TY - JOUR
T1 - ‘One size does not fit all’: The value of person-centred analysis in health professions education research
T2 - The value of person-centred analysis in health professions education research
AU - Kusurkar, Rashmi A.
AU - Mak-van der Vossen, Marianne
AU - Kors, Joyce
AU - Grijpma, Jan-Willem
AU - van der Burgt, Stéphanie M. E.
AU - Koster, Andries S.
AU - de la Croix, Anne
N1 - Funding Information: We would like to thank Dr. Anouk Wouters, Jettie Vreugdenhil, Lianne Mulder, Malou Stoffels and Marnix Westein from Research in Education, Amsterdam UMC, Faculty of Medicine Vrije Universiteit Amsterdam, for their feedback on an earlier version of the manuscript. Publisher Copyright: © 2020, The Author(s).
PY - 2021/8
Y1 - 2021/8
N2 - 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.
AB - 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.
KW - Person-centred analysis
KW - Personalized approach
KW - Research method
UR - http://www.scopus.com/inward/record.url?scp=85097244598&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/s40037-020-00633-w
DO - https://doi.org/10.1007/s40037-020-00633-w
M3 - Article
C2 - 33284407
SN - 2212-2761
VL - 10
SP - 245
EP - 251
JO - Perspectives on medical education
JF - Perspectives on medical education
IS - 4
ER -