Therapist in the Loop

Research

Showing 5 summaries.

An artificial intelligence–assisted self-referral and assessment system was associated with shorter wait times, reduced clinician assessment time, lower dropout rates, higher recovery rates, and improved allocation of patients to appropriate treatment pathways.

Max Rollwage, Johanna Habicht, Keno Juechems, et al.

JMIR AI

Despite strong performance on medical licensing exams, LLMs may still fall short in real-world settings, where accuracy depends on interaction quality, such as both user input and the model's ability to communicate effectively to the user.

Andrew M. Bean, Rebecca Elizabeth Payne, Guy Parsons, et al.

Nature Medicine

Reviewing psychotherapy standards and testing both general LLMs and commercial therapy bots, the authors argue that current AI systems should not replace therapists because they can express stigma, respond inappropriately in some mental health situations, and cannot reproduce key human elements of care.

Jared Moore, Declan Grabb, William Agnew, et al.

Preprint

MindEval shows state-of-the-art models struggle with realistic multi-turn therapy conversations.

Jose Pombal, Maya D'Eon, Nuno M. Guerreiro, et al.

Preprint

A proposed framework suggests that general-purpose AI chatbots could perpetuate OCD and anxiety by reinforcing avoidance and reassurance-seeking.

Ashleigh Golden, Elias Aboujaoude

npj Digital Medicine

Editor's note: Includes a practical section on addressing reassurance-seeking dynamics in recurrent conversations with LLM chatbots.