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Our lab

Our lab

Our lab

Our lab

Our lab

Our lab

The Psychotherapy Research Laboratory, directed by Prof. Dana Atzil-Slonim, is part of the Department of Psychology at Bar-Ilan University.

We study the intrapersonal and interpersonal dynamics that unfold during psychotherapy, with the goal of understanding how people change in treatment and the mechanisms that make such change possible. At the heart of our work is the question of how patients’ and therapists’ emotions, behaviors, thoughts, and needs influence one another moment by moment, and how these interactions give rise to meaningful therapeutic change.

Our research integrates contemporary clinical theory with advanced research methods and tools from Artificial Intelligence (AI), Natural Language Processing (NLP), Machine Learning (ML), and multimodal analysis of language, voice, video, questionnaires, and physiological signals. Using these approaches, we analyze a rich collection of naturalistic psychotherapy data that includes both verbal and nonverbal information collected throughout the course of treatment. This integration enables us to examine therapeutic processes in depth and at scale, and to identify the patterns and mechanisms that promote change and recovery.

Our goal is to advance the scientific understanding of human change and to contribute to the development of approaches and tools that support more precise, personalized, and responsive mental health care.

 

 

Fields of Interest

Multimodal Intrapersonal dynamics

In-session emotional flexibility and self-regulation: how within-person dynamics shape outcomes.

Multimodal Interpersonal dynamics

In-session synchrony and co-regulation: how coordination in the therapeutic relationship shapes outcomes.

MIND Framework

MIND: a shared process language for identifying intrapersonal and interpersonal dynamics linked to therapeutic change.

Leveraging AI in Psychotherapy to Advance Mental Health

Using AI, NLP, and machine learning methods for scalable, automated multimodal psychotherapy research.

Monitoring, prevention, and early detection

Computational linguistics to support mental health monitoring in naturalistic settings.

Real-time feedback for therapists

Supporting therapist responsiveness by integrating context, intervention, and impact

Dynamics across relationships

Do couples and therapeutic dyads share the same “helpful” interaction sequences?

Recent Publications

Klein, A., Song, J., Chim, J., Keren, L., Triantafyllopoulos, A., Schuller, B., Liakata, M., & Atzil-Slonim, D. (2026). Clinical Summaries of Social Media Timelines for Mental Health Monitoring: Human Versus Large Language Model Comparative Evaluation Study. JMIR Formative Research, 10, Article e71230. https://doi.org/10.2196/71230
Sayda, D., Bar-Kalifa, E., Gordon, I., & Atzil-Slonim, D. (Accepted/In press). Flexible and multimodal synchrony during psychotherapy for depression: Addressing the mixed synchrony–outcome findings. Journal of Counseling Psychology. https://doi.org/10.1037/cou0000860
Goren, O., Paz, A., Bar-Kalifa, E., Gilboa-Schectman, E., & Atzil-Slonim, D. (2026). Respiratory sinus arrhythmia as a within-session biomarker in depression psychotherapy: integrrefereating resting RSA and RSA reactivity. Psychotherapy Research. Advance online publication. https://doi.org/10.1080/10503307.2026.2621741
Imel, Z. E., Creed, T., Kious, B., Althoff, T., Atzil-Slonim, D., & Srikumar, V. (2026). A Framework for Automation in Psychotherapy. Current Directions in Psychological Science, 35(2), 66-76. https://doi.org/10.1177/09637214251386047

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