Ecological momentary assessment (EMA) has been used in many mHealth apps. EMA captures valuable insights into many diseases. Identifying the Granger causal relationships across the EMA variables may contribute to the interpretation of a disease and improve treatment decisions. In our study, we perform a circadian conditional Granger causality analysis on multivariate time series. The analysis was done on EMA data of 270 users of an mHealth app on tinnitus and on their registration data, using the latter to explain the circadian conditional Granger causal relationships. We discovered that some EMA items Granger cause others for more than 8% of the mHealth app users and that these users have answered 8 out of 40 questions at registration differently.