The current study investigates participants’ perspective on the predictive relationship between (prodromal) symptomology and mood episodes. In addition, it aims to gain insight in successful self-management strategies. To this end, we launched an online questionnaire in The Netherlands and Belgium through several patient networks for bipolar disorder. Participants with bipolar spectrum disorder (n=100) were asked to indicate the predictiveness of certain early symptoms for either depressive or (hypo)manic episodes. In addition participants were asked how helpful certain strategies were in managing specific mood episodes. The results of the current study provide important user generated information that can be implemented in future mHealth self-management tools for bipolar disorder.Specifically, the present study has generated important insights into the predictive power of prodromal symptomology that signals the occurrence of an episode of mood dysregulation and will provide a database of successful strategies that specifically target such mood-symptom correlations when they arise and thus help to prevent further exacerbation of mood instability. Availability of such strategies to people with bipolar disorder through a mHealth application will be crucial to the effectiveness of their self-management.