Real world testing of AI mental health app
Testing of artificial intelligence-enabled app Wysa used to support patients with mental health concerns
Unmet need for additional patient support
Mental health conditions place a large burden on individuals, healthcare systems, and the economy. This burden has been exacerbated by the COVID-19 pandemic, which has seen an increase in both demand for mental health services and in wait times to access them. This unmet need is a serious concern, because mental health conditions can have wide ranging negative impacts on individuals’ lives and well-being.
Over a million people are referred to UK mental health services each year but just over half are provided with one session of workbook-based support. Few other free services are available, so people may have to wait over 12 weeks to receive treatment or support for their mental health conditions. As this 12-week wait often occurs after a period of hesitancy about whether to seek treatment at all, it can be a stressful time that risks worsening their mental health.
Wysa address this need via its AI chatbox app
Early intervention during this critical period may be the key to reducing the burden of mental health concerns on the health care system. Artificial intelligence and digital interventions present an opportunity to improve the efficiency of care and provide people with mental health support during this waiting period.
This research project examined the use of the digital health app Wysa on patients’ symptoms of anxiety and depression during the referral process for standard UK mental health services. Funding for this project came from a £36 million boost from central government for AI technologies to transform NHS care.
Wysa is a digital health app that uses an artificial intelligence (AI) chatbot and a series of self-care exercises to provide mental health support. The app provides exercises to help people manage their mental health and improve their resilience based on clinically-reviewed cognitive-behavioural techniques.
Early intervention during this critical period may be the key to reducing the burden of mental health concerns on the health care system. Artificial intelligence and digital interventions present an opportunity to improve the efficiency of care and provide people with mental health support during this waiting period.
This research project examined the use of the digital health app Wysa on patients’ symptoms of anxiety and depression during the referral process for standard UK mental health services. Funding for this project came from a £36 million boost from central government for AI technologies to transform NHS care.
Wysa is a digital health app that uses an artificial intelligence (AI) chatbot and a series of self-care exercises to provide mental health support. The app provides exercises to help people manage their mental health and improve their resilience based on clinically-reviewed cognitive-behavioural techniques.
Evaluation
The project evaluated the impact that access to the Wysa app has on anxiety and depression and its cost effectiveness in patients waiting for mental health treatment.
Randomly selected participants were given access to Wysa at the point of referral and were encouraged to explore the self-support tools. Participants were able to monitor their levels of anxiety and depression using questionnaires provided through the app. The results were compared with a control group of people who were on the waiting list but not using Wysa.
The project evaluated the impact that access to the Wysa app has on anxiety and depression and its cost effectiveness in patients waiting for mental health treatment.
Randomly selected participants were given access to Wysa at the point of referral and were encouraged to explore the self-support tools. Participants were able to monitor their levels of anxiety and depression using questionnaires provided through the app. The results were compared with a control group of people who were on the waiting list but not using Wysa.
Contribution to knowledge
The aims of this project support the NHS Long Term Plan’s efforts to promote digitally-enabled care, improve access to mental health support, and reduce wait times. Timely support provision and early identification of deteriorating mental health could enable earlier interventions for those who need it and improve service efficiency.
This project was funded by an Artificial Intelligence in Health and Care Award (part of the NHS Artificial Intelligence Lab managed by the Accelerated Access Collaborative in partnership with NHSX and the National Institute for Health and Care Research (NIHR) and was evaluated by Dr Edward Meinert and his team at the University's Centre for Health Technology.
The aims of this project support the NHS Long Term Plan’s efforts to promote digitally-enabled care, improve access to mental health support, and reduce wait times. Timely support provision and early identification of deteriorating mental health could enable earlier interventions for those who need it and improve service efficiency.
This project was funded by an Artificial Intelligence in Health and Care Award (part of the NHS Artificial Intelligence Lab managed by the Accelerated Access Collaborative in partnership with NHSX and the National Institute for Health and Care Research (NIHR) and was evaluated by Dr Edward Meinert and his team at the University's Centre for Health Technology.
For collaborations with the Centre for Health Technology, please contact the Co-Directors:
Professor Sheena Asthana
Professor Ray Jones MBE
Professor Shang-Ming Zhou
Professor Edward Meinert
Dr Edward Meinert is Associate Professor of eHealth at the University of Plymouth. A chartered engineer, European Engineer, a Fellow of the British Computer Society and Chartered Management Institute, Edward was previously Sir David Cooksey Fellow in Healthcare Translation at the University of Oxford.
With extensive experience in data science, his research focuses on the use of digital technology in healthcare including mobile digital apps, wearables, robotics and clinical artificial intelligence with a primary aim to enable preventive healthcare.
