Changing maladaptive cognitions in traumatized children
Using artificial intelligence analysing 10,000 sessions of trauma-focused cognitive behaviour therapy.
Project Manager
Project Members
The primary objective is to identify treatment aspects and techniques that lead to reduction of maladaptive trauma-related cognitions and subsequent symptom improvement in TF-CBT. This contributes to increase our understanding of therapeutic resolution of PTSD. We will do so by developing and validating a new AI-assisted tool to identify and classify therapeutic techniques and children’s emotional engagement, and combine this with self-report data on alliance, maladaptive cognitions and symptoms of PTSD.
We will conduct a naturalistic mixed methods observational study where qualitative observational data will be combined with quantitative data from independent psychologist specialists as well as quantitative self-report data from the children. The data sources are: 1) 10,000 audio files/transcriptions of TF-CBT sessions with 550 children and their therapists. 2) Self-reported data on maladaptive thoughts and PTSD symptoms from validated questionnaires. 3) Assessments from psychologist specialists regarding therapists’ adherence to TF-CBT components. By developing, testing, and using AI tools on this dataset, we aim to achieve new knowledge that can improve trauma treatment.