Helping Samaritans better understand and meet the needs of callers
The school of psychology and computing have joined forces to understand the impact that the pandemic is having on a major support helpline
The effect the pandemic is having on our mental health and wellbeing are all too well known; however, the pressure it is placing on our frontline support services are not. The school of psychology and computing have joined forces to utilise data science in an attempt to understand the impacts that the pandemic is having on us all - reflected in how people are reaching out to samaritans, a major support helpline.
Focus of the study
The ongoing partnership aims to understand the effects COVID-19 is having on call volume and duration to build a more profound understanding of how people use the service. The pandemic has led to more distressed people having longer calls, at different times from before the crisis, pointing to the all too real effects that isolation and the crisis are having on our health and mental wellbeing.
Isolation, social distancing and the removal of many existing mental health support systems, has meant that many of us have never felt so alone. It is vital to provide empirical evidence and analysis to support frontline providers like samaritans, empowering them to adapt and evolve and meet the needs of callers as the crisis unfolds.
The ongoing work is using anonymous data on a daily basis, offering immediate effect and shedding light on the experience for callers. The work continues, ensuring that even amidst the pandemic, callers can still receive compassionate, confidential support.
Professor Siobhan O'Neill discusses using data to meet the needs of callers
Professor of Mental Health Sciences
School of Psychology
Areas of expertise Mental health and wellbeing, trauma, suicidal behaviour.
Professor of Computer Science
School of Computing
Areas of expertise Computing and mental health, artificial intelligence, digital wellbeing, innovation and assistive technologies, human-computer interaction, data mining.
Reader in Data Analytics
School of Computing
Areas of expertise Digital health, biomedical and healthcare informatics, human-computer interaction, data modelling.