Online weight-loss communities (OWCs) provide individuals with various tools to support their weight management, such as weight recorders and weight-loss journals. These tools enable individuals to focus on different aspects of their self-regulation, including weight-loss outcomes and behavioral routines. Prior research, however, has not fully incorporated individuals’ self-regulation focuses; thus, there is limited understanding of individuals’ online weight-management dynamics as well as the operating mechanisms of OWCs. This gap in the literature motivates us to develop a framework that is able to account for individuals’ multiple self-regulation focuses, termed self-regulatory dimensions in this study. We propose a multidimensional, continuous-time hidden Markov model, which can not only capture individuals’ self-regulatory dimensions jointly as a multidimensional vector, but also can incorporate a hidden layer of dynamics that depicts individuals’ cognitive states in producing weight-management behaviors. By investigating a leading noncommercial OWC in the United States, we find that individuals tend to increase their journal-recording behaviors while decreasing self-weighing behaviors after they have participated in online social activities. Given that individuals usually expend limited effort toward weight management, this result suggests that individuals may shift their focus from weight-loss outcomes (i.e., changes in weight) to weight-management behavioral routines. Therefore, neglecting either self-regulatory dimension would result in an underestimation of individuals’ engagement in conducting self-management in OWCs. Our results also provide insight into social influence on individuals’ weight-management behaviors. This study contributes to the extant literature on individuals’ engagement in online healthcare communities and the functionality of OWCs. This paper was accepted by Anandhi Bharadwaj, information systems.