not superior to Control at any measurement point. PC participants lost significantly more weight than Controls at 6 months (net effect −1.92 kg [CI −3.17, −0.67], p=0.003), but not at 12 and 24 months.ConclusionsDespite high intervention engagement and study retention, the inclusion of behavioral principles and tools in both interventions, and weight loss in all treatment groups, CP did not lead to weight loss and PC did not lead to sustained weight loss relative to control. Although mHealth solutions offer broad dissemination and scalability, the CITY results sound a cautionary note concerning intervention delivery by mobile applications. Effective intervention may require the efficiency of mobile technology, the social support and human interaction of personal coaching, and an adaptive approach to intervention design.Trial RegistrationClinicalTrials.gov Identifier NCT01092364.https://clinicaltrials.gov/ct2/show/NCT01092364?term=Cell+phone+intervention+for+you&rank=3

In 2004, Murray et al. reviewed methodological developments in the design and analysis of group-randomized trials (GRTs). We have highlighted the developments of the past 13 years in design with a companion article to focus on developments in analysis. As a pair, these articles update the 2004 review. We have discussed developments in the topics of the earlier review (e.g., clustering, matching, and individually randomized group-treatment trials) and in new topics, including constrained randomization and a range of randomized designs that are alternatives to the standard parallel-arm GRT. These include the stepped-wedge GRT, the pseudocluster randomized trial, and the network-randomized GRT, which, like the parallel-arm GRT, require clustering to be accounted for in both their design and analysis.