ieso commissioned this research study, using a deep learning approach, to understand the relationship between patient language and outcomes in internet-enabled cognitive behavioural therapy.
ieso uses a data-driven approach to define fluid depressive states and explore how patients transition between these states in response to cognitive behavioural therapy (CBT).
ieso uses therapy transcripts derived from internet enabled cognitive behavioural therapy (CBT) treatment sessions to understand how therapist variables are associated with clinical outcomes in IAPT.
In this study, ieso adopts a deep learning model to automatically categorize therapist utterances from approximately 90 000 hours of internet-enabled cognitive behavior therapy (CBT).
ieso piloted a comparative study of therapy sessions following the interaction of 10 participants with human therapists versus a chatbot to recommend ways of overcoming the drawbacks of chatbots.
ieso introduces and demonstrates the usefulness of a tool that automatically annotates therapist utterances in real-time according to the therapeutic role.
This study, commissioned by ieso, investigates the demographic and clinical predictors of response to one-to-one CBT delivered via the internet.
In this multicentre, randomised controlled trial, ieso investigates the eﬀectiveness of CBT delivered online in real time by a therapist for patients with depression in primary care.