The role of inequalities in managing symptoms of menstruation: harnessing shopping data to innovate female reproductive health research


   Bristol Medical School

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  Dr Anya Skatova, Dr G Sharp, Dr A Fraser, Dr L Howe, Dr Anna Powell, Dr Mai Stafford  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

This is an exciting opportunity for individuals who wish to develop a career in health data science research. Digital Footprints Lab at the University of Bristol is advertising a 4-year funded PhD studentship to start in early October 2023. Applicants must have a first degree in a quantitative discipline relevant to data, behavioural or health science and will be expected to complete a PhD during the four-year award period. This studentship is currently available on full-time basis but candidates wishing to study part-time are welcome to reach out to discuss options.

We are committed to a supportive, inclusive, caring, and positive community. We warmly welcome applications from people with disability and those of different cultures, genders, ages, ethnicities, and beliefs.

Background

This scholarship is part-funded by The Health Foundation. The award is leveraged by the Department of Population Health Science at the Bristol Medical School, University of Bristol, and the student will have access to all training available to postgraduate students at the Bristol Medical School (e.g., short courses at BMS: https://www.bristol.ac.uk/medical-school/study/short-courses/) and the University of Bristol (e.g., through Bristol Doctoral College: http://www.bristol.ac.uk/doctoral-college/).

Project outline:

Menstruation affects 50% of the population yet its patterns (e.g., heaviness of periods, experience of pain) are largely understudied. There is evidence that heavy menstrual bleeding can be a vital sign or risk factor of other health issues. In this PhD project, we aim to evaluate the utility and acceptability of using a novel health data source - shopping history data - to study how individuals manage menstruation symptoms such as pain, intensity of flow, mental health and other issues, and explore potential social inequalities in these management strategies.

This predominantly quantitative, data intensive project will explore shopping history data combined with survey responses and evaluate its potential and utility in female reproductive health research. In addition to quantitative approaches, the project will also use a small amount of qualitative data to study public attitudes to and acceptability of using shopping data for reproductive health research, as well as engage with general public members to guide research questions and interpretations of the patterns in the data. This will be achieved through:

  1. Exploring relevant product data available in UK supermarkets and health stores, i.e., identifying products and patterns of purchasing products that may be relevant to the management of menstrual symptoms and a variety of associated behaviours. For example, purchases of contraception, remedies for pain or mood management, snacks and other products that may be purchased in relation the menstrual cycle; accessing and conducting exploratory descriptive analyses; summarising granularity and missingness;
  2. Trialling the use of these data sets in addressing questions relevant to the management of menstruation i.e., is there escalation of pain symptoms over time? Do people in different areas of the country with differing levels of deprivation demonstrate different patterns of managing menstruation and its symptoms? 
  3. Understanding women's attitudes about the use of shopping data to study their health, as well as what research questions in this area they think are important to study: discussing the use of these datasets with women in focus groups and through online surveys;
  4. Exploring sources of error in shopping data when studying management of menstrual symptoms e.g., who shops in the specific outlet, who has a loyalty card, whether individuals buy specific products elsewhere, etc.

Supervisors:

Dr Anya Skatova ([Email Address Removed]), Dr Gemma Sharp ([Email Address Removed]), Prof Abigail Fraser ([Email Address Removed]), Prof Laura Howe ([Email Address Removed]), Dr Anna Powell ([Email Address Removed]), Dr Mai Stafford ([Email Address Removed]).

University of Bristol

The University of Bristol (UoB) ranks in the top-100 of universities worldwide and the PhD student would be registered in the Faculty of Health Sciences (http://www.bristol.ac.uk/health-sciences/) which provides ‘research excellence at every scale, from cellular mechanisms to health service provision’. This PhD will be affiliated to the MRC Integrative Epidemiology Unit (IEU) at the University of Bristol. The IEU is a world-class research centre in the field of integrative epidemiology. It brings together an innovative collection of research programmes and cross-cutting themes that will collectively fuel a step-change in analysis of causes of disease. This environment will facilitate the PhD student’s multidisciplinary project, which combines methods and ideas from epidemiology, statistics and data science applied to health.

Eligibility criteria

We strongly encourage applications from a range of disciplines (e.g., statistics, computer science, life or natural sciences, psychology, social sciences, epidemiology, or other related quantitative disciplines). Your application will be assessed using the following criteria as part of the application shortlisting process:

  • A first or upper second-class UK honours degree, or the equivalent qualifications gained outside the UK, in an appropriate subject
  • Previous research experience or formal training (e.g. a Master’s degree) is preferable but not essential 
  • Desirable to have good knowledge of statistics and/or advanced data analytics techniques
  • Desirable to be able to program analysis (e.g., in R or/and Python)
  • Evidence of ability for and commitment to a research career in health 
  • Excellent written and verbal communication skills
  • Desirable to have interest in research to improve population health and reduce health inequalities

How to apply

Apply online. Select “Population Health Sciences” PhD programme and state in the application that you are applying for funding from The Health Foundation. The application will prompt you to upload a research proposal - please skip this section.

Please provide a personal statement, two academic referees and a two-page CV. Advice on personal statements can be found in the Admissions Statement.

Closing Date: 5pm Friday 18th August 2023.

Interviews: Late Aug/Sept

Enquiries

Questions about the project should be directed to Dr Anya Skatova ([Email Address Removed]). 

Please direct general enquiries to: [Email Address Removed] 


Computer Science (8) Mathematics (25) Medicine (26) Psychology (31)

Funding Notes

UK fees (UKRI rate); students with overseas status are welcome to apply but will need to fund the remainder of their fees and any visa requirements from alternative sources.
Annual tax-free stipend at UKRI for 2023/24 is £18,622 plus training grant.

Where will I study?