Using AI to Teach Psychology Trainees

I recently came across a pre-print comprehensive scoping review that sheds light on this emerging area, titled "Can Artificial Intelligence be used to teach Psychiatry and Psychology?- A Scoping Review." While focused on these specific disciplines, the insights are incredibly relevant to our work in school psychology. Let's explore the methods, key findings, and what this all means for those of us involved in training the next generation of school psychologists.

Unpacking the Methods of the Review
To get a handle on how AI is being integrated into psychiatry and psychology education, the researchers conducted a systematic search across six major electronic databases (MEDLINE, PubMed, Embase, PsycINFO, EBM Reviews, and Google Scholar) up to October 2024. They followed rigorous PRISMA-ScR guidelines for scoping reviews. The studies included in the review had to focus on psychiatry or psychology, describe the use of an AI tool, and discuss at least one facilitator or barrier to its educational use. After sifting through a whopping 6219 records, only 10 studies met all the criteria for inclusion. The researchers then extracted data on various aspects, including the AI application, educational outcomes, facilitators, and barriers, and even assessed the methodological quality of the included studies.

Key Findings: How AI is Showing Up
The review identified eight broad categories of AI applications currently being used in psychiatry and psychology education:

Clinical Decision Support: AI tools are helping trainees learn diagnosis, prognosis, risk assessment, and early intervention strategies. Imagine future school psychologists using AI to understand risk factors for mental health challenges in students or to inform their assessment processes.

Educational Content Creation & Enhancement: Generative AI, like ChatGPT, is being used to develop learning materials such as script concordance tests (a type of assessment used in health professions education to measure clinical reasoning), potentially offering a way to rapidly create quality training resources aligned with psychological frameworks. This could mean AI-assisted creation of case studies or assessment scenarios for our trainees.

Therapeutic Tools & Mental Health Monitoring: The review highlights the use of AI in digital interventions like CBT apps and chatbots, emphasizing the need for future clinicians to understand and evaluate these tools. School psychologists will likely encounter and need to understand these resources for students.

Administrative & Research Assistance: AI is helping with tasks like documentation, summarization, and literature reviews, potentially freeing up time for more direct learning and client care. This could assist in the research components of school psychology training.

Natural Language Processing (NLP) Applications: NLP tools are being used to analyze clinical language, aiding in understanding communication patterns and even identifying potential risk factors. This could have implications for understanding student communication and identifying potential needs.

Program/Policy Development: AI is influencing the design of teaching modules and the creation of policies around AI use in educational settings. This suggests that training programs will need to consider policies around AI use by students.

Student/Applicant Support: AI is being used to assist with application processes, such as drafting personal statements, and even in application screening. This might change how we advise students on their professional development.

Professional Development and Assessment: AI supports competency-based assessment and provides tailored feedback in postgraduate education. This could lead to innovative ways of assessing the skills of school psychology interns and practicing professionals.

The review also identified key facilitators for AI integration, such as the availability of AI tools, positive learner attitudes, digital infrastructure, and time-saving features. Conversely, barriers include limited AI training, ethical concerns (like data privacy and algorithmic bias), lack of digital literacy, algorithmic opacity, and insufficient curricular integration.

Implications for Trainers of School Psychologists: Our Call to Action
So, what does all of this mean for us, the trainers of future school psychologists? Several key implications emerge:

Curriculum Integration is Key: We need to proactively consider how AI-related concepts and tools can be thoughtfully integrated into our school psychology training programs. This isn't about replacing core skills but rather augmenting them with an understanding of how AI is and will be used in mental health.

Focus on AI Literacy: Just like any other tool, our trainees need to develop AI literacy – the ability to understand, evaluate, and use AI technologies effectively and ethically. This includes understanding the strengths and limitations of AI, recognizing potential biases, and critically evaluating AI-generated outputs.

Address Ethical Considerations: The ethical implications of using AI in mental health, such as data privacy, algorithmic bias, and the potential impact on the therapeutic relationship, must be explicitly addressed in our training. We need to prepare our students to navigate these complex issues responsibly.

Develop Digital Literacy: A foundational digital literacy is crucial for both educators and trainees to effectively engage with AI tools. This includes basic competence in using digital platforms and critically evaluating online information.

Faculty Development is Essential: As trainers, we ourselves need to become more knowledgeable about AI and its applications in our field. Professional development opportunities focused on AI literacy and pedagogical approaches to integrating AI will be vital.

Promote Critical Evaluation: We must emphasize the importance of critical thinking and professional judgment when interacting with AI-generated information or tools. AI should be seen as a support, not a replacement for human expertise and ethical decision-making.

Explore Practical Applications: We should explore and potentially pilot the use of relevant AI tools within our training programs to provide students with hands-on experience and facilitate deeper learning. This could involve using AI for generating case studies, practicing diagnostic reasoning, or exploring mental health apps.

Key Takeaways for Trainers of School Psychologists

• AI is increasingly relevant in mental health education, and school psychology training needs to adapt.

• Training programs should integrate AI literacy, including understanding its applications, limitations, and ethical implications.

• Curricular integration of AI-related concepts and tools is crucial to prepare future school psychologists.

• Faculty development in AI is necessary for effective teaching and guidance.

• Emphasis on critical thinking and ethical considerations remains paramount when using AI in mental health contexts.

Final Thoughts
The AI revolution in mental health education isn’t something on the horizon—it’s already here. This review makes it clear that school psychology training programs have an opportunity and responsibility to engage with AI thoughtfully. By introducing our trainees to the tools, ethics, and practical realities of AI in mental health, we prepare them not just to adapt—but to lead.