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Distinguishing Three Unprofessional Behavior Profiles of Medical Students Using Latent Class Analysis
Marianne C Mak-van der Vossen1, Walther N K A van Mook, Joyce M Kors
1M.C. Mak-van der Vossen is a general practitioner, PhD student, Department of Research in Education, and coordinator of the educational theme "Professional behavior," VUmc School of Medical Sciences, Amsterdam, the Netherlands. W.N.K.A. van Mook is internist/intensivist, Department of Intensive Care Medicine, Maastricht University Medical Center, and associate professor, Medical Education, Maastricht University, Maastricht, the Netherlands. J.M. Kors is a midwife and medical educator, AVAG Midwifery Academy, Amsterdam Groningen, the Netherlands. W.N. van Wieringen is biostatistician, Department of Epidemiology and Biostatistics, VU University Medical Centre, Amsterdam, the Netherlands. S.M. Peerdeman is neurosurgeon, VU University Medical Centre, and professor of professional development, VUmc School of Medical Sciences, Amsterdam, the Netherlands. G. Croiset is professor of medical education and director, VUmc School of Medical Sciences, Amsterdam, the Netherlands. R.A. Kusurkar is head, Department of Research in Education, VUmc School of Medical Sciences, Amsterdam, the Netherlands.
Purpose:
Because unprofessional behavior of physicians is associated with unprofessional behavior in medical school, identifying unprofessional behavior in medical school is critical. Research has noted the difficulty in assessing professional behavior. Instead of identifying isolated behaviors, it could be more helpful to recognize behavioral patterns to evaluate students' professional behavior. The authors aimed to identify patterns in the unprofessional behaviors of medical students and to construct descriptions based on these patterns.
Method:
Content analysis of research articles yielded a template of unprofessional behaviors for coding student evaluation forms indicating unsatisfactory professional behavior, collected from 2012 to 2014 at the VUmc School of Medical Sciences, Amsterdam, the Netherlands. Latent class analysis was used to identify classes of students with a high chance of displaying comparable unprofessional behaviors. Teachers' feedback of prototype students was summarized to generate profile descriptions.
Results:
A template of 109 behaviors was used to code 232 evaluation forms of 194 students (3.9% students/year). Latent class analysis identified three hypothetical classes of students: Class 1 (43%) was labeled as "Poor reliability," class 2 (20%) was labeled as "Poor reliability and poor insight," and class 3 (37%) was labeled as "Poor reliability, poor insight, and poor adaptability."
Conclusions:
These profiles of unprofessional behavior might help to improve the evaluation of unprofessional behavior in medical school. Further research should provide evidence for confidently accepting or rejecting the profiles as an instrument to identify which students are expected to benefit from remediation trajectories.
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