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

Abstract

Background: There is increasing use of psychotherapy apps in mental health care.Objective: This mixed methods pilot study aimed to explore postgraduate clinical psychology students' familiarity and formal exposure to topics related to artificial intelligence and machine learning (AI/ML) during their studies.Methods: In April-June 2020, we conducted a mixed-methods online survey using a convenience sample of 120 clinical psychology students enrolled in a two-year Masters' program at a Swiss University.Results: In total 37 students responded (response rate: 37/120, 31%). Among respondents, 73% (n = 27) intended to enter a mental health profession, and 97% reported that they had heard of the term “machine learning.” Students estimated 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. Qualitative analysis of students' comments resulted in four major themes on the impact of AI/ML on mental healthcare: (1) Changes in the quality and understanding of psychotherapy care; (2) Impact on patient-therapist interactions; (3) Impact on the psychotherapy profession; (4) Data management and ethical issues.Conclusions: This pilot study found that postgraduate clinical psychology students held a wide range of opinions but had limited formal education on how AI/ML-enabled tools might impact psychotherapy. The survey raises questions about how curricula could be enhanced to educate clinical psychology/psychotherapy trainees about the scope of AI/ML in mental healthcare.

Ethical issues of the use of AI-driven mobile apps for education

“…The following studies have been yielded as they contain a clear systematic approach to the topic and they fully focus on the ethical issues of AI in mobile apps (14,(18)(19)(20)(21)(22)(23)(24). The other detected texts only included more or less superficial comments on ethics, touching only on isolated issues, such as privacy [e.g., (25)(26)(27)(28)]. These studies are interesting and important, however, they could not be included in this specific conceptual research frame.…”

Computerization of the Work of General Practitioners: Mixed Methods Survey of Final-Year Medical Students in Ireland

“…We performed a brief scoping review of the literature using the terms "artificial intelligence," "machine learning," "education," and "training" in the search engines of PubMed and Google Scholar, and explored the grey literature. Only a few surveys, which were conducted in Europe, the United States, and South Korea, explored the attitudes of medical or health care students about the encroachment of AI/ML in medicine, and most were single-site studies [12][13][14][15][16][17][18]. Our objective was to explore the opinions of final-year medical students across Ireland to obtain a better understanding of their forecasts about the capacity of future technology to fully replace or to partner with physicians in undertaking key components of the work of GPs.…”

“…Despite these developments, in surveys, many medical professionals are skeptical about the impact and value of digital and AI/ML tools on their job, with surveyed physicians doubting the scope of technological innovations to replace clinicians in fundamental medical tasks [9][10][11]. Emerging surveys among students enrolled in a range of health care training programs, including medicine, dentistry, and clinical psychology, also revealed divergent opinions about the impact of AI/ML on their chosen profession, with participants reporting limited formal education on these topics [12][13][14][15][16][17][18].…”

Machine learning in medical education: a survey of the experiences and opinions of medical students in Ireland

“…Only a few studies -conducted in Europe, the US and South Korea -have explored the formal education and familiarity of medical or healthcare students with respect to digital advances in healthcare, and much of this work consists of single site studies. [8][9][10][11][12][13][14] To better understand and engage with discussion about the benefits, limitations, and ethical dilemmas presented by these tools, today's medical students will need to become more digitally savvy. Equally, as patients make increasing use of healthcare and well-being algorithms, medical students will need to become better prepared to offer patients advice, and to have knowledge about, the robustness of these tools including when algorithms are safe to use.…”

“…Furthermore, surveys consistently find limited evidence of formal teaching in medical education about AI/ML. Only a few studies – conducted in Europe, the US and South Korea – have explored the formal education and familiarity of medical or healthcare students with respect to digital advances in healthcare, and much of this work consists of single site studies 8–14. To better understand and engage with discussion about the benefits, limitations, and ethical dilemmas presented by these tools, today’s medical students will need to become more digitally savvy.…”