利用机器学习检测治疗师的倦怠与 flourishing

ABSTRACT Background Burnout is pervasive among therapists and is associated with impaired well‐being and reduced clinical effectiveness. Although flourishing and character strengths may function as protective factors, intervention implementation is limited by a lack of feasible, scalable methods for monitoring therapist well‐being. Machine‐learning (ML) approaches may be suited to address these limitations. Aims This proof‐of‐concept study examined the use of a transformer‐based natural language processing (NLP) model to detect therapist burnout, flourishing, mental health continuum, employee