[Corpora-List] ** Deadline 18th February ** ESRC CASE PhD Studentship: Understanding how people living with bipolar disorder talk about risk on social media

Rayson, Paul p.rayson at lancaster.ac.uk
Mon Feb 10 10:48:55 CET 2020

ESRC CASE PhD Studentship: Understanding how people living with bipolar disorder talk about risk on social media Lancaster University | Division of Health Research | Lancaster | United Kingdom

Supervision Team: Prof Steven Jones, Prof Fiona Lobban (Spectrum Centre for Mental Health Research, Department of Health Research) Dr Paul Rayson (UCREL research centre, School of Computing and Communications) Dr Jasper Palmier-Claus (Lancashire and South Cumbria NHS Foundation Trust)

Application Deadline: Tuesday, February 18, 2020

Project Description Individuals living with bipolar disorder are likely to engage in behaviours which can be risky for themselves or others. This includes increased prevalence of suicide and self‐harm, excessive spending, alcohol or drug use and risky sexual behaviour. Understanding more about this behaviour is crucial as with the right help people living with bipolar “have the potential to return to normal function with optimal treatment” p 45 (NICE, 2014).

Current psychological models of bipolar explain risky behaviour as an attempt to avoid low mood, a response to mood elevation or to impulsivity/sensitivity to reward. These approaches have informed the development of psychological interventions to improve coping strategies for mood change. However, the effectiveness of such approaches is mixed and evidence is lacking for improvements in the functional and recovery outcomes which qualitative research has shown are valued. Current research has relied on questionnaire measures of hypothesised processes, which limits what can be learnt about the subjective experiences of people living with bipolar. For instance, they tell us little about how such individuals define risk, why they chose to engage in some such behaviours and how socially normative such behaviour might be. It is clear therefore, that a mixed method approach is needed to understand the processes which underpin risk in bipolar. This should combine in‐depth qualitative approaches with methods that explore how people describe their experiences in natural language, not constrained by typical research or clinical settings. This is particularly important for risky behaviour that is likely to have been stigmatised.

Services users increasingly share information through Facebook, Twitter, Reddit (a comprehensive network of user forums) and blogs. The volume of such data would prevent manual processing but computational linguistics offers opportunities to learn more about how people describe their risk experiences on these platforms. Natural language processing has been employed to predict suicidality. In contrast to this potentially ethically problematic predictive approach, this research seeks to understand what such behaviours mean to the individual, how they calibrate risk, and why they chose to engage or not with risk.

This ESRC-funded CASE studentship will take a mixed‐methods approach. The student will conduct a systematic review of risk taking in mood disorders to inform a qualitative investigation of this area in bipolar disorder, to help to shape a framework for the natural language processing of social media posts on Twitter and Reddit. To ensure relevance to people living with bipolar disorder the PhD student will work with service user advisors to finalise the implementation and dissemination of the research. This builds on work by the supervisory team using this approach to understand personal recovery in bipolar disorder.

Key questions

1. What does current research tell us about relationships between risky behaviour and the experiences of people living with mood disorders (including bipolar disorder)? 2. How do people with bipolar disorder describe risk? 3. What range of risky behaviours do people with bipolar describe? 4. What reasons do people report for risky behaviour and what contextual and emotional factors influence this?

Funding Notes This full-time three-year CASE Studentship covers fee plus a stipend of 15,009. The studentship is available from October 2020. ESRC Residential conditions: To be eligible for a full award (stipend and fees), you must meet all of the following conditions:

* have settled status in the UK, meaning there are no restrictions on how long you can stay

* have been 'ordinarily resident' in the UK for three years prior to the start of the studentship grant. This means you must have been normally residing in the UK (apart from temporary or occasional absences)

* not have been residing in the UK wholly or mainly for the purpose of full-time education. This does not apply to UK and EU nationals.

Applicants should submit via email to Professor Steven Jones, s.jones7 at lancaster.ac.uk<mailto:s.jones7 at lancaster.ac.uk>: CV (max 2 A4 sides), including details of two academic references A cover letter outlining their qualifications and interest in the studentship (max 2 A4 sides)


Dr. Paul Rayson Director of UCREL and Reader in Natural Language Processing Director of Studies (UG) Group Lead (Data Science) School of Computing and Communications, InfoLab21, Lancaster University, Lancaster, LA1 4WA, UK. Web: http://www.lancaster.ac.uk/staff/rayson/ Tel: +44 1524 510357 Fax: +44 1524 510492

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