Dr. Aoyjai Montgomery is an Assistant Professor and Applied Quantitative Methodologist in the Department of Family, Community and Health Systems, School of Nursing, University of Alabama at Birmingham, with a distinguished track record in quantitative methodology and healthcare research. Her research interests center on the nursing workforce, including nurse burnout, work environment factors, and their influence on patient outcomes among nurses and nurse leaders. Dr. Montgomery has served as a lead quantitative methodologist on numerous NIH- and foundation-funded grants, contributing her expertise across a wide range of healthcare domains. She also has experience with web-based survey design using platforms such as Qualtrics and REDCap. An experienced educator and mentor, Dr. Montgomery has taught doctoral-level quantitative methods courses, including DNP classes, and has provided extensive methodological guidance to doctoral students, post-doctoral fellows, and faculty. She brings deep proficiency in advanced statistical modeling and data analysis, utilizing software platforms such as SPSS and R to generate impactful insights.
Dr. Aoyjai Montgomery is an Assistant Professor and Applied Quantitative Methodologist in the Department of Family, Community and Health Systems, School of Nursing, University of Alabama at Birmingham, with a distinguished track record in quantitative methodology and healthcare research. Her research interests center on the nursing workforce, including nurse burnout, work environment factors, and their influence on patient outcomes among nurses and nurse leaders. Dr. Montgomery has served as a lead quantitative methodologist on numerous NIH- and foundation-funded grants, contributing her expertise across a wide range of healthcare domains. She also has experience with web-based survey design using platforms such as Qualtrics and REDCap. An experienced educator and mentor, Dr. Montgomery has taught doctoral-level quantitative methods courses, including DNP classes, and has provided extensive methodological guidance to doctoral students, post-doctoral fellows, and faculty. She brings deep proficiency in advanced statistical modeling and data analysis, utilizing software platforms such as SPSS and R to generate impactful insights.