This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.
This study seeks to contribute to the growing body of literature on hypnosis by providing robust, data-driven insights into the physiological mechanisms underlying trance states. The integration of electroencephalogram (EEG) and other wearable-derived physiological data will offer a comprehensive assessment of the changes that occur during a standardized hypnosis protocol: the Harvard Group Scale of Hypnotic Susceptibility (HGSHS:A). The results of this study are intended to facilitate derivation and validation of an Artificial Intelligence/Machine Learning (AI/ML)-based monitor that quantifies a patient's instantaneous emotional/arousal state along the spectrum that spans anxiety through states of calmness and trance. Future investigations will explore the ability of using such an interactive virtual system as a component of a closed-loop adaptive device to create optimal states of non-pharmacological sedation using personalized audiovisual content to allay anxiety and discomfort during medical procedures, such as percutaneous biopsies.
Standardized Hypnotic Susceptibility Testing to Facilitate Development of a Machine Learning Tool to Characterize Physiological Biomarkers of Calm and Tranced States
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
| Inclusion Criteria | Exclusion Criteria |
|---|---|
|
|
Sponsor: Icahn School of Medicine at Mount Sinai
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.