Robert Askew
Assistant Professor
Department of Management
Stetson University
United States of America
Biography
Dr. Robert Askew is a quantitative psychologist and epidemiologist whose research focuses on the measurement of distinct facets of physical and mental health through the application of latent variable modeling techniques. Prior to coming to Stetson, Askew was a cancer epidemiologist at the UT M.D. Anderson Cancer Center in Houston, where he explored the impact of diverse treatment modalities on patient quality of life and well-being in addition to more traditional outcomes like cancer recurrence and survival. During his doctoral studies at the University of Washington in Seattle, he specialized in the use of Item Response Theory based statistical models to develop and validate self-report measures of self-efficacy, depression, and mobility. His dissertation work on the multidimensional assessment of pain was recently published in the Journal of Clinical Epidemiology and Value in Health. Upon graduating, Askew was appointed Post-Doctoral Fellow at Northwestern University (NU) in Chicago, where he documented the impact of healthcare processes on patient health, recovery, and disability. His collaborations with faculty and fellows from the NIH-funded PROMIS (Patient Reported Outcome Measurement Information System) initiative led to his dual appointment as Chief Post-Doctoral Fellow at NU's Department of Medical Social Sciences. Askew's recent investigations of the impact of delays to rehabilitation services (i.e., Physical, Occupational, and Speech therapies) on post-stroke recovery have been presented at multiple international conferences including the American Public Health Association, Academy Health, and the American Congress of Rehabilitation Medicine. A selection of Askew's contributions to the scientific literature are available at the U.S. National Library of Medicine's website.
Research Interest
Measurement, Factor analysis, Item response theory, Latent class/profile analyses, Public health, Epidemiology of mental health, Symptom assessment, Study design and statistical modeling.