{"id":70,"date":"2023-07-26T12:14:57","date_gmt":"2023-07-26T12:14:57","guid":{"rendered":"https:\/\/geiselmed2.dartmouth.edu\/scd2\/?page_id=66"},"modified":"2023-09-08T21:15:25","modified_gmt":"2023-09-08T21:15:25","slug":"predoctoral-trainees","status":"publish","type":"page","link":"https:\/\/geiselmed.dartmouth.edu\/scd\/predoctoral-trainees\/","title":{"rendered":"Predoctoral Trainees"},"content":{"rendered":"

\"women<\/p>

Jesse Boggis, MPH<\/h3>\n

I am a PhD candidate at The Dartmouth Institute for Health Policy & Clinical Practice. Since completing my T32 training, I was awarded the NIDA-funded NRSA F31 Individual Predoctoral Fellowship to Promote Diversity in Health-Related Research to support my dissertation: Evaluation of a Pharmacist-Integrated Model of Opioid Use Disorder Treatment to Increase Naloxone Co-Prescribing in Primary Care. At Dartmouth I am mentored by Dr. Lisa Marsch and contribute towards The Northeast Node of the National Drug Abuse Treatment Clinical Trials Network. I am interested in using mixed methods approaches to examine substance use, access to medication treatment for opioid use disorder, and evidence-based models of care which integrate harm reduction to reduce overdose mortality.<\/p>\n<\/div><\/div>

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Sukriti Ghosh, BS<\/h3>\n

Sukriti Ghosh is a PhD student in the Quantitative Biomedical Sciences(QBS) program at Dartmouth. Receiving her Bachelor of Science in Bioengineering from the University of Maryland and completing a minor in Neuroscience, she has conducted Bioengineering research at various institutions such as UMD, the Food and Drug Administration (FDA), and New York University\u2019s (NYU) Tech4Health Institute(T4H) and Neural Interface Engineering Lab (NIEL). Her engineering background has allowed her to gain skills in imaging and microscopy, medical devices, and virtual reality gaming and eye-tracking. Through these diverse research endeavors, she developed an interest in data science and computational techniques as well as psychiatry and mental healthcare. At QBS, she has found the combination of these interests in the Jacobson Lab and is particularly interested in learning and contributing to the digital mental health field more through her PhD. She ultimately hopes to apply machine learning and deep learning techniques to develop solutions in preventative and diagnostic mental healthcare.<\/p>\n<\/div><\/div>

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Salar Khaleghzadegan, MPP (Affiliated Trainee)<\/h3>\n

Salar Khaleghzadegan is a PhD student at The Dartmouth Institute for Health Policy and Clinical Practice. He completed his Master of Public Policy degree with a concentration in health policy at the University of Maryland Baltimore County School of Public Policy. Prior to starting at Dartmouth, he was a Research Data Analyst at the Armstrong Institute for Patient Safety and Quality at Johns Hopkins University School of Medicine. At Hopkins, he worked on numerous projects that primarily investigated the role of leadership, teamwork, and communication in the coordination of safe and high-quality care. One of his primary interests is exploring the intersection of health services research and computational precision health, where novel data sources (e.g. unobtrusive data, sensor-based data) and analysis approaches (e.g. quantitative text analysis approaches like natural language processing) are used to better inform learning health systems of the current status of health care delivery and to find innovative solutions for improving patient care and outcomes. One specific line of research he is especially interested in is studying the quality of conversations between patients and providers through the use of quantitative text analysis measures such as linguistic style matching. Ultimately, he is interested in exploring whether this method can provide a scalable approach for assessing communication quality during clinical interactions. In his free time, he likes to cook and enjoys gardening.<\/p>\n<\/div><\/div>

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Enzo Plaitano, BA, NRP (Affiliated Trainee)<\/h3>\n

Enzo is a 4th year PhD Candidate and Predoctoral Fellow at the Dartmouth Center for Technology and Behavioral Health (CTBH). Formerly, he was a Predoctoral Trainee in the NIH-NIDA T32 Science of Co-occurring Disorders Training Program within CTBH before transitioning to his own award. Enzo\u2019s NIH-NIDA Individual Predoctoral Fellowship Grant (1F31DA062393) and CTBH P30 Pilot Grant (P30DA029926) focus on identifying modifiable momentary predictors of substance use in high-risk emergency medical services clinicians. This work is informed by his lived experience as a licensed paramedic. Enzo understands the toll of this tough profession on his own mental health and sees the stress of this job contribute to mental health and substance use problems in his coworkers, impacting their lives, families, and healthcare careers. Therefore, his research methods leverage ecological momentary assessments (EMAs) and intensive longitudinal analysis to assess risk factors for substance use and mental health symptoms in real life environments. He plans to use these findings to develop and test robust digital health interventions to support this high-risk population. Enzo\u2019s mentors include Drs. Lisa Marsch, Nicholas Jacobson, and Madelyn Frumkin at CTBH. Enzo also collaborates with experts at the National Registry of EMTs, National Association of EMTs, and the National Center for PTSD, receiving wide-spread, national media attention for this novel, pioneering research. His free time is often spent traveling to new destinations or outside skiing, hiking, and biking around New England. Enzo also continues to work clinically as a licensed paramedic and ski patroller in a nearby town.<\/p>\n<\/div><\/div>

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