Fully Funded PhD Scholarship in Psychology

University of Sheffield - Psychology

Project title: A network approach to bipolar disorder


Primary supervisor: Richard Bentall

Co-supervisor/s:  Prof Jamie Murphy at the University of Ulster

Project description:  Abstract: Bipolar disorder is a severe but complex condition, which may not be entirely separate from the other psychotic disorders such as schizophrenia (Tamminga et al., 2014). According to classical accounts, patients fluctuate between the three phases of euthymia (normal functioning), depression and mania (characterised by periods of intense excitement, irritability and sometimes psychosis (Cassidy, Forest, Murry, & Carroll, 1998); hence the term ‘bipolar disorder’. However, mania can co-occur with depression in a so-called ‘mixed episode’ (McElroy et al., 1992) and, longitudinally, the two types of mood symptoms fluctuate almost independently (Johnson et al., 2011). The manic state is probably the least understood psychopathological phenomenon, and existing psychological theories implicate dysfunctional strategies for avoiding depression and abnormal reward sensitivity (Mason, O'Sullivan, Montaldi, Bentall, & El-Deredy, 2014; van der Gucht, Morriss, Lancaster, Kinderman, & Bentall, 2009). Major progress in understanding bipolar disorder would be achieved by advancing our understanding of the manic state, and how it relates to the depressed state.

Network models provide a novel approach to understanding the structure of psychopathology and the underlying causal processes that lead to illness (Borsboom & Cramer, 2013). According to this approach, recognizable ‘syndromes’ (clusters of symptoms) occur, not because the symptoms have common underlying causes, but because symptoms are connected in a network of causal relationships so that triggering one symptom can lead to a cascade of others. Importantly, new statistical tools allows us to discover the potential underlying causal relationships. Mania is a network of symptoms, almost by definition, and yet this approach has never been applied to bipolar disorder.

This research will begin by using network analysis with two datasets: 255 well-characterized bipolar patients followed up at regular intervals over a two-year period; and a large population sample (N > 30,000) in which people were interviewed about mood symptoms. The aim will be to develop a network analysis of the relationship between depression and mania and, in the longitudinal datset, characterize how network structure is related to vulnerability to reoccurrence of symptoms (relapse). In later stages of the work, it may be possible to test hypotheses generated from the analyses in small-scale experimental studies with bipolar patients

Start date: 1 October 2018

Requirements:  Applicants must have a minimum of a first class or high upper second-class undergraduate honours degree and a distinction or high merit at Masters level in psychology or a related discipline.

Funding: Tuition fees £4194 per year Living Expenses £14,500.00

Science Graduate School

As a PhD student in one of the science departments at the University of Sheffield, you'll be part of the Science Graduate School. You'll get access to training opportunities designed to support your career development by helping you gain professional skills that are essential in all areas of science. You'll be able to learn how to recognise good research and research behaviour, improve your communication abilities and experience the breadth of technologies that are used in academia, industry and many related careers. Visit www.sheffield.ac.uk/sgs to learn more.

For further details and the application process please visit:


Closing date for applications is 5pm Wednesday 24 January 2018

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Northern England