Professor Sinead Brophy
Professor (CIPHER)
Biomedical Sciences
Telephone: (01792) 602058
Room: Cellular Office - 205
Second Floor
Data Science Building
Singleton Campus

Publications

  1. Cooksey, R., Brophy, S., Kennedy, J., Gutierrez, F., Pickles, T., Davies, R., Piguet, V., & Choy, E. Cardiovascular risk factors predicting cardiac events are different in patients with rheumatoid arthritis, psoriatic arthritis and psoriasis. Seminars in Arthritis and Rheumatism, 48
  2. Brophy, S., Kennedy, J., Fernandez-Gutierrez, F., John, A., Potter, R., Linehan, C., & Kerr, M. Characteristics of Children Prescribed Antipsychotics: Analysis of Routinely Collected Data. Journal of Child and Adolescent Psychopharmacology, 28(3), 1-12.
  3. James, M., Christian, D., Scott, S., Todd, C., Stratton, G., Demmler, J., McCoubrey, S., Halcox, J., Audrey, S., Ellins, L., & Brophy, S. Active Children Through Individual Vouchers Evaluation: A Mixed-Method RCT. American Journal of Preventive Medicine, 58(2), 232-243.
  4. Bandyopadhyay, A., Tingay, K., Akbari, A., Griffiths, L., Bedford, H., Cortina-Borja, M., Walton, S., Dezateux, C., Lyons, R., & Brophy, S. Behavioural difficulties in early childhood and risk of adolescent injury. Archives of Disease in Childhood, archdischild-2019.
  5. James, M., Christian, D., Scott, S., Todd, C., Stratton, G., Demmler, J., McCoubrey, S., Halcox, J., Audrey, S., Ellins, L., & Brophy, S. Predictors of cardiovascular health in teenagers (aged 13–14 years): a cross-sectional study linked with routine data. Open Heart, 6(2), e001147

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Teaching

  • PM-274 Practical Epidemiology

    This module explores the underlying concepts that are used to evaluate population health. How to design a study, measuring frequency and rate of diseases, how tell what the risk factors are for getting a disease, how to critically appraise research, and understanding the limitations of research including bias, reverse causality and confounding. The module will use the current work with Public Health Wales, Welsh Government and Charities and show how their programmes are evaluated using epidemiology design and analysis. The data used in workshops will come directly from our research working in primary schools, arthritis and with the Growing up in Wales study. This course provides hands on experience and training in understanding and measuring population health, and is delivered by practicing researchers in the National Centre for Population Health and Well-being.

  • PM-344 Capstone Project

    The aim of this module is to provide a capstone experience to students¿ learning, through participating in their own enquiry-based research project. The project may be laboratory or non-laboratory based, but it will always involve a research question that is drawn from the literature, and focused on a topic relevant to medical science. It will ask a novel research question and involve the critical analysis of research findings. Students will refine their oral and written communication skills to a graduate level through creating an introductory presentation on the project background, and a written dissertation and oral presentation on their research conclusions.

  • PM-367 Practical Epidemiology for Population Health Measurement

    This module explores the underlying concepts that are used to evaluate population health. How to design a study, measuring frequency and rate of diseases, how tell what the risk factors are for getting a disease, how to critically appraise research, and understanding the limitations of research including bias, reverse causality and confounding. The module will use the current work with Public Health Wales, Welsh Government and Charities and show how their programmes are evaluated using epidemiology design and analysis. The data used in workshops will come directly from our research working in primary schools, arthritis and with the Growing up in Wales study. This course provides hands on experience and training in understanding and measuring population health, and is delivered by practicing researchers in the National Centre for Population Health and Well-being.

  • PMIM02 Health Data Modelling

    Health data scientists are expected to work with diverse data sources. Modelling data encompasses setting up database models and analysing the data using statistical models. The objective of this module is to raise the awareness of students about the various processes of data modelling and the key operations involved in the data processing of large and diverse datasets. Module leader is Dr Joanne Demmler

  • PMIM102 Scientific Computing and Health Care

    The module aims to raise the awareness of students about scientific computing in the field of health data science. It focuses on basic software development workflows, tools, and skills that health data scientists most often employ. Students will also learn about the professional context within which health data scientists operate. This is a core / compulsory module and worth 20 Masters level credits.

  • PMIM202 Health Data Modelling

    Health data scientists are expected to work with diverse data sources. Modelling data encompasses setting up database models and analysing the data using statistical models. The objective of this module is to raise the awareness of students about the various processes of data modelling and the key operations involved in the data processing of large and diverse datasets. This is a core / compulsory module and worth 20 Masters level credits.

  • PMIM202J Health Data Modelling

    Health data scientists are expected to work with diverse data sources. Modelling data encompasses setting up database models and analysing the data using statistical models. The objective of this module is to raise the awareness of students about the various processes of data modelling and the key operations involved in the data processing of large and diverse datasets. This is a core / compulsory module and worth 20 Masters level credits.

  • PMIM301 Using Secondary Health Data

    Students will study data quality and management, secondary uses of clinical data, service improvement and clinical audit. Academic skills are developed and enhanced by an introduction to quantitative research methodologies. Students will be introduced to statistical software such as SPSS.

Supervision

  • TBC (current)

    PhD
    Other supervisor: Prof Gareth Stratton
  • Exploring the Potential Use of Telehealth to Improve the Diagnostic Process of Autism Spectrum Disorder in Wales, UK.«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /» (current)

    PhD
    Other supervisor: Dr Jodie Croxall
  • Stories of autistic students lived experiences transitioning throughout education: A Narrative Analysis (current)

    PhD
    Other supervisor: Dr Claire Vogan Mccabe
  • ACTIVE CHILDREN THROUGH INDIVIDUAL VOUCHERS – EVALUATION (ACTIVE): A MIXED METHOD RANDOMISED CONTROL TRIAL TO IMPROVE THE CARDIOVASCULAR FITNESS AND HEALTH OF TEENAGERS (current)

    PhD
    Other supervisor: Prof Damon Berridge
    Other supervisor: Dr Richard Fry
  • Repeatable and reusable research - Exploring the needs of users for a Data Portal for Disease Phenotyping (current)

    PhD
    Other supervisor: Dr Jodie Croxall
  • Mining free-text clinical notes for early prediction of the progression and recurrence of colorectal cancer. (current)

    PhD
    Other supervisor: Prof Ronan Lyons
  • An Assessment of Machine Learning and Geographical Profiling Techniques to Identify Vulnerable Families Through Health and Socioeconomic Data in Wales. (current)

    MSc
    Other supervisor: Prof Alan Watkins
  • HAPPEN: The Health and Attainment of Pupils in a Primary Education Network (awarded 2020)

    PhD
    Other supervisor: Prof Ronan Lyons
  • 'Population based ankylosing spondylitis electronic cohort' (awarded 2017)

    PhD