Kusurkar, Rashmi A., Marianne Mak-van der Vossen, Joyce Kors, Jan-Willem Grijpma, Stéphanie M. E. van der Burgt, Andries S. Koster, & Anne de la Croix (2020, December). One size does not fit all’: The value of person-centred analysis in health professions education research. Perspectives on Medical Education. (ePub in advance of print). 7 pp. (doi: 0.1007/s40037-020-00633-w) (Open Access: https://doi.org/10.1007/s40037-020-00633-w)

Abstract: Health professions education (HPE) research is dominated by variable-centred analysis, which enables the exploration of relationships between different independent and dependent variables in a study. Although the results of such analysis are interesting, an effort to conduct a more person-centred analysis in HPE research can help us in generating a more nuanced interpretation of the data on the variables involved in teaching and learning. The added value of using person-centred analysis, next to variable-centred analysis, lies in what it can bring to the applications of the research findings in educational practice. Research findings of person-centred analysis can facilitate the development of more personalized learning or remediation pathways and customization of teaching and supervision efforts. Making the research findings more recognizable in practice can make it easier for teachers and supervisors to understand and deal with students. The aim of this article is to compare and contrast different methods that can be used for person-centred analysis and show the incremental value of such analysis in HPE research. We describe three methods for conducting person-centred analysis: cluster, latent class and Q-sort analyses, along with their advantages and disadvantage with three concrete examples for each method from HPE research studies.

Rashmi A Kusurkar <r.kusurkar@amsterdamumc.nl> is in Research in Education, Faculty of Medicine, Vrije Universiteit Amsterdam, The Netherlands.

Leave a Reply

Please log in using one of these methods to post your comment:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.