Machine Learning in Clinical Psychology and Psychotherapy Education
A Mixed Methods Pilot Survey of Postgraduate Students at a Swiss University
Bibliographic Data
| ID | 22076266 |
|---|---|
| Authors | Charlotte Blease (0000-0002-0205-1165, Beth Israel Deaconess Medical Center, corresponding author), Anna Kharko (0000-0003-0908-6173, University of Plymouth), Marco Annoni (0000-0003-3259-1856, Fondazione Umberto Veronesi), Jens Gaab (0000-0002-9194-8491, University of Basel), Cosima Locher (0000-0002-9660-0590, University of Basel) |
| Year | 2021 |
| Volume | 9 |
| Pages | 623088-623088 |
| Publication date | 2021-04-09 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2021.623088 |
| PMID | 33898374 |
| OpenAlex | W3154086819 |
| Language | EN |
| Citations received | 8 |
| References cited | 21 |
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
Family medicine · Medical education · Psychotherapist · Applied Psychology · Artificial Intelligence in Healthcare and Education · Clinical Psychology · Digital Mental Health Interventions · Medicine · Mental Health Research Topics · Psychology
Investigating psychotherapists’ attitudes towards artificial intelligence in psychotherapy
Integrating Artificial Intelligence into Psychological Counseling
Leveraging Random Forests explainability for predictive modeling of children's conduct problems
Ethical issues of the use of AI-driven mobile apps for education
A Call to Action on Assessing and Mitigating Bias in Artificial Intelligence Applications for Mental Health
Application of artificial intelligence in medical education
A Systems Thinking Framework for the Integration of Generative Artificial Intelligence in Decolonising Higher Education
Multi-stakeholder preferences for the use of artificial intelligence in healthcare
| Citations per year | 2.67 |
|---|---|
| Citation span | 2023 - 2026 (4) |
| Highly cited | No |