Symposium 11 - Digital Phenotypes of Psychological Disorders

Thursday, June 25, 2026

11:30 AM - 1:00 PM PDT

Location: Yerba Buena Salon 10, B3 Level

CE: 1.5

Keywords: Assessment , Trauma , Emotion
Level of Familiarity: Basic to Moderate
Recommended Readings: Galatzer-Lev IR, McDuff, D., Natarajan, V., Karthikesalingam, A., & Malgaroli, M. The Capability of Large Language Models to Measure Psychiatric Functioning. arXiv preprint 2023: 2308.01834., Malgaroli, M., Schultebraucks, K., Myrick, K. J., Andrade Loch, A., Ospina-Pinillos, L., Choudhury, T., Kotov, R., De Choudhury, M., & Torous, J. (2025). Large language models for the mental health community: framework for translating code to care. Lancet Digit Health, 7(4), e282-e285., Schultebrauck K, Yadav, V., Shalev AY, Bonanno GA, Galatzer-Levy IR. Deep learning-based classification of posttraumatic stress disorder and depression following trauma utilizing visual and auditory markers of arousal and mood. Psychological Medicine 2022; 5(5): 957-67., ,

Chair(s)

RB

Richard Bryant, B.A., Ph.D., PsyM

Scientia Professor, head of Traumatic Stress Clinic
University of New South Wales
Sydney, New South Wales, Australia

Discussant(s)

RB

Richard Bryant, B.A., Ph.D., PsyM

Scientia Professor, head of Traumatic Stress Clinic
University of New South Wales
Sydney, New South Wales, Australia

Presenter(s)

Suzanna Azevedo, PsyM (she/her/hers)

UNSW
Randwick, New South Wales, Australia
JC

Jasmine Choi-Christou, Other

PhD Student
University of New South Wales
Sydney, New South Wales, Australia
Tomas Meaney, B.S., M.S., Ph.D. (he/him/his)

post-Doctorate
University of New South Wales
Sydney, New South Wales, Australia
RB

Richard Bryant, B.A., Ph.D., PsyM

Scientia Professor, head of Traumatic Stress Clinic
University of New South Wales
Sydney, New South Wales, Australia

Recent advances in digital technology and artificial intelligence have enabled more detailed analysis of expressions of emotions. Records of facial expressiveness (e.g., pupil dilation, muscle movements), acoustic (e.g., pitch, tone, jitter), and speech (e.g., sentiment) features have allowed more nuanced understanding of psychological states and processes. This symposium presents four empirical studies that have utilized digital biomarkers to focus on key psychological phenotypes observed in clinical settings. The first study reports the capacity of facial, acoustic, and speech data to map how positive emotion is expressed in Prolonged Grief Disorder. The second study reports on the digital phenotyping variables associated with different emotion regulation strategies. The third study reports on how Large Language Models can identify people with PTSD. Finally, the fourth study on the capacity of digital phenotyping to identify suicide risk. Together, these studies represent the latest advances in AI-driven approaches to detect emotional states, and harnessed to assist detection of key psychological phenotypes observed in clinical settings.

Learning Objectives:

To be aware of how AI-based platforms using multimodal data can identify psychopathological states.
To identify how suicide risk can be assessed using facial, acoustic, and speech data.
To understand how digital phenotyping of emotional states can identify anhedonia in prolonged grief.

Presentations:

11:36 AM - 11:57 AM PDT

(SYM 11) Digital Measurement of Positive Affect in Prolonged Grief Disorder
Speaker: Suzanna Azevedo, PsyM (she/her/hers) – UNSW
Co-Author: Tomas Meaney, B.S., M.S., Ph.D. (he/him/his) – University of New South Wales
Co-Author: Richard Bryant, B.A., Ph.D., PsyM – University of New South Wales
11:57 AM - 12:18 PM PDT

(SYM 11) Expressive Flexibility in Posttraumatic Stress Disorder
Speaker: Jasmine Choi-Christou, Other – University of New South Wales
12:18 PM - 12:39 PM PDT

(SYM 11) Classification of PTSD in Veterans Using Digital Phenotypes Processed by Large Language Models
Speaker: Tomas Meaney, B.S., M.S., Ph.D. (he/him/his) – University of New South Wales
Co-Author: Isaac Galatzer-Levy, PhD, MSC, BA – New York University
Co-Author: Vijay Yadav, PhD, MSC, BA – New York University
Co-Author: Richard Bryant, B.A., Ph.D., PsyM – University of New South Wales
12:39 PM - 1:00 PM PDT

(SYM 11) Identifying Suicide Risk with Digital Biomarkers of Emotional States
Speaker: Richard Bryant, B.A., Ph.D., PsyM – University of New South Wales