OPTIMAX: Optimising Outcomes in Psychotherapy for Anxiety Disorders
Anxiety disorders, such as phobia, panic disorder or generalized anxiety disorder, are the most common class of mental disorders present in the general population. They are hugely disruptive, place psychological distress and role impairments on individuals and their families and create a serious economic burden for society. Psychological psychotherapies, such as cognitive behavior therapy (CBT), based on principles of basic cognitive and behavioral science and implemented via standardized treatment manuals, are amongst the most effective treatments for such disorders. These treatments are nevertheless only moderately successful in initiating and sustaining individual change in anxiety.
The present program of research aims to improve outcomes in CBT for anxiety. To achieve this objective, a multi-method research program is proposed combining a large-scale clinical study with experimental laboratory paradigms. First, I will in a randomized controlled clinical trial examine genetic, endocrine, demographic and clinical predictors of response to CBT for anxiety. Using cutting-edge machine learning analysis methods will enable classification of subtypes of individual treatment responses based on these multiple predictors. Second, drawing from basic neuroscience science findings, I will in the laboratory examine the potential of (i) brain stimulation and (ii) memory reactivation during sleep to enhance learning during CBT. The projected findings will lead to important theoretical and clinical innovations in forecasting treatment outcome and break the ground for improving current psychotherapy for anxiety disorders that forms an ever-growing burden for society.
Künzler, F. (2019) Context-aware notification management systems for just-in-time adaptive interventions, PhD Forum at the IEEE International Conference on Pervasive Computing and Communications (PerCom), Kyoto, Japan, 435-436. (PDF)
Künzler, F., Kramer, J., Kowatsch, T. (2017) Efficacy of Mobile Context-aware Notification Management Systems: A Systematic Literature Review and Meta-Analysis, IEEE 13th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Rome, Italy, 131-138. (PDF)
Kowatsch, T., Nißen, M.K., Shih, I., Rüegger, D., Volland, D., Filler, A., Künzler, F., Barata, F., Haug, S., Büchter, D., Brogle, B., Heldt, K., Gindrat, P., Farpour-Lambert, N., l’Allemand, D. (2017) Text-based Healthcare Chatbots Supporting Patient and Health Professional Teams: Preliminary Results of a Randomized Controlled Trial on Childhood Obesity, Persuasive Embodied Agents for Behavior Change (PEACH 2017) Workshop, co-located with the 17th International Conference on Intelligent Virtual Agents (IVA 2017), Stockholm, Sweden. (PDF)
Kowatsch, T., Volland, D., Shih, I., Rüegger, D., Künzler, F., Barata, F., Filler, A., Büchter, D., Brogle, B., Heldt, K., Gindrat, P., Farpour-Lambert, N., l’Allemand, D. (2017) Design and Evaluation of a Mobile Chat App for the Open Source Behavioral Health Intervention Platform MobileCoach, In: Maedche A., vom Brocke J., Hevner A. (eds) Designing the Digital Transformation. DESRIST 2017. Lecture Notes in Computer Science, vol 10243. Springer: Berlin; Germany, 485-489. (Paper-PDF | Poster-PDF | Slide-PDF | Screencast)
Filler, A., Kowatsch, T., Haug, S., Wahle, F., Staake, T. & Fleisch, E. (2015) MobileCoach: A Novel Open Source Platform for the Design of Evidence-based, Scalable and Low-Cost Behavioral Health Interventions – Overview and Preliminary Evaluation in the Public Health Context. Wireless Telecommunications Symposium 2015 (WTS 2015), New York, USA. ***Outstanding Paper Award & Best Graduate Student Paper Award*** PDF