Dr. P.F.M. Krabbe

Paul Krabbe, a quantative psychologist, serves as an associate professor at the Department of Epidemiology and leads the Health Technology Assessment unit. He specializes in measuring health outcomes, particularly focusing on health status and 'health-related quality of life' (HRQoL).

He obtained his master's degree in psychology from the University of Utrecht in 1989. His career journey began as a researcher at the Department of Public Health at Erasmus University Rotterdam, followed by his pursuit of a Ph.D. at the same institution, successfully completed in 1998. In 1997, he assumed the role of assistant professor at Radboud University Medical Center. During his tenure as a visiting research fellow at the Harvard Initiative for Global Health in 2004, under the leadership of Christopher Murray, he began exploring modern scaling models as an alternative approach to measuring HRQoL. In 2010, he transitioned to his current position at the University Medical Center Groningen, affiliated with the University of Groningen.

Paul Krabbe has also served as a co-editor for the Journal of Quality of Life Research. He has authored and co-authored over 150 international publications covering a wide range of empirical, methodological, and theoretical topics in outcomes research. Additionally, he has contributed to book chapters and authored his own handbook (2016) on health outcome measurement. His work has received recognition through awards for research excellence and has prompted editorial responses. On multiple occasions, he has organized and presented workshops at international conferences. Notably, in 2022, he obtained a patent for an innovative new measurement method.

Research interests

Measurement theory – Measurement models - Health concepts

Key publications

• Krabbe PFM. The Measurement of Health and Health Status: Concepts, Methods and Applications from a Multidisciplinary Perspective. San Diego: Elsevier/Academic Press, 2016.

• Groothuis-Oudshoorn CGM, van der Heuvel E, Krabbe PFM. A preference-based item response theory model to measure health: concept and mathematics of the multi-attribute preference response model. BMC Medical Research Methodology 2018; 18: 62.