mHealth interventions for youth increasingly capitalize on the ubiquity and high uptake of social media and digital communication tools. Despite the promise of mHealth interventions, barriers to intervention delivery remain. A motivating example is provided by a study that aimed to prevent HIV among youth at high risk for acquiring HIV, including men having sex with men, transgender women, homeless and substance-using youth. The sample includes 914 youth, ages 14 to 24 who received weekly short message service (SMS) surveys on their mobile phones to help them self-monitor risk behaviors and stay engaged in the study. About half of the participants responded to surveys. It is important to understand the characteristics of non-responders for future intervention development. In this vein, we applied a hidden Markov model to the data to understand response patterns. Three clusters emerged: active responders who filled out most weekly surveys, intermittent responders, and inactive participants who rarely filled out surveys. A key predictor of cluster membership was whether the participant had ever been homeless.