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ESRC CASE PhD Studentship: Understanding how people living with bipolar disorder talk about risk on social media

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  • Full or part time
    Prof S Jones
    Prof F Lobban
    Dr Paul Rayson
    Dr Jasper Palmier-Claus
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (UK Students Only)
    Funded PhD Project (UK Students Only)

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 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

Applicants should submit via email to Professor Steve Jones, [Email Address Removed]:

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)

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FTE Category A staff submitted: 64.40

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