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Ecological Momentary Assessment (EMA) involves repeated measures regarding the current behaviors and experiences in the patient's natural environments [1]. This assessment tool involves daily questions in diferent time-points along the day (e.g. Morning, Afternoon, and/or Evening). EMA is...

Our research focuses on implementing innovative techniques in the assessment and treatment of pain, mental health and substance use conditions in children and adolescents, including evaluating the progression of these conditions and the benefits of interventions (e.g., medications, invasive...

In parallel studies, we've examined the efficacy, safety, moderators and mediators of specific medications routinely used in treating pediatric pain patients and their common psychiatric comorbidities, as well as pharmacological interventions used to treat specific pain disorders in children and...

A survey study assessing opinions on the use of smartphone sensing for clinical purposes among adolescents with chronic pain and their parents Principal Investigator: Joe Kossowsky, PhD, MMSc Collaborators: Bobbie Riley, MD, Kristen Uhl, PhD, and Christine Greco, MD Research Staff: Justin Chimoff...

The Laboratory for Digital Assessment, Research and Treatment (DART Lab) in the Department of Anesthesiology, Critical Care and Pain Medicine at Boston Children’s Hospital/Harvard Medical School is seeking a talented, highly motivated Postdoctoral Fellow who is passionate about using digital health...

Helen Koechlin, PhD My research focuses on chronic pain in children and adolescents. I am interested in psychological factors, especially emotions, emotion regulation and sensory processing sensitivity, that might contribute to the development and maintenance of chronic pain. Knowing more about...

A longstanding barrier to progress, both in clinical settings and pediatric pain research, has been the fundamental difficulty of accurately assessing behavioral and functional outcomes in a continuous, nonobtrusive, and objective fashion. In a series of studies, we are testing the usage of wearable...

In pain, sleep and substance use disorders, we use bioinformatic and machine learning approaches to improve clinical phenotyping, as well as to understand their association with genetic variations. Our findings indicate genetic correlation between these disorders and highlight the importance of...