In an effort to improve equity, diversity and inclusion across medical sciences and education, students and academics at the University of Exeter Medical School co-created a checklist to help lecturers embed these qualities into curricula.
In a previous resource – part one – we presented three checklist questions designed to guide academics in dismantling systemic barriers, promoting health equity and fostering a sense of belonging among students.
Here we present the second half of the checklist with three questions focused on ethical issues, health inequalities and diverse learning sources.
4. What are the current ethical issues surrounding the topic in question?
Exploring the intricacies of past and present ethical issues and dilemmas within medical sciences is paramount to developing well-rounded doctors and scientists. Ensuring students have this contextual knowledge will help them navigate a quickly evolving healthcare and research ecosystem in their future careers.
A current area of medicine requiring ethical scrutiny is genetic testing which, while it enables more personalised care, also raises concerns over privacy and security of individual genetic data. The risks of unauthorised access or discriminatory use of data pose an ethical challenge for genomics initiatives in medical research. As academics, we must raise awareness of these risks to students when considering the potential benefits of large-scale data collection for personalised healthcare. With data sharing now so easy, students must understand that patient data requires careful handling and protection. The primary focus must remain on the patient’s well-being and interests, ensuring commercial agendas do not compromise patient trust and confidentiality.
- Resource collection: Embracing diversity in higher education
- Address STEM inequality by reconceiving merit
- Resource collection: Decolonising the curriculum
Artificial intelligence (AI) in healthcare also raises ethical issues that need careful consideration. AI is being implemented across healthcare in numerous ways, from predicting disease risks and drug candidates using patient data analytics, to identifying neurological abnormalities from medical images. The AI algorithms are trained on large datasets to optimise their effectiveness and interact with pre-existing technologies. If these datasets are biased, the algorithms can perpetuate or even exacerbate existing healthcare disparities. For example, if training data predominantly represents specific demographics, which may be more readily available, AI could make inaccurate or discriminatory decisions for underrepresented groups.
Evidence of this has been seen in the detection and treatment of skin cancer, where images of white patients are largely used to train AI to spot melanoma, which risks missed diagnoses for black and ethnic minority patients and could worsen health outcomes underpinned by inequality.
Raising awareness of these barriers to the inclusive implementation of AI is crucial for students who are increasingly reliant on intelligent technology. By educating students on these matters, we can hope to train future researchers who do not exacerbate health inequalities when working with AI, and instead push for an inclusive and equitable approach.
5. Have you considered and explored health inequalities that exist in relation to your topic?
Exploring the health inequalities that underlie many diseases requires a multifaceted approach owing to their complexity. We need to acknowledge and raise awareness of systemic racism in healthcare. Maternal mortality rates for black and minority ethnic women continue to be significantly higher than for their white counterparts in the US, UK and several other Global North countries. This poses questions about why this remains the case despite global advances in maternal healthcare. We should discuss why black women’s voices are not heard and why they are under-treated for pain and underlying health conditions. While these conversations may be uncomfortable for students, the more knowledge and support they have from us as academics, the more freely they can engage in such discussions.
Inequalities also arise from socio-economic barriers that hinder access to cutting-edge treatments. Alzheimer’s, a fatal neurodegenerative disease that causes dementia, currently offers only symptomatic treatment. Neurological research suggests that early detection of Alzheimer’s pathology is crucial for effective treatment, as cognitive symptoms emerge years after preclinical neuronal degradation occurs. However, advanced methods like genetic testing and imaging require specialised training, unlike standard cognitive assessments. Therefore, demographics with limited education and healthcare access face worse prognoses if Alzheimer’s is detected late, leading to debilitating cognitive decline.
Despite growing mental health awareness across global communities, there remains a stigma within some minority groups that may hinder individuals from merely acknowledging potential disorders, let alone seeking treatment. Ethnic minorities are at a higher risk of experiencing stigmas around psychosis disorders, leading to potential exacerbation of symptoms in the absence of support. Classroom discussions around evidence-based insights into ideological disparities and reasons why mental health outcomes are worse within ethnic minority communities are important.
6. Have you explored, identified and recommended resources or research from diverse authors and regions to enable knowledge outside Eurocentric or West-centric perspectives?
Representation in literature has a powerful impact on students, fostering a sense of belonging and relatability to others’ success. Therefore, dismantling homogeneity in the academic literature we share with students is crucial to communicating scientific research and successes from a diverse body of people. To do this, we must look beyond the most popular or accessible textbooks and recognise that reputable sources extend far beyond West-centric countries, and accessibility does not equate to adequacy as a sole source. Diversification can go further with the use of “grey” and open-access literature that sits outside of traditional scientific publishing but can be just as useful for students. Revising citations and reading lists through the lens of diversification will enrich student learning and give academics a heightened awareness of the literature landscape.
We should challenge and nurture the future generation by promoting a wider breadth of knowledge through readings and research. Openly discussing and critically appraising sources will empower students with a sense of ownership over their educational journeys.
This two-part article employs academics as architects of transformation within medical education. The EDI checklist can help us shape informed medical professionals and future advocates for justice, inclusivity and progress.
Musarrat Maisha Reza is a senior lecturer in biomedical sciences, and Mia-Rose Gillison is a neuroscience student, both at the University of Exeter.
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