Research To Read, Edition 1.
This newsletter is my 2025 resolution in action: to make reading medical research a consistent habit. Just like any muscle that needs regular exercise, the only way to strengthen this practice is by doing it—repeatedly.
That’s the motivation behind Research to Read. It's a way for me to share the research I’m diving into, while also expanding my own knowledge. And I’m inviting my fellow medicos to join me on this journey. We all stand to benefit from staying informed and sharpening our understanding of the latest studies in our field.
So, let’s get into the research, together!
Before you dive in:
I came across this beneficial blog post by James Lee on Medium, How to Read Academic Papers without Freaking Out in which he wrote, “...reading academic papers can be quite the headache, especially for the uninitiated”. So he has shared some handy tips for effectively approaching academic papers and reading research, which I highly recommend checking out.
Here’s my list of research papers to read:
A Scoping Review of Professional Identity Formation in Undergraduate Medical Education
Sarraf-Yazdi, S., Teo, .N., How, A.E.H. et al. A Scoping Review of Professional Identity Formation in Undergraduate Medical Education. J GEN INTERN MED 36, 3511–3521 (2021). https://doi.org/10.1007/s11606-021-07024-9
This paper discusses PIF, a.k.a. Professional Identity Formation, among medical students by systematically reviewing 76 full-text articles. What I found interesting about this research was it’s usage of Krishna and Alsuwaigh’s Ring Theory of Personhood (RToP), which consists of four rings, and its application of Krishna’s systematic evidence-based approach (SEBA).
Read it here: https://link.springer.com/article/10.1007/s11606-021-07024-9#citeas
2. Heuristic decision making in medicine
Marewski JN, Gigerenzer G. Heuristic decision making in medicine. Dialogues Clin Neurosci. 2012 Mar;14(1):77-89. doi: 10.31887/DCNS.2012.14.1/jmarewski. PMID: 22577307; PMCID: PMC3341653.
Heuristics is a simple decision strategy that ignores part of the available information and focuses on the few relevant predictors to simplify and efficiently make decisions. This paper dives into how applying this in healthcare would work, the benefits, and potential future applications.
Read it here: https://pmc.ncbi.nlm.nih.gov/articles/PMC3341653/
3. ‘Immunising’ physicians against availability bias in diagnostic reasoning: a randomised controlled experiment
Mamede S, de Carvalho-Filho MA, de Faria RMD, et al‘Immunising’ physicians against availability bias in diagnostic reasoning: a randomised controlled experiment BMJ Quality & Safety 2020;29:550-559.
“Immunisation” interventions aim to increase physicians’ knowledge of a cluster of related diseases and decrease the rates of diagnostic errors under circumstances known to induce error. This study finds that non-immunised physicians incorrectly gave that diagnosis to vignettes of different (though similar) diseases twice more frequently than immunised physicians and that the diagnostic accuracy decreased by 40% between immunised and non-immunised physicians.
So, this study highlights the importance of implementing initiatives and learning curricula that will allow students and residents to compare and contrast alternative diagnoses for similar-looking diseases.
Read it here: https://qualitysafety.bmj.com/content/29/7/550
4. Beginnings of Artificial Intelligence in Medicine (AIM): Computational Artifice Assisting Scientific Inquiry and Clinical Art – with Reflections on Present AIM Challenges
Kulikowski CA. Beginnings of Artificial Intelligence in Medicine (AIM): Computational Artifice Assisting Scientific Inquiry and Clinical Art - with Reflections on Present AIM Challenges. Yearb Med Inform. 2019 Aug;28(1):249-256. doi: 10.1055/s-0039-1677895. Epub 2019 Apr 25. PMID: 31022744; PMCID: PMC6697545.
This article provides insight into the history and origins of AI in the medical field from the 1950s to the present, highlighting the major innovations and milestones that have led to the current state of AI use in healthcare.
Clinical AI is the majority focus of the article, but it also touches upon regulation, governance and the ethics of AI use in healthcare.
Read it here: https://pmc.ncbi.nlm.nih.gov/articles/PMC6697545/
This was a completely new domain for me a while back, so I’d like to recommend this video to better understand and learn more about the mind-boggling world of AI: Explained: The conspiracy to make AI seem harder than it is! By Gustav Söderström https://www.youtube.com/watch?v=2eWuYf-aZE4
…and that brings us to the end of our first-ever Research to Read!!
I hope you enjoyed it and look forward to reading more research along with me, where I’ll be diving into research rooted in different medical specialities :)
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