Studentship opportunity

Does the nature of frailty in later life vary by individual circumstances and national context?

This studentship is funded by the ESRC through the Scottish Graduate School of the Social Sciences

Institution
University of Edinburgh
Pathway
Social Work and Social Policy
Mode of study

Full time / Part time

Application deadline
12 April 2019

Project details

Frailty is an important concept capturing age-related declines in various aspects of physical condition and mental capacity. Previous research has developed measures of frailty that ‘count’ the number of age related declines in physical and mental functioning with higher counts indicating higher levels of frailty. We know that those with higher frailty scores are more likely to die early, to be admitted to a care home or to suffer a fall. Research has also shown stark inequalities in frailty among older people. For example, in England, we observe a ten-year difference in the level of frailty such that an 85 year-old in the richest wealth fifth of the population has a similar level of frailty compared to a 75 year-old in the poorest fifth of the population. What we do not know is whether the nature of frailty is the same among these two groups. Do we see similar patterns of age-related declines in physical condition and mental capacity and wellbeing for the rich and the poor? Or do the differences in levels of frailty come with different sets of underlying conditions? It is these questions that this PhD addresses testing whether the specific underlying conditions of frailty vary according to wealth, age, gender or the country a person lives in. Understanding of the nature of frailty in later life better enables us to care for an ageing population and develop strategies to deal with the stark inequalities observed in frailty and by extension life expectancy.

The project will use the English Longitudinal Study of Ageing and its partner studies in other countries to assess whether the patterns of age-related physiological and cognitive declines used within survey measure of frailty, vary across national contexts and within England according to individual characteristics/circumstances. The studentship is part of the Advanced Quantitative Methods steer and views frailty as a latent construct which is potentially complex and multidimensional and uses Bayesian Item Response models to analyse this complex structure in different population groups and national settings.

About the institution

This PhD project will sit within the School of Social and Political Science in the Social Policy subject area and is embedded within Edinburgh Q-Step Centre. Q-Step is a £19.5 million programme designed to promote a step-change in quantitative social science training. Q-Step was developed as a strategic response to the shortage of quantitatively-skilled social science graduates in the UK. It is funded by the Nuffield Foundation, the Economic and Social Research Council (ESRC) and the Higher Education Funding Council for England (HEFCE). For more information go to www.nuffieldfoundation.org/q-step. Edinburgh Q-Step centre contains one of the largest collections of quantitative social scientists in the UK involved in a range of substantive and methodological research involving social statistics. The PhD will be jointly supervised by Dr Alan Marshall (Social Policy) and Dr Ugur Ozdemir (Politics and International Relations), both Q-Step staff.   Depending on prior experience, the student would be encouraged to complete the following PG courses in their MSc year: Core Quantitative Data Analysis; Intermediate Inferential Statistics; Statistical Modelling in the Social Sciences, Researching Contemporary Britain Using Longitudinal data; Research Design. Q-Step runs a seminar series which brings together our community of students and staff involved in QM research, where all PG students are encouraged to attend and present. AQMeN, now based in the School of Social and Political Science, also offers relevant training, as do other UK Quantitative Methods hubs, and the successful candidate could enrol on condensed courses on, for example, Missing Data Imputation and Joint Models, Sequence Analysis and Latent Class Analysis if necessary.

Eligibility

Applicants must meet the following eligibility criteria
  • A good first degree (at least 2:1), preferably with both social science and social statistics components
  • Demonstrate an interest in, and knowledge of issues around ageing including inequalities in experiences of later life
  • Have a good grounding in multivariate statistical analysis including generalized linear models and techniques to uncover structure in latent constructs such as frailty
  • Experience of analyzing surveys with complex designs
  • Competent in the handling of large datasets using statistical software such as Stata, R, SPSS or similar

Students must meet ESRC eligibility criteria. ESRC eligibility information can be found here.

Award details

The scholarship is available as a +3 or a 1+3 programme depending on prior research training.  This will be assessed as part of the recruitment process.  The programme will commence in September 2019. An annual maintenance grant at the RCUK rate (2019/20 rate £15,009 full-time) and also includes
  • fees at the standard Home rate
  • possibility to draw on a pooled Research Training Support Grant, usually up to a maximum of £750 per year

Other information

Knowledge exchange: The student will be encouraged to disseminate the results of this PhD project widely to both academic and non-academic audiences such as policy makers and practitioners as well as lay audiences.

How to apply

  1. Applicants register on GradHub and fill out data (this is a requirement of the application process)
  2. Applicants complete and upload the prescribed list of required documentation to include:
  • Application form (download from button above)
  • Academic transcripts
  • References
  • CV
  • A covering letter (1 side) in which you address the questions of i. what attracts you to the project? ii. what do you see as the key challenges of this PhD? ii. How would you overcome the challenges you identify? This letter should be uploaded in a standalone document with a naming convention as follows

*name/supervisor/institution/competition/date*

  1. Applicants submit application through GradHub (button below)

 

Selection process

Applications will be ranked by a selection panel and applicants will be notified if they have been shortlisted for interview by 19th April. Interviews will take place on 30th April. All scholarship awards are subject to candidates successfully securing admission to a PhD programme within The University of Edinburgh. Successful scholarship applicants will be invited to apply for admission to the relevant PhD programme after they are selected for funding.

Supervisor/Contact details

Name
Alan Marshall
Email
Alan.marshall@ed.ac.uk