Jarrad Van Stan, PhD, CCC-SLP
- Adjunct Assistant Professor
- PhD in Rehabilitation Sciences
Jarrad Van Stan, PhD, CCC-SLP is an Adjunct Assistant Professor in the PhD in Rehabilitation Sciences program in the School of Health and Rehabilitation Sciences at MGH Institute of Health Professions.
Currently, the majority of his time is oriented towards clinical research projects at the MGH Voice Center; with additional effort directed towards education/training of HMS laryngology fellows at the MGH Voice Center, PhD students from the SHBT program at HMS, and PhD and master’s students from the MGH Institute.
In his role as a research speech-language pathologist, he is involved in research projects funded through federal agencies (National Institute of Health [NIH NIDCD] and the Patient-Centered Outcomes Research Institute [PCORI]). More specifically, NIH grants have funded his work on developing ambulatory voice monitoring technology in hopes to improve clinical assessment and treatment of voice disorders. PCORI has funded his involvement in a national endeavor to improve behavioral therapy measurement throughout the field of rehabilitation by refining the Rehabilitation Treatment Taxonomy (RTT). His individual contribution to the RTT endeavor is incorporating clinical expertise from his work in developing treatment taxonomies for the field of speech pathology and voice therapy.
In terms of teaching and education, he is involved in providing research mentorship for PhD students in the Speech and Hearing Bioscience and Technology Program in the Division of Medical Sciences at Harvard Medical School, and for post-residency Fellows in Laryngeal Surgery at the MGH Voice Center. He also helps direct the Master’s theses of 1-2 speech-language pathology students per year (students from the MGH Institute). In addition, four of his first-author articles in the past three years have been used for national-level online education series/continuing education credits.
Dr. Van Stan clinical research program hopes to improve the assessment and treatment of voice disorders through the use of cutting-edge technology (e.g., ambulatory voice monitoring and biofeedback, virtual environments, machine learning) and testing/developing clinical treatment theory.