In contrast to the disease model, that claims one factor is the cause of someone's symptoms, the network theory proposes that the symptoms cause each other. The network model enables therapists and researchers to conceptualise disorders, such as depression, differently. By unravelling these symptom-to-symptom-relationships, a personalized network of one’s depression symptoms can be created and visualised. This method is known as the PECAN - Perceived Causal Network - approach and consists of both symptoms (the nodes) and the relationship between symptoms (the edges). However, it is still unclear if all these symptoms relate to each other in the same way. More specifically it is implicitly assumed that these relationships follow a linear pattern, but is this assumption valid? To test this, participants were asked what symptoms they experienced during a time in their life when they felt depressed/down, and if so, which other symptoms caused this. In addition, they were also asked in what way they perceived these symptoms to relate to each other; to investigate whether the linearity assumption was suitably applicable for the network model. If you are interested in the results of this study or in the PECAN approach in general, feel free to join this presentation!