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.
The 5-year K01 Mentored Research Scientist proposal will employ brain, neurocognitive, and computational tools (e.g., machine learning) to understand the impact of opioid-use disorder (OUD) and common co-occurring issues on executive function and clinical outcomes. There have been record numbers of fatal and non-fatal overdoses (ODs) associated with opioids (and other drugs) in the past 12-months. Improving classification and predictive capabilities to enhance treatment and prevent relapse is of the upmost importance. Deficits in neurocognition often are associated with poor treatment outcomes (e.g., more drug use, medication non-adherence), yet co-occurring issues associated with OUD (e.g., depression, anxiety, physical/sexual abuse, neglect) make it difficult to parse which contributing factors lead to worse executive function (EF) and poorer treatment outcomes. Novel brain, neurocognitive, and computational tools are needed to help determine these differences, in order to lay the foundation for better treatments. This need has shaped both the training plan and the associated research project in a 5-year K01 Mentored Research Scientist proposal, building on Dr. Regier's prior preclinical and clinical addiction neuroscience experience (focused mostly on cocaine-use disorders, cue-reactivity, subcortical networks, prior adversity, and univariate imaging techniques).
Integrating Brain, Neurocognitive, and Computational Tools in Opioid Use Disorder (OUD) to Characterize Executive Function and to Predict Clinical Outcomes.
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.
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Sponsor: University of Pennsylvania
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.