Warren Scott Comulada

Dr. W. Scott Comulada, DrPH, is Professor-in-residence in the UCLA Departments of Psychiatry and Biobehavioral Sciences and Health Policy and Management, Director of the Semel Institute Center for Community Health, a statistician, and a public health researcher. His work focuses on the development and evaluation of AI-enhanced digital health interventions that incorporate chatbots and virtual reality. 

Semel Institute Center for Community Health

Education

  • DrPH, Biostatistics, University of California, Los Angeles, CA, 2006
  • MS, Biostatistics, University of California, Los Angeles, CA, 2000
  • MPH, Biostatistics, Loma Linda University, Loma Linda, CA, 1998
  • BS, Biophysics, Pacific Union College, Angwin, CA, 1993

Related Tags

Areas of Interest

  • Digital health intervention design and analysis
  • Hierarchical and longitudinal data analysis

Selected Publications

  • van Heerden A, Harris DM, van Rooyen H, Barnabas R, Ramanathan N, Ngcobo N, Mpiyakhe Z, Comulada WS (2017). Perceived mHealth barriers and benefits for home-based HIV testing and counseling and other care: Qualitative findings from health officials, community health workers, and persons living with HIV in South Africa. Social Science & Medicine. 183: 97-105.
  • Comulada WS, Goldbeck C, Almirol E, Gunn HJ, Ocasio MA, Fernández MI, Arnold EM, Romero-Espinoza A, Urauchi S, Ramos W, Rotheram-Borus MJ, Klausner JD, Swendeman D, Adolescent Medicine Trials Network (ATN) Cares Team (2021). Using machine learning to predict young people’s Internet health and social service information seeking. Prevention Science. 22(8): 1173-1184.
  • Gunn HJ, Hayati Rezvan P, Fernández MI, Comulada WS (2023). How to apply variable selection machine learning algorithms with multiply imputed data: A missing discussion. Psychological Methods. 28(2):452-471.
  • Comulada WS, Rezai R, Sumstine S, Flores DD, Kerin T, Ocasio MA, Swendeman D, Fernández MI, Adolescent Trials Network (ATN) CARES Team (2024). A necessary conversation to develop chatbots for HIV studies: Qualitative findings form research staff, community advisory board members, and study participants. AIDS Care. 36(4):463-471.
  • Weisman D, Sugarman A, Huang YM, Gelberg L, Ganz PA, Comulada WS. AI-driven communication training for medical students to practice discussing abnormal mammogram results with patients: Development of a GPT-4 powered virtual simulated patient. JMIR Formative Research. in press.