UC Irvine

Despite a growing interest in self-tracking of one's health, what factors lead to self-tracking routinely (i.e., collecting data at regular intervals), and the effects of this behavior, remain largely understudied. Using data from the Pew Survey on Tracking for Health, we examined the patterns of self-tracking activity to understand reasons for this behavior and its impact on health management practices. We tested multiple logistic regression models to assess the influence of different predicting variables, and to find whether routine self-tracking leads to positive change to one's approaches to health management. Our results suggest that recent visits to emergency care and the type(s) of tracking tools used are significant predictors of routine self-tracking activities. Further, the results suggest that routine self-tracking, as opposed to occasional, event-triggered tracking, is more likely to result in positive changes to health management approaches. Our findings also highlight barriers to and opportunities for designing useful and usable tools to facilitate self-tracking and empower patients to become more proactive in managing their own health.