Knowledge, skills and beetles: respecting the privacy of private experiences in medical education

In medical education, we assess knowledge, skills, and a third category usually called values or attitudes. While knowledge and skills can be assessed, this third category consists of ‘beetles’, after the philosopher Wittgenstein’s beetle-in-a-box analogy. The analogy demonstrates that private experiences such as pain and hunger are inaccessible to the public, and that we cannot know whether we all experience them in the same way. In this paper, we claim that unlike knowledge and skills, private experiences of medical learners cannot be objectively measured, assessed, or directly accessed in any way. If we try to do this anyway, we risk reducing them to knowledge and skills—thereby making curriculum design choices based on what can be measured rather than what is valuable education, and rewarding zombie-like student behaviour rather than authentic development. We conclude that we should no longer use the model of representation to assess attitudes, emotions, empathy, and other beetles. This amounts to, first of all, shutting the

Organic or organised: An interaction analysis to identify how interactional practices influence participation in group decision meetings for residency selection

Objectives This study aims to shed light on interactional practices in real-life selection decision-making meetings. Adequate residency selection is crucial, yet currently, we have little understanding of how the decision-making process takes place in practice. Since having a wide range of perspectives on candidates is assumed to enhance decision-making, our analytical focus will lie on the possibilities for committee members to participate by contributing their perspective. Design We analysed interaction in seven recorded real-life selection group decision meetings, with explicit attention to participation. Setting Selection meetings of four different highly competitive specialties in two Dutch regions. Participants 54 participants discussed 68 candidates. Methods To unravel interactional practices, group discussions were analysed using a hybrid data-driven, iterative analytical approach. We paid explicit attention to phenomena which have effects on participation. Word counts and an inductive qualitative analysis were used to identify existing variations in the current practices. Results We found a wide variety of practices. We highlight two distinct interactional patterns, which are illustrative of a spectrum of turn-taking practices, interactional norms and conventions in the meetings. Typical for the first pattern - organised' - is a chairperson who is in control of the topic and turn-taking process, silences between turns and a slow topic development. The second pattern - organic' - can be recognised by overlapping speech, clearly voiced disagreements and negotiation about the organisation of the discussion. Both interactional patterns influence the availability of information, as they create different types of thresholds for participation. Conclusions By deconstructing group decision-making meetings concerning resident selection, we show how structure, interactional norms and conventions affect participation. We identified a spectrum ranging from organic to organised. Both ends have different effects on possibilities for committee members to participate. Awareness of this spectrum might help groups to optimise decision processes by enriching the range of perspectives shared

Medical student engagement in small-group active learning: A stimulated recall study

Background: Active learning relies on students' engagement with teachers, study materials and/or each other. Although medical education has adopted active learning as a core component of medical training, teachers have difficulties recognising when and why their students engage or disengage and how to teach in ways that optimise engagement. With a better understanding of the dynamics of student engagement in small-group active learning settings, teachers could be facilitated in effectively engaging their students. Methods: We conducted a video-stimulated recall study to explore medical students' engagement during small-group learning activities. We recorded one teaching session of two different groups and selected critical moments of apparent (dis)engagement. These moments served as prompts for the 15 individual semi-structured interviews we held. Interview data were analysed using Template Analysis style of thematic analysis. To guide the analysis, we used a framework that describes student engagement as a dynamic and multidimensional concept, consisting of behavioural, cognitive and emotional components. Results: The analysis uncovered three main findings: (1) In-class student engagement followed a spiral-like pattern. Once students were engaged or disengaged on one dimension, other dimensions were likely to follow suit. (2) Students' willingness to engage in class was decided before class, depending on their perception of a number of personal, social and educational antecedents of engagement. (3) Distinguishing engagement from disengagement appeared to be difficult for teachers, because the intention behind student behaviour was not always identifiable. Discussion: This study adds to the literature by illuminating the dynamic process of student engagement and explaining the difficulty of recognising and influencing this process in practice. Based on the importance of discerning the intentions behind student behaviour, we advise teachers to use their observations of student (dis)engagement to initiate interaction with students with open and inviting prompts. This can help teachers to (re-)engage students in their classrooms

Medical student engagement in small-group active learning: a stimulated-recall study

Background: Active learning relies on students' engagement with teachers, study materials and/or each other. Although medical education has adopted active learning as a core component of medical training, teachers have difficulties recognising when and why their students engage or disengage and how to teach in ways that optimise engagement. With a better understanding of the dynamics of student engagement in small-group active learning settings, teachers could be facilitated in effectively engaging their students. Methods: We conducted a video-stimulated recall study to explore medical students' engagement during small-group learning activities. We recorded one teaching session of two different groups and selected critical moments of apparent (dis)engagement. These moments served as prompts for the 15 individual semi-structured interviews we held. Interview data were analysed using Template Analysis style of thematic analysis. To guide the analysis, we used a framework that describes student engagement as a dynamic and multidimensional concept, consisting of behavioural, cognitive and emotional components. Results: The analysis uncovered three main findings: (1) In-class student engagement followed a spiral-like pattern. Once students were engaged or disengaged on one dimension, other dimensions were likely to follow suit. (2) Students' willingness to engage in class was decided before class, depending on their perception of a number of personal, social and educational antecedents of engagement. (3) Distinguishing engagement from disengagement appeared to be difficult for teachers, because the intention behind student behaviour was not always identifiable. Discussion: This study adds to the literature by illuminating the dynamic process of student engagement and explaining the difficulty of recognising and influencing this process in practice. Based on the importance of discerning the intentions behind student behaviour, we advise teachers to use their observations of student (dis)engagement to initiate interaction with students with open and inviting prompts. This can help teachers to (re-)engage students in their classrooms

Developing a two-dimensional model of unprofessional behaviour profiles in medical students

Standardized narratives or profiles can facilitate identification of poor professional behaviour of medical students. If unprofessional behaviour is identified, educators can help the student to improve their professional performance. In an earlier study, based on opinions of frontline teachers from one institution, the authors identified three profiles of medical students’ unprofessional behaviour: (1) Poor reliability, (2) Poor reliability and poor insight, and (3) Poor reliability, poor insight and poor adaptability. The distinguishing variable was Capacity for self-reflection and adaptability. The current study used Nominal Group Technique and thematic analysis to refine these findings by synthesizing experts’ opinions from different medical schools, aiming to develop a model of unprofessional behaviour profiles in medical students. Thirty-one experienced faculty, purposively sampled for knowledge and experience in teaching and evaluation of professionalism, participated in five meetings at five medical schools in the Netherlands. In each group, participants generated ideas, discussed them, and independently ranked these ideas by allocating points to them. Experts suggested ten different ideas, from which the top 3 received 60% of all ranking points: (1) Reflectiveness and adaptability are two distinct distinguishing variables (25%), (2) The term reliability is too narrow to describe unprofessional behaviour (22%), and (3) Profiles are dynamic over time (12%). Incorporating these ideas yielded a model consisting of four profiles of medical students’ unprofessional behaviour (accidental behaviour, struggling behaviour, gaming-the-system behaviour and disavowing behaviour) and two distinguishing variables (reflectiveness and adaptability). The findings could advance educators’ insight into students’ unprofessional behaviour, and provide information for future research on professionalism remediation

Learning about stress from building, drilling and flying: a scoping review on team performance and stress in non-medical fields

Background: Teamwork is essential in healthcare, but team performance tends to deteriorate in stressful situations. Further development of training and education for healthcare teams requires a more complete understanding of team performance in stressful situations. We wanted to learn from others, by looking beyond the field of medicine, aiming to learn about a) sources of stress, b) effects of stress on team performance and c) concepts on dealing with stress. Methods: A scoping literature review was undertaken. The three largest interdisciplinary databases outside of healthcare, Scopus, Web of Science and PsycINFO, were searched for articles published in English between 2008 and 2020. Eligible articles focused on team performance in stressful situations with outcome measures at a team level. Studies were selected, and data were extracted and analysed by at least two researchers. Results: In total, 15 articles were included in the review (4 non-comparative, 6 multi- or mixed methods, 5 experimental studies). Three sources of stress were identified: performance pressure, role pressure and time pressure. Potential effects of stress on the team were: a narrow focus on task execution, unclear responsibilities within the team and diminished understanding of the situation. Communication, shared knowledge and situational awareness were identified as potentially helpful team processes. Cross training was suggested as a promising intervention to develop a shared mental model within a team. Conclusion: Stress can have a significant impact on team performance. Developing strategies to prevent and manage stress and its impact has the potential to significantly increase performance of teams in stressful situations. Further research into the development and use of team cognition in stress in healthcare teams is needed, in order to be able to integrate this ‘team brain’ in training and education with the specific goal of preparing professionals for team performance in stressful situations

‘One size does not fit all’: The value of person-centred analysis in health professions education research

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