Population and Behavioural Science Research Division
Research at the University of St Andrews School of Medicine
A core concept emerging from scientific advances over the past decade is that dependence or addiction is fundamentally a chronic relapsing brain condition that develops over time as a result of a combination of pre-morbid vulnerabilities and chronic use of psychoactive substances.
The consequence to some is an uncontrollable, compulsive-like dysfunctional behaviour that will severely impact on the individual’s day-to-day existence within one’s own immediate family and surrounding community. Understanding resilience is not to eliminate stress or erase life’s difficulties. Instead, it gives people the strength to tackle problems, overcome adversity and move on with their lives.
Addiction medicine research is a cross cutting speciality that involves the acquisition of skills to undertake biological (e.g neurocognitive and other domains of behavioural and imaging related neuroscience), clinical (e.g. cardiovascular, infections, respiratory pathologies and other multiple morbidities), behavioural (e.g. fatal and non fatal overdose, injecting, codependencies, criminal activities) social (e.g. homelessness) and policy (e.g. global health) related activities.
This will create opportunities to utilise innovative and traditional methodologies to help understand mechanisms better and ultimately improve the outcomes, compliance, predictions and quality of life of the dependent populations. This might include the use of informatics through linked datasets, clinical trials, qualitative, quantitative and anthropological research processes, profiling through epidemiological and clinical studies, predictions through machine learning, among many others.
Projects of Interest
DigitAS – We conduct research around the development and implementation of innovative digital solutions to meet the needs of people facing addiction. We do this by creating a network of shared knowledge and we are committed to a design philosophy based on person centredness, visual and inclusive communication, collaboration, co-creation and continuous improvement.
EleCtra – Developing a Learning Health System for NHS Fife.
Health data research
Health data research is a term used to describe a subject that combines maths, statistics and technology. It tries to answer different types of health problems by using statistical and machine learning techniques to explore large medical datasets. Modern healthcare generates large amounts of data as most contacts we have with healthcare is recorded.
More about Health data research
Why is health data science important?
Making sense of the large amounts of data we produce can provide earlier insights to diseases and health conditions. Using tools and methods, data can be turned into useful information that can be analysed to detect patterns which help clinicians offer patients the best care. For example, data on individual patients can be combined and analysed in order to learn more about how conditions develop in populations, and who is more likely to develop these. Analysing data can help us learn more about causes and symptoms so that we can learn to spot diseases and conditions earlier and plan how best to manage the care of patients.
Where does the health data come from?
The data used by health data scientists comes from many sources and can also come in a variety of formats, such as text, numeric and images. Sources include:
- Health care records on primary care and hospital attendance, such as doctors’ records — both notes and codes— prescriptions and social care provision, records of hospital admission and A & E visits
- Mobile phone applications, smart watches and other tracker devices that collect information on heart rate, physical activity, sleep, age and menstrual cycle.
Who has access to health data?
The ethical and legal responsibility of using data is closely controlled in the UK, each project is assessed by the relevant governing body and data is provided in an anonymous format in order to protect patient confidentiality. Health Data Research UK suggested best practice is that access to data is given for a specific use and provided through a data safe haven. A data safe haven is a platform that holds electronic records in a secure environment, providing restricted access in a de-identifiable format for analysis to enable research.
Who are the data scientists?
Data scientists come from a broad range of disciplines such as: Computer Science, Mathematics, Statistics, Biomedical Science, Physical Science and Social Science. Multidisciplinary teams work particularly well in health data research, as each expert, brings a different perspective and approach to how they interpret the research. Through sharing their thoughts, opinions and expertise, better results can be achieved.
What are some of our current research interests?
Health Data Research UK enhance our research through their funding, support and endeavours to combine health data from across the UK through their national implementation projects.
Multimorbidity resource — defined as two or more long-term conditions — identifying which conditions are commonly found together, how these develop with age and what challenges are faced by these people and the health services that are supporting them.
Projects of Interest
Multimorbidity Resource Project – Multimorbidity is defined as two, or more, existing conditions which may affect health outcomes.
MuM-Predict – Developing research to study and improve maternity care for pregnant women who are managing two or more long-term health conditions.
EleCtra – Developing a Learning Health System for NHS Fife.
The Health Psychology group focuses on the determinants of health behaviour such as smoking tobacco, physical exercise, sugar snack intake, use of drugs and alcohol consumption. We investigate fundamental individual factors that influence the instigation and maintenance of these behaviours and develop innovative interventions using different techniques. We are interested in the mechanisms of how messages are conveyed in clinical and non-clinic settings. We are a multi-disciplinary group with a wide variety of research methodologies being utilised including attention to measurement issues and use of new technology.
Projects of Interest
CAREER Project – The CAREER project is a longitudinal research study seeking to understand how the COVID-19 pandemic is affecting the anxiety, feelings of uncertainty and preparedness for practice of early career dental health professionals.
FORECAST2 – An Experience-Based Co-Design process with breast cancer patients and radiographers that led to the development of communication skills training for the radiotherapy service: ‘KEW’, for Know (Confidence, Expectations, Person), Encourage (Emotions, Space, Follow-Up) and Warmth (Start, Normalize, Ending).
COBELT Co-Design – Using co-design strategies to ensure that a future lung cancer screening service with a biomarker blood test is designed around the needs of those who could benefit most, and potential service providers.
COVID-19 Messages – Co-creation of communication to support vulnerable groups who are at increased risk from the effects of the COVID-19 pandemic. Collaboration with NHS Fife, Fife Council and Fife Voluntary Action.
EAGLE – Development of Connection Pathways from Primary Care to Golf Packages. The EAGLE project will develop connection pathways from primary care to golf packages for non-golfers and returning golfers to increase physical activity and improve physical and mental health and wellbeing. We are working with GP practices, primary care patients and golf clubs in Fife to co-design acceptable, feasible and engaging referral pathways
The Primary Care and Populations Research team is dedicated to improving the way healthcare is delivered to individuals and the community at local, national and global levels. We work as a multi-disciplinary team, collaborating with other schools in the university, including Computer Science, Psychology, Geography, and Mathematics and Statistics, focusing on incorporating cutting-edge analytical tools and methodologies in to Health Data Research:
- Clinical trials and complex interventions
- Health Informatics – Record-linkage of electronic health records to aid decision support, machine learning methods for clinical prediction rules.
- Health Services Research
- Systematic reviews and meta-analysis
- Antimicrobial stewardship in primary care and infectious disease epidemiology
The Primary Care and Populations Research department is also part of the Scottish School of Primary Care. Since its inception in 2000, the SSPC has been responsible for high quality research and for bringing new research funding into Scottish universities. http://www.sspc.ac.uk/about_us/
The World Health Organization reports that 71% of deaths (41 million people) around the world each year are due to non-communicable diseases. The major risk factors for non-communicable diseases such as tobacco use, physical inactivity, the harmful use of alcohol and unhealthy diets are often initiated in early life or adolescence. Adolescence is also a time when half of all mental health conditions develop, affecting up to 1 in 5 adolescents globally. Consequently, it has been proposed that in order to improve the health of the public we need to develop cultures and environments in which the healthy choice is the easiest choice, throughout the life course (the fifth wave of public health).
It is in this context in which the Societal and Behavioural Public Health group undertake research with the ambition of improving the health of individuals, communities and populations. We focus primarily on adolescents and young people, with a life course social epidemiological approach. We collect and analyse data on health and wellbeing locally, nationally and internationally to understand health disparities and undertake evaluations of public health interventions into complex social systems to inform practice and policy. Our research is multidisciplinary and co-produced with relevant stakeholders and publics. We place special emphasis on capacity building both in teaching and supervision, and also through working with schools and communities to empower people to use data for the public good.