Examining mental representations of contamination stimuli in a population with obsessive-compulsive disorder, a data-driven approach

Exposure with response prevention (ERP) is the gold standard for treating obsessive-compulsive disorder (OCD) and is recommended by national and international treatment guidelines. Despite recent developments in this approach, a large share of patients remains symptomatic after treatment, discontinue treatment or are reluctant to start treatment at all. One reason might be that the stimulus material used during ERP is not tailored to the patient, so it does not necessarily target the relevant dimensions of the OCD symptomatology. Currently, there exists no contamination OCD (C-OCD) stimuli set that is validated to provoke other emotions than anxiety, that offers a wide range of intensities along different emotions. It is conceivable that other dimensions of the stimuli are of relevance than the theory-driven dimensions rooted in preexisting emotional theories that represent a fixed model of mental representations, and therefore might miss important unknown domain specific dimensions that might be of higher relevance for some patients. This project intends to complement theory-driven approaches by a data-driven approach to identify relevant dimensions of C-OCD triggers by exploring their mental representations. Methodologically, crowdsourced similarity judgements will be implemented that will be analyzed with multidimensional scaling to identify underlying dimensions followed by a crowdsourced dimension-naming task. Further characterizing C-OCD stimuli and their mental representations as well as compiling a freely available database of contamination-OCD cues will inform the design of new personalized ERP approaches that counteract common problems of ERP treatments for OCD.