AI for early detection in employee mental health

It is estimated that in the UK over 5 million workers suffer from mental health (MH) related problems. Mental health (MH) conditions cost the UK £34.9bn p/a in diagnosis and treatment, and an estimated £35bn in economic losses to the workforce. MH leaders, such as Mind, have indicated that early detection and holistic treatments would increase productivity whilst reducing pressures on society and the health service. Due to resource constraints, social taboos and often, fear and anxiety, patients are not self-identifying their symptoms early enough resulting in a "better late than never" last resort MH system. One of the leading causes of MH difficulties is work-related stress, anxiety, burn-out and unhealthy working environments. Following the impact of COVID-19 pandemic and on-going cost-of-living crisis, we can reasonably expect that social isolation will be a significant contributing factor to the rise of MH related issues within the UK population and in particular company employees. Most companies tend to use staff appraisal and internal feedback systems; however these are inadequate in identifying early onset of MH related issues.

Our vision is to use artificial intelligence (AI), in the form of machine-learning (ML) with deep learning (DL) capability, to accurately detect early symptoms of MH challenges in the workforce and connect people who need more support with the appropriate form of responsive talking therapy to reduce the number of mild cases reaching the NHS. Early detection and intervention for mild MH conditions will relieve the NHS to focus on serious mental illnesses (SMI) which require medication or inpatient care, such as schizophrenia or addiction