PhD Studentship: Harnessing national helpline data to better understand, identify and prevent the abuse of older people

The abuse of older people is one of the most abhorrent, growing, yet under-researched problems in modern society. Among the reasons for this is the lack of reliable datasets to understand the scale, nature, causes and impacts of elder abuse (the last ONS-led national survey was in 2006). This PhD studentship aims to create a step-change in understanding the nature and scale of this abuse, by: 

1. Co-developing the principles (e.g. ethics) and methods for anonymising, processing and analysing sensitive data collected by a national charity’s 24/7 helpline for people experiencing or witnessing elder abuse. 

The Hourglass (https://www.wearehourglass.org/) helpline receives ~20,000 interactions per year, but the organisation has little capacity or staff research capability to utilise the data, e.g. for service evaluation, policy advocacy, or better understanding the contexts and causes of such abuse. The student will use advanced data science and applied statistics to enable combined analysis of different modes of contact (e.g. online chat, e-mail or telephone) and explore potential linkage to other helpline datasets (e.g. AgeUK).

In the 2nd and 3rd year of the PhD research, the data will then be used to conduct substantive analyses of important questions that are a priority for Hourglass and other organisations that safeguard older people, such as:

2. What are the signs, help-seeking pathways, and opportunities for preventing abuse by those who have Lasting Power of Attorney over others? 

3. What are the characteristics of the (alleged) perpetrators of elder abuse, and how can better knowledge of these inform more effective strategies for preventing, identifying and stopping the abuse of older people? 

While the advanced methods training of the PhD will be data science and statistical analysis, there will also be opportunities to combine this with training in and application of qualitative/mixed methods data analysis. The team of three supervisors bring nationally and internationally recognised expertise in applied health and social care research (Prof. Anderson), applied statistics and analysis of large routine datasets (Prof. Abel), and substantive knowledge of the abuse of older people and related policy issues and third sector data and advocacy (Mr Tatlow). 

The PhD scholarship would particularly suit EITHER social scientists or social policy researchers seeking to expand their skills and application of data science methods, OR data scientists/statisticians looking to expand their skills and knowledge of applied social research. The student should be prepared to spend some weeks working at Hourglass offices in other parts of the UK (e.g. Suffolk, Scotland). An existing interest in adult safeguarding or the problem of abuse would be a bonus, as is an interest in or experience of working closely with third sector organisations. 

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