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

Publications

  1. Todd, C., Cooksey, R., Davies, H., McRobbie, C., & Brophy, S. Mixed-methods evaluation comparing the impact of two different mindfulness approaches on stress, anxiety and depression in school teachers. BMJ Open, 9(7), e025686
  2. Brophy, S. & John, A. Authors’ reply. The British Journal of Psychiatry, 214(2), 113-114.
  3. Marchant, E., Todd, C., Cooksey, R., Dredge, S., Jones, H., Reynolds, D., Stratton, G., Dwyer, R., Lyons, R., & Brophy, S.
  4. Dennis, M., Shine, L., John, A., Marchant, A., McGregor, J., Lyons, R., Brophy, S., & Brophy, S. Correction to: Risk of Adverse Outcomes for Older People with Dementia Prescribed Antipsychotic Medication: A Population Based e-Cohort Study. Neurology and Therapy
    http://europepmc.org/abstract/med/29524109
  5. Rahman, M., Todd, C., John, A., Tan, J., Kerr, M., Potter, R., Kennedy, J., Rice, F., & Brophy, S. School achievement as a predictor of depression and self-harm in adolescence: linked education and health record study. The British Journal of Psychiatry, 212(4), 215-221.

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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.

  • PMIM102J 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

  • Possibly, we will pull the detail together over the coming months and then adjust the thesis title accordingly (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 /» (current)

    PhD
    Other supervisor: Dr Jodie Croxall
  • The Effectiveness of Individual Vulnerability Profiling Tools Versus the Flying Start Programme in Rhonnda Cynon Taff to Target Early Support Pregnant Women, Children and Families (current)

    MSc
    Other supervisor: Prof Alan Watkins
  • ‘The lived experiences of Autistic Individuals transitioning throughout education: A Narrative analysis’. (current)

    PhD
    Other supervisor: Dr Claire Vogan Mccabe
  • HAPPEN: The Health and Attainment of Pupils in a Primary Education Network (current)

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

    PhD