Machine Learning in Clinical Psychology and Psychotherapy Education: A Survey of Postgraduate Students at a Swiss University

Abstract

BackgroundThere is increasing use of for machine learning-enabled tools (e.g., psychotherapy apps) in mental health care.ObjectiveThis study aimed to explore postgraduate clinical psychology and psychotherapy students’ familiarity and formal exposure to topics related to artificial intelligence and machine learning (AI/ML) during their studies.MethodsIn April-June 2020, we conducted a mixed-methods web-based survey using a convenience sample of 120 clinical psychology and psychotherapy enrolled in a two-year Masters’ program students at a Swiss university.ResultsIn total 37 students responded (response rate: 37/120, 31%). Among the respondents, 73% (n=27) intended to enter a mental health profession. Among the students 97% reported that they had heard of the term ‘machine learning,’ and 78% reported that they were familiar with the concept of ‘big data analytics’. Students estimated 18.61/3600 hours, or 0.52% of their program would be spent on AI/ML education. Around half (46%) reported that they intended to learn about AI/ML as it pertained to mental health care. On 5-point Likert scale, students moderately agreed (median=4) that AI/M should be part of clinical psychology/psychotherapy education.ConclusionsEducation programs in clinical psychology/psychotherapy may lag developments in AI/ML-enabled tools in mental healthcare. This survey of postgraduate clinical psychology and psychotherapy students raises questions about how curricula could be enhanced to better prepare clinical psychology/psychotherapy trainees to engage in constructive debate about ethical and evidence-based issues pertaining to AI/ML tools, and in guiding patients on the use of online mental health services and apps.