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Enhancing Psychiatry Education with Generative AI: A Pilot Study on AI-Assisted Object Relations Theory Training.

Conner Polet^1,2, Deepti Anbarasan³, Brennan Carrithers³

¹New York University Langone Medical Center, New York, United States. poletc@nychhc.org.

Academic Psychiatry : the Journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry

|February 24, 2026

Summary

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Large language models (LLMs) can aid psychodynamic psychiatry education by generating object relations theory (ORT) formulations. While valuable for conceptual development, faculty oversight is crucial to mitigate potential biases and inaccuracies in AI-generated content.

Area of Science:

Psychiatry
Medical Education
Artificial Intelligence

Background:

Psychodynamic psychiatry training relies on understanding complex theories like object relations theory (ORT).
Large language models (LLMs) offer new tools for educational content generation.
Assessing the utility of LLM-generated ORT formulations in resident education is warranted.

Purpose of the Study:

To evaluate the effectiveness of LLM-generated ORT formulations in enhancing psychodynamic psychiatry resident education.

Main Methods:

An observational study involving 11 residents using GPT-4 to generate ORT formulations from case narratives.
Residents rated the accuracy, clarity, and educational value of the AI-generated content.
Qualitative thematic analysis explored resident perceptions and identified key themes.

Keywords:

Generative AI Object relations theory Psychiatry education

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Main Results:

Residents rated the AI-generated ORT formulations highly for clarity, structure, and educational value.
Key themes included improved conceptual anchoring, but also risks of overgeneralization and maternal bias.
Outputs were generally concise and clinically applicable, with noted occasional inaccuracies.

Conclusions:

AI-generated ORT formulations, with supervision, can supplement psychodynamic education by standardizing terms and aiding conceptual growth.
Further research is needed to assess impact on standardized assessments and other theoretical models.