BackgroundDeveloping professionalism is a core task in medical education. Unfortunately, it has remained difficult for educators to identify medical students’ unprofessionalism, because, among other reasons, there are no commonly adopted descriptors that can be used to document students’ unprofessional behaviour. This study aimed to generate an overview of descriptors for unprofessional behaviour based on research evidence of real-life unprofessional behaviours of medical students.MethodsA systematic review was conducted searching PubMed, Ebsco/ERIC, Ebsco/PsycINFO and Embase.com from inception to 2016. Articles were reviewed for admitted or witnessed unprofessional behaviours of undergraduate medical students.ResultsThe search yielded 11,963 different studies, 46 met all inclusion criteria. We found 205 different descriptions of unprofessional behaviours, which were coded into 30 different descriptors, and subsequently classified in four behavioural themes: failure to engage, dishonest behaviour, disrespectful behaviour, and poor self-awareness.ConclusionsThis overview provides a common language to describe medical students’ unprofessional behaviour. The framework of descriptors is proposed as a tool for educators to denominate students’ unprofessional behaviours. The found behaviours can have various causes, which should be explored in a discussion with the student about personal, interpersonal and/or institutional circumstances in which the behaviour occurred. Explicitly denominating unprofessional behaviour serves two goals: [i] creating a culture in which unprofessional behaviour is acknowledged, [ii] targeting students who need extra guidance. Both are important to avoid unprofessional behaviour among future doctors.Electronic supplementary materialThe online version of this article (10.1186/s12909-017-0997-x) contains supplementary material, which is available to authorized users.

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.

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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