Anxiety & Mood Disorders Research | NYU Langone Health

Department of Child & Adolescent Psychiatry Research Anxiety & Mood Disorders Research

Anxiety & Mood Disorders Research

Researchers in NYU Langone’s Department of Child and Adolescent Psychiatry investigate risk factors, symptom presentation, illness course, and evidence-based treatments for anxiety and mood disorders to improve patient outcomes. As leaders in research for conditions affecting children’s development and mental health, we conduct observational studies and clinical trials in collaboration with investigators at the Anita Saltz Institute for Anxiety and Mood Disorders at the Child Study Center, part of Hassenfeld Children’s Hospital at NYU Langone.

Current Studies

Our researchers are currently working on the following studies.

Digital Phenotyping: A Novel Method to Predict Proximal Suicide Risk in Youth

The goal of this study is to use digital phenotyping—a method of collecting data from smartphone sensors—and traditional assessments, including questionnaires and interviews, to determine suicide risk in adolescents. Using smartphone keyboards, we will continuously collect data that may lead to more accurate and timely prediction, and enable prompt intervention if needed. We are currently recruiting adolescents with a history of suicidal thoughts or behaviors in the past six weeks.

The Digital Phenotype of Bipolar Disorder: An Observational Study of Mood Symptoms in Adolescents

Our research study goal is to use digital phenotyping and traditional assessments to study the symptoms and progression of bipolar disorder in adolescents. Research suggests that before the onset of clinically significant mood symptoms, there is a period of time when people who have bipolar disorder experience a change in functioning. This finding could result in an opportunity to intervene before harmful symptoms develop. We are currently recruiting both adolescents with bipolar disorder and adolescents who do not have a mental health diagnosis.

Predicting Adolescent Suicide Risk Using a Machine Learning Approach with Family Medical Records

This project aims to build a statistical algorithm to assess the risk of suicide in adolescents using data accessible through a patient’s electronic health record (EHR). Our goal is to improve upon past suicide prediction tools which have largely focused on single sources of data by incorporating multiple data sources, including patients’ EHR, parents’ EHR, natural language processing of clinical notes, and patients’ self-reports. The resulting algorithm will serve as the foundation for a larger prospective study to predict proximal suicide risk in youth. We are not currently recruiting participants for this study.

Effectiveness Implementation Trial of SilverCloud as a School-Based Intervention

The goal of this study is to test the efficacy of SilverCloud, a clinician-guided, app-based cognitive behavioral therapy program and refine it to optimize its benefits as a school-based mental health intervention. Currently, the need for mental health services professionals in schools outnumbers available staff. SilverCloud can enable clinicians to work with more youth than is possible through traditional, in-person services. If successful, this trial could lead to evidence-based treatment for many more students in need of help. Recruitment is currently occurring through participating school-based health centers.

Contact Us

For more information about our current studies, please contact our research coordinator, Rena Ferrara, at 646-754-5053 or email ImpactLab@NYULangone.org.