AI4CBT – Explainable, Human-Centric, Psychology- Grounded Fine-Grained Assessment and Planning for Cognitive Behavioral Therapy

Background

Mental illness is one of the largest causes of suffering in society and of social costs. An alternative to the classic therapies, characterized by high treatment costs, is the online Cognitive Behavioral Therapy (CBT). It provides a scalable, cost-effective, and accessible approach, building on modules that patients can carry out independently. CBT therapists are required to assess patients’ therapeutic context and recommend appropriate therapeutic plans. Currently, these activities are carried out manually, using scales and therapists’ intuitions and memories, which are known to be time-consuming and difficult to carry as the number of patients or sessions increase.

Aim

To establish foundations for developing AI-enhanced CBT therapy methods for supporting therapists both during the assessment and therapy planning phases.

Methods and results

Systematic literature reviews for developing a specific vocabulary, ontology and theory through interdisciplinary crossing of AI assessment and planning methods with psychology and therapeutic assessment and planning methods and praxis. Data collection for enabling the validation and assessment of future tools.

Significance

WASP-HS perspective: The project will bring forwards new approaches for AI methods to be used for mental health and psychology research praxis, in particular in the context of CBT applied for depression and anxiety.

DDLS perspective: Data collection will support assessing the relations between the key variables for training, calibrating and validating assessment and CBT planning models.

Together, the project provides a concrete case for enabling a scalable precision personalized mental healthcare and wellbeing.