RELEASE – Research Project Update

By Janine Aitken, studying MSc Big Data, University of Stirling

With over 20 years of experience in health, social care, and statutory services, I have supported individuals facing mental health and substance use challenges. When I sought a career change, it was essential for me to continue applying the skills and knowledge I have gained. This led me to take on a volunteer role with the Salvation Army Centre for Addiction Services and Research at the University of Stirling. I am thrilled to support the RELEASE team while applying what I am learning in my MSc in Big Data.

RELEASE, funded in 2022 by the Chief Scientist Office, is led by Dr Connell and Professor Hunt at the University of Stirling. As the project nears completion, its focus has been on understanding how individuals access health services for mental health and substance use following their release from prison. Research shows that people released from prison in Scotland face a higher risk of suicide, overdose, and illness linked to mental health and substance use, suggesting that people may not be accessing effective community-based support, early enough.

This certainly reflects my own professional experience, supporting people within addiction services and homelessness.  Often people leaving prison do so with no support and feel a reluctance to access services.  This can be attributed to the stigma and poor treatment they have experienced in the past or feeling anxious about speaking on issues they are struggling with due to a fear of judgement.  Another issue they may face is having no way to contact or refer themselves to services, due to not having access to the appropriate technology (mobile phone, Wi-Fi etc.) or simply having no information on how or where to access services.  People often leave health and mental health issues until they reach crisis and require a more advanced level of support including emergency services.  This study will provide valuable insights and a greater understanding of how and when people access support (or don’t), which will assist in highlighting areas for improvement in terms of service access and support pathways.

Often people leaving prison do so with no support and feel a reluctance to access services. 

This study compares health service use for mental health and substance use between individuals released from Scottish prisons and the general population, using national Scottish data. It is a retrospective cohort study analysing data from 8,917 individuals released in 2015 and 42,455 matched controls (individuals) from the general population. By linking data from the Scottish Prison Service, health services, and death registrations, the study explores service use and will use Poisson regression models for further analysis. The findings aim to better understand disparities in service access and inform interventions that improve access for individuals released from prison, ultimately addressing inequalities, and enhancing public health in Scotland.

The RELEASE Study benefits from a large quantity of data – often referred to as ‘Big Data, and as I reflect on my own learning so far, and as I consider the size of the RELEASE data set, I see the potential for applying ‘Big Data’ approaches to future projects.  The use of big data exemplifies how this approach can drive more effective decision making in terms of research and interventions. Big data enhances research by enabling deeper insights, improved accuracy, and faster decision-making. It allows researchers to analyse large datasets, identify patterns, create predictive models, and conduct personalized studies, particularly in healthcare and environmental science. It fosters cross-disciplinary collaboration, automates processes like data cleaning, and supports long-term studies. Additionally, big data helps explore unstructured data, simulate complex systems, and share data globally, accelerating scientific progress and improving access to actionable insights.

We know that data analysis has been transformed with the introduction of new technologies, such as machine learning.  Machine learning is a subset of Artificial Intelligence that utilises algorithms to break down large data sets (to analyse, identify patterns and then build mathematical models based on those patterns).  It has been used to automate data analytics and unlike more traditional types of computer programming, machine learning entails feeding a computer a vast amount of data, where it will then look for patterns and learn from those patterns.  Machine learning is useful in analysing large and complex data sets.  By highlighting trends in historical data, this in turn leads to predictive decision making.  Machine learning can then segment data into groups based on patterns, which would enable a more personalised approach.  Further research would benefit from using this technology to look for patterns within the data and to make future predictions, as well as providing deeper insights that would provide a more personalised approach in addressing some of the challenges faced by people leaving prison.   Machine learning can also be used to aid in communicating research findings with data visualisation techniques and data storytelling, to enhance interaction and understanding of complex information.

RELEASE has emphasised meaningful involvement of people with lived justice experience in the research process. I look forward to sharing more about this approach in a future blog.

Picture ©University of Stirling, credit Linda McGowan