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 <email@example.com> is in Research in Education, Faculty of Medicine, Vrije Universiteit Amsterdam, The Netherlands.