Promises and Challenges of AI-Enabled Mental Healthcare: A Foundational Study

Sruthi Viswanathan, Max Rollwage, Ross Harper

Keywords: Mental health, Clinician-centred, User research

TL;DR: Understanding promises and concerns for AI usage amongst mental-health clinicians

Abstract: Mental health and behavioural problems are the primary drivers of disability worldwide. Further escalated by the COVID-19 pandemic, millions across the globe are breaking traditional stigma by seeking professional support for their mental health. However, this increased demand for mental healthcare needs to be met by a limited number of services and professionals. We conducted qualitative interviews with mental health practitioners to understand the landscape of opportunities and challenges for AI-enabled mental healthcare in 2022, focussing on triage and decision support. Our findings suggest important opportunities for AI to accommodate the growing demand for mental healthcare, support clinicians’ workload, and improve data management. However, there were also major challenges identified regarding practitioner trust in AI solutions and their incorporation into the care pathway. Our findings indicate a need for coordinated training and education for mental health professionals to improve trust in AI solutions and correspondingly facilitate wider adoption of this promising technology. Moreover, a re-positioning of AI solutions as decision support tools rather than absolute decision tools might lead to improved acceptance and adoption within the clinical community. Finally, our results highlight the importance of understanding the end-user's perspective (in this case, mental health practitioners) and including them in the process of developing AI solutions in order to achieve optimal real-world impact.