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Machine Learning in Clinical Psychology and Psychotherapy Education: A Mixed Methods Pilot Survey of Postgraduate Students at a Swiss University
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift) |
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ID |
4636947 |
Author(s) |
Blease, Charlotte; Kharko, Anna; Annoni, Marco; Gaab, Jens; Locher, Cosima |
Author(s) at UniBasel |
Gaab, Jens Locher, Cosima
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Year |
2021 |
Title |
Machine Learning in Clinical Psychology and Psychotherapy Education: A Mixed Methods Pilot Survey of Postgraduate Students at a Swiss University |
Journal |
Frontiers in Public Health |
Volume |
9 |
Pages / Article-Number |
623088 |
Keywords |
artificial intelligence, attitudes, ethics, machine learning, medical education, psychotherapy education, opinions, psychology students, survey |
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. |
ISSN/ISBN |
2296-2565 |
Full Text on edoc |
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Digital Object Identifier DOI |
10.3389/fpubh.2021.623088 |
PubMed ID |
http://www.ncbi.nlm.nih.gov/pubmed/33898374 |
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29/04/2024
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