PhD Studentship: PhD Opportunity Title An AI driven approach for aiding towards the mental wellbeing of online social network usersUsing natural language processing to understand and enhance therapeutic mechanisms in digital psychological therapy

Project description:

This studentship will seek to integrate expertise from psychology and computer science to develop and test natural language processing (NLP) of patient responses within digital cognitive-behavioural therapy for worry and overthinking. Psychological research indicates that distinct modes of cognitive processing causally influence whether overthinking is helpful or unhelpful, brief versus prolonged (e.g., reviewing negative events in an abstract, general way [e.g., “Why me?”] versus more specific contextualised processing [e.g., “How did this happen?”]; self-critical processing versus self-compassionate processing).

The goal of this studentship is to develop, train, and test NLP models that can (a) assess these cognitive mechanisms within text relative to human judgement (e.g. performing sentiment analysis and topic modelling and measuring textual cohesion and coherence); provide feedback on performance tailored to therapy users; (c) assess whether such feedback improves engagement and effectiveness of the therapy.

Methods include experimental studies involving controlled text generation from a validated corpus using tailored large language models, and the use of different NLP approaches (e.g., surface oriented, number of words, coherence measures, underlying themes in topic modelling, sentiment analysis).

The studentship will include training in experimental methods and advanced cognitively inspired NLP models, access to regular seminars and conferences, and will afford professional development opportunities in cognitive science, clinical psychology, the development of digital therapy and conversational agents. Infrastructure and support will include use of the facilities of the Sir Henry Wellcome Building for Mood Disorders Research, a fit-for-purpose clinical research facility, and the Institute for Data Science and Artificial Intelligence (IDSAI), which provides a hub for data-intensive science and artificial intelligence (AI) activity within the University of Exeter and the wider region.

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