AI-driven mental health decision support linked to clinician resilience and preparedness.

Objectives: Mental health services are facing unprecedented demand, placing significant pressure on clinicians to conduct timely and effective patient assessments. Rising staff turnover and burnout threatens service quality across many countries. This study examined whether providing clinical information, collected via an artificial intelligence (AI)-enabled decision support tool for mental health assessments in the UK's National Health Service (NHS), was associated with differences in clinician wellbeing and patient assessment performance. Method: In this observational study, we surveyed mental health clinicians ( Results: Relative to traditional methods, assessments supported by information provided by the AI tool were associated with significantly higher clinician wellbeing and task performance, and significantly lower cognitive load, irrespective of the clinician's experience. These associations were magnified by workload. Conclusion: These findings provide preliminary evidence that AI-powered pre-assessment tools may be associated with differences in clinician experience including higher wellbeing, higher task performance, and lower cognitive burden. By targeting systemic drivers of burnout, such tools may represent a potentially scalable approach to support workforce sustainability and service quality in mental health care.