News & Latest 29.05.2020

Award funding for research on unemployment and mental health issues arising from COVID -19.

A rapid and reliable assessment method for screening mental health and wellbeing in job centres in the United Kingdom: A Computerised Adaptive Testing (CAT) response to the mental health impacts of Covid19 related job-loss

The ARC East of England (EoE) Mental health over the life course theme has received an award from the University of Cambridge, to carry out research on unemployment and mental health issues arising from COVID -19. This project will focus on quickly and reliably identifying mental health and wellbeing issues among job seekers, using computerised adaptive testing (CAT). The COVID - 19 crisis is predicted to lead to mass unemployment over coming months with tremendous impacts on the mental health and wellbeing of those who find themselves out-of-work. Over the past five weeks two million people have registered as unemployed.

As a result of the outbreak of COVID-19, the Department for Work and Pensions and Job Centre Plus transferred the majority of services online. All government welfare services face considerable challenges in terms of resource capacity to deliver routine frontline services. Helping people with existing mental health issues and those arising from the Covid situation is a key government concern. Already 60% of the DWP case load suffer from mental health issues. This is set to rise with surges in unemployment over coming months.

Over the past year Drs Adam Coutts (Department of Sociology, University of Cambridge) and Jan Stochl (Dept of Psychiatry, University of Cambridge), in collaboration with Profs Jesus Perez (ARC EoE Mental Health Theme Lead) and Peter Jones (ARC EoE Director), have been developing a highly effective method using CAT for quickly and reliably measuring MH and WB among the unemployed job seekers. CAT is an innovative form of computer-based assessment applicable for screening or diagnostic in mental health. This technology uses psychometric parameters of items in combination with item responses of assessed individual to instantly identify the most informative questions and to avoid less relevant ones. With this innovation, each individual answer a small and tailored set of questions. This makes MH assessments personalised, precise, and much more efficient compared to standard paper questionnaires.

Researchers have developed more holistic and multi-dimensional measures of mental health, wellbeing and flourishing linked to cost benefit analysis but there is little understanding or appreciation as to how this information could be collected in the hurly-burly and day-to-day policy operations across a range of live policy settings and with different client groups. Routine frontline policy interventions and programmes across public services involve hundreds of thousands of service-client interactions per month and present an ideal opportunity and cost-efficient way to collect large amounts of health and wellbeing data yet this remains an underutilised and little understood approach. This is due to researchers being reliant on replicating batteries of questionnaires taken from large secondary data sets such as that of the Understanding Society and the European Social Survey. The problem is that these are not appropriate for the collection of data in routine operational and policy delivery settings where 1) there is limited time to ask questions outside of job search and 2) where research can interfere with policy delivery and the development of job seekers / work coach relationships. In addition, frontline staff such as employment and welfare advisors who are not clinically trained are usually those asked to deliver large batteries of questions that are cumbersome and intrusive for vulnerable participants to complete. Moreover, there is limited empirical evidence on their reliability or cost-effectiveness for use in such settings.

Using CAT with existing data from a major national Randomised Control Trial of a back-to-work programme (n=16,000) we have reduced large and cumbersome batteries of standardised MH and WB questions from 33 items down to an average of 5. This offers considerable cost savings, reduction of response burden and enhanced monitoring of mental health issues. This will enable better targeting and referral of newly unemployed to appropriate support services. The study team aim to use the response funding to quickly test and make further refinements to the assessment method and technological app. This will expedite the deployment of the app to meet the expected high demand for DWP and JCP services over coming months. It also offers considerable potential for the commercial development of the application.

This study is expected to take six months and will offer an ideal platform to continue developing support for jobseekers who may be suffering from mental health and wellbeing difficulties during and after the COVID-19 epidemic.

For further information about this research project, please contact Dr Adam Coutts (

You can view Dr Adam Coutts profile here.