Assessments in Medical education play a crucial role in predicting the safety and efficiency of doctors we graduate. In Health professions education, clinical case vignettes are frequently used within routinely undertaken assessment tools such as Multiple-Choice Questions (MCQs) and Objective Structured Clinical Examinations (OSCEs).
Clinical case vignettes
Vignettes are used to illustrate a patient case by providing information on the patient’s medical history, symptoms, and relevant clinical information, allowing students to examine and make decisions about diagnosis and management. Sociodemographic variables such as race, ethnicity, gender identity, and sexual orientation, may also be included. These vignettes present a snapshot of hypothetical or real-life clinical cases in a focussed manner allowing students to situate these assessments within clinical context. That way, students are encouraged to make connections of their understanding of medical concepts into a real-world context, promoting learning.
An example of a clinical case vignette looks like:
“A 2-year-old girl from a South Asian background has not yet begun walking. She is currently growing well, measuring in the 25th percentile for weight. However, she has bowed legs and infrequent bowel movements. You suspect rickets as your preliminary diagnosis” (Ahluwalia et al., 2023, p. 926)↗️.
Ahluwalia et al. (2023)↗️ question the extent to which information about the child’s ethnic background is necessary to diagnose this disease. On one hand, Cookson (2023)↗️ argues that it is crucial to include such demographic information to increase the probability of the correct answer/diagnosis. On the other hand, Ahluwalia et al. (2023)↗️ contend that it holds lesser significance and that the use of information on ethnic background can perpetuate negative stereotypes linking people of a particular race and ethnic background to poor dietary and socio-economic conditions.
While incorporating information on race or gender within vignettes may seem to perpetuate stereotypes and worsen biases, omitting this socio-demographic information might imply to students that details about a patient’s sociocultural background are either irrelevant or presumed (Lee et al., 2022)↗️. Alternatively, suggesting all scenarios should uniformly include contextual material, irrespective of its relevance, is meaningless and may inadvertently reinforce connections (for ex: between one’s race and social determinants of health), where they do not exist (Cookson, 2023)↗️. This blog post aims to engage in an ongoing conversation around creating inclusive assessments and suggesting ways of thinking through this, leaning on the existing assessment literature.
Cultural competence
We want our students to be culturally competent; that is, to be aware of the fluid nature of different cultures and be cautious of rigid views, for example, subconsciously linking one’s race to a particular health condition that can reinforce harmful stereotypes and perpetuate biases (Almutairi, Dahinten and Rodney, 2015)↗️. We want them to understand the potential links between patient demographics and social determinants of health, yet have a broader, unbiased perspective while making decisions, within both assessment and clinical contexts. Lambert, Funk and Adam (2022)↗️ suggest that an inclusive assessment within the subset of a decolonised curriculum will involve placing one’s own culture at the centre of their learning, while also incorporating elements to help understand other cultures and their complexities. This means the different clinical case vignettes that we use in assessments should ideally present clinical cases that reflect a given student’s own culture while providing a diverse view of all the other cultures and their complexity.
Application of culturally inclusive assessment model
Lambert, Funk and Adam (2022)↗️’s ‘Culturally Inclusive Assessment Model’ suggests potential avenues for educators to work towards inclusive assessments in medical education, encompassing three dimensions: Justice-as-content, Justice-as-process, and Justice-as-pedagogy.
Justice as content
Firstly, Lambert, Funk and Adam (2022)↗️ encourage us to look through our content material, in our case, question banks, textbooks, lecture notes, etc., and work towards diversification and decolonisation. This is complex and involves doing a harm-benefit analysis, asking and debating ‘Why should we include/exclude this content?’ and ensuring that benefits always overweigh potential harms.
- Content diversification
- Identify, carefully consider and rectify use of exclusive terminologies that can potentially perpetuate stereotypes, such as ‘single mother’ or ‘homeless’ or ‘immigrant’
- Also, correct under-representation by inclusion of diversified cultural examples and improving visibility of marginalised population.
- Correcting misrecognition
- Identify and rectify content that portrays cultural differences in a negative or stereotypical manner.
- deficit discourse that focusses on lacks be re-storied to form an inclusive narrative that embraces diverse patient characteristics. For example, A patient from a low-income neighbourhood presents with poorly controlled diabetes – Instead of labelling the patient as non-compliant due to lack of motivation, an empathetic approach seeks to understand their circumstances and explore resources for improving their health outcomes.
Justice as process
Secondly, Lambert, Funk and Adam (2022)↗️ invite us to promote assessment and learning activities that focus on co-creation and plurality of thought e.g. designing an assessment task for students to create and critique clinical case vignettes with an intention to promote inclusive assessment practices. Such a task would:
- encourage co-creation and trust: Students and staff are invited to reflect together on their own personal positions and conscious/unconscious biases.
- critique whose knowledge or narrative the vignettes reflect and thus encourage diversity in ways of thinking.
- inculcate a two-way learning mindset (we learn from and about each other’s culture) to bridge cross-cultural and cross-contextual knowledge.
Justice as pedagogy
Thirdly, Lambert, Funk and Adam (2022)↗️ suggest incorporating principles of socio-cultural justice, decolonisation, and cultural competence into the teaching and assessment process. They recommend:
- designing assessment that drives unlearning of pre-existing assumptions, and deficit discourses.
- promoting discussions that delve into the socio-cultural injustices and bias narratives in their curriculum flattening hierarchies.
- providing feedback opportunities to reflect and comment on the inclusive nature of their medical school assessments.
AI integration potential:
To fit in all of these into a densely packed medical education curriculum feels daunting. To mitigate some of these challenges, Bakkum et al. (2024)↗️ suggest ways in which we can utilise Generative AI technologies such as ChatGPT in creating inclusive clinical case vignettes. They provide a detailed recipe of prompts that outline the patients’ medical history, social identities and case description – with some elements randomised together (e.g., name, gender and ethnicity) and some independently (e.g., BMI, lifestyle) to ensure creation of diverse and inclusive clinical case vignettes. While we try to integrate novel AI tools into medical education, in this context, it would be valuable to reflect on the process and outcomes using the culturally inclusive assessment model thinking in terms of justice as content, justice as process and justice as pedagogy.
It is good practice to build clinical case vignettes that are culturally specific and diverse. However, it is important to be woke and be consciously aware of the potential negative stereotypes they may reinforce.
Although this post aims to discuss how to make clinical case vignettes more inclusive, the model discussed by Lambert, Funk and Adam (2022)↗️ seems transferable to a number of different assessment approaches across different contexts and disciplines.
References
Ahluwalia, A., Arif, A., Shah, M. H. and Roy, S. (2023) ‘Towards equitable medical education resources: Challenging the representation of ethnicity in clinical vignettes’↗️, Medical Teacher, 45(8), pp. 926-926.
Almutairi, A. F., Dahinten, V. S. and Rodney, P. (2015) ‘Almutairi’s Critical Cultural Competence model for a multicultural healthcare environment’↗️, Nursing Inquiry, 22(4), pp. 317-325.
Bakkum, M. J., Hartjes, M. G., Piët, J. D., Donker, E. M., Likic, R., Sanz, E., de Ponti, F., Verdonk, P., Richir, M. C., van Agtmael, M. A. and Tichelaar, J. (2024) ‘Using artificial intelligence to create diverse and inclusive medical case vignettes for education’↗️, Br J Clin Pharmacol, 90(3), pp. 640-648.
Cookson, J. (2023) ‘Ethnicity in clinical vignettes’↗️, Medical Teacher, 45(12), pp. 1441-1441.
Lambert, S., Funk, J. and Adam, T. (2022) ‘What can decolonisation of curriculum tell us about inclusive assessment? ‘↗️, in Ajjawi, R. (ed.) Assessment for Inclusion in Higher Education : Promoting Equity and Social Justice in Assessment. 1 ed. Milton, UNITED KINGDOM: Taylor & Francis Group.
Lee, C. R., Gilliland, K. O., Beck Dallaghan, G. L. and Tolleson-Rinehart, S. (2022) ‘Race, ethnicity, and gender representation in clinical case vignettes: a 20-year comparison between two institutions’↗️, BMC Medical Education, 22(1), pp. 585.
Sylvia Joshua Western
Sylvia is currently doing her PhD in Clinical Education at The University of Edinburgh and has a Master’s degree in Clinical Education. Her PhD research explores test-wise behaviours in Objective Structured Clinical Examination (OSCE) context. Coming from a dental background, she enjoys learning about and researching clinical assessments. She works part-time as a PhD intern at Teaching Matters, the University’s largest blog and podcast platform through Employ.ed↗️ scheme at the Institute of Academic Development.
Jane Hislop
Dr Jane Hislop is Director of the PG Certificate in Simulation Based Clinical Education and senior lecturer in medical education in the Medical School. Jane teaches on online distance-learning programmes for those involved in undergraduate and post-graduate education of health professionals (including qualified doctors, nurses, dentists, pharmacists, and allied health professionals). In addition, Jane works part-time as a Clinical Education lead in Musculoskeletal Physiotherapy within NHS Fife Scotland. Jane has a particular interest in peer assessment and feedback, as well as Simulation methodology. You can find Jane on Twitter at @hijanehislop↗️.
Alan Jaap
Dr Alan Jaap is Deputy Director of Teaching and Assessment Lead at Edinburgh Medical School↗️. He has a research interest in learning, assessment and feedback in the clinical workplace and in preparation for clinical practice. He is a senior fellow of the HEA.
David Hope
Dr David Hope is a psychometrician specialising in assessment and feedback. A fellow of the HEA, he is closely involved in the assessment of undergraduate and postgraduate medical students and mentors on the Edinburgh Teaching Award↗️. His previous work with PTAS has received a Teaching Innovation Award from the International Association for Medical Education. He is currently working on supporting at-risk students before they fail assessment, helping to improve formative feedback in the clinical assessments.
