Medicine

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This repository contains the published and unpublished research of the Faculty of Medicine by the staff members of the faculty

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    Medical students' and trainees' country-by-gender profiles: Hofstede's Cultural Dimensions across sixteen diverse countries
    (Frontiers Media S.A, 2022) Monrouxe, L.V.; Chandratilake, M.; Chen, J.; Chhabra, S.; Zheng, L.; Costa, P.S.; Lee, Y.M.; Karnieli-Miller, O.; Nishigori, H.; Ogden, K.; Pawlikowska, T.; Riquelme, A.; Sethi, A.; Soemantri, D.; Wearn, A.; Wolvaardt, L.; Yusoff, M.S.B.; Yau, S.Y.
    Purpose: The global mobility of medical student and trainee populations has drawn researchers' attention to consider internationalization in medical education. Recently, researchers have focused on cultural diversity, predominately drawing on Hofstede's cross-cultural analysis of cultural dimensions from general population data to explain their findings. However, to date no research has been specifically undertaken to examine cultural dimensions within a medical student or trainee population. This is problematic as within-country differences between gender and professional groups have been identified within these dimensions. We address this gap by drawing on the theoretical concept of national context effects: specifically Hofstede's six-dimensional perspective. In doing so we examine medical students' and trainees' country profiles across dimensions, country-by-gender clustering, and differences between our data and Hofstede's general population data. Methods: We undertook a cross-cultural online questionnaire study (eight languages) containing Hofstede's 2013 Values Survey. Our questionnaire was live between 1st March to 19th Aug 2018, and December 2018 to mitigate country holiday periods. We recruited undergraduate medical students and trainees with at least 6-months' clinical training using school-specific methods including emails, announcements, and snowballing. Results: We received 2,529 responses. Sixteen countries were retained for analyses (n = 2,307, 91%): Australia, Chile, China, Hong Kong, India, Indonesia, Ireland, Israel, Japan, Malaysia, New Zealand, Pakistan, South Africa, South Korea, Sri-Lanka, Taiwan. Power distance and masculinity are homogenous across countries. Uncertainty avoidance shows the greatest diversity. We identified four country clusters. Masculinity and uncertainty are uncorrelated with Hofstede's general population data. Conclusions: Our medical student and trainee data provides medical education researchers with more appropriate cultural dimension profiles than those from general population data. Country cluster profiles stimulate useful hypotheses for further research, especially as patterning between clusters cuts across traditional Eastern-Western divides with national culture being stronger than gendered influences. The Uncertainty dimension with its complex pattern across clusters is a particularly fruitful avenue for further investigation.
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    A Scoping review of clinical reasoning research with Asian healthcare professionals
    (Kluwer Academic Publishers, 2021) Lee, C.Y.; Jenq, C.C.; Chandratilake, M.; Chen, J.; Chen, M.M.; Nishigori, H.; Wajid, G.; Yang, P.H.; Yusoff, M.S.B.; Monrouxe, L.
    ABSTRACT: Clinical reasoning is the thought process that guides practice. Although a plethora of clinical reasoning studies in healthcare professionals exists, the majority appear to originate from Western cultures. A scoping review was undertaken to examine clinical reasoning related research across Asian cultures. PubMed, SciVerse Scopus, Web of Science and Airiti Library databases were searched. Inclusion criteria included full-text articles published in Asian countries (2007 to 2019). Search terms included clinical reasoning, thinking process, differential diagnosis, decision making, problem-based learning, critical thinking, healthcare profession, institution, medical students and nursing students. After applying exclusion criteria, n = 240 were included in the review. The number of publications increased in 2012 (from 5%, n = 13 in 2011 to 9%, n = 22) with a steady increase onwards to 12% (n = 29) in 2016. South Korea published the most articles (19%, n = 46) followed by Iran (17%, n = 41). Nurse Education Today published 11% of the articles (n = 26), followed by BMC Medical Education (5%, n = 13). Nursing and Medical students account for the largest population groups studied. Analysis of the articles resulted in seven themes: Evaluation of existing courses (30%, n = 73) being the most frequently identified theme. Only seven comparative articles showed cultural implications, but none provided direct evidence of the impact of culture on clinical reasoning. We illuminate the potential necessity of further research in clinical reasoning, specifically with a focus on how clinical reasoning is affected by national culture. A better understanding of current clinical reasoning research in Asian cultures may assist curricula developers in establishing a culturally appropriate learning environment. KEYWORDS: Asia; Clinical reasoning; Health professions; Scoping review.
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    Genetic drivers of heterogeneity in type 2 diabetes pathophysiology
    (Nature Publishing Group, 2024) Suzuki, K.; Hatzikotoulas, K.; Southam, L.; Taylor, H.J.; Yin, X.; Lorenz, K.M.; Mandla, R.; Huerta-Chagoya, A.; Melloni, G.E.M.; Kanoni, S.; Rayner, N.W.; Bocher, O.; Arruda, A.L.; Sonehara, K.; Namba, S.; Namba, S.S.K.; Preuss, M.H.; Petty, L.E.; Schroeder, P.; Vanderwerff, B.; Kals, M.; Bragg. F.; Lin, K.; Guo, X.; Zhang, W.; Yao, J.; Kim, Y.J.; Graff, M.; Takeuchi, F.; Nano, J.; Lamri, A.; Nakatochi, M.; Moon, S.; Scott, R.A.; Cook, J.P.; Lee, J.J.; Pan, I.; Taliun, D.; Parra, E.J.; Chai. J.F.; Bielak, L.F.; Tabara, Y.; Hai, Y.; Thorleifsson, G.; Grarup, N.; Sofer, T.; Wuttke, M.; Sarnowski, C.; Gieger, C.; Nousome, D.; Trompet, S.; Kwak, S.H.; Long, J.; Sun, M.; Tong, L.; Chen, W.M.; Nongmaithem, S.S.; Noordam, R.; Lim, V.J.Y.; Tam, C.H.T.; Joo, Y.Y.; Chen, C.H.; Raffield, L.M.; Prins, B.P.; Nicolas, A.; Yanek, L.R.; Chen, G.; Brody, J.A.; Kabagambe, E.; An, P.; Xiang, A.H.; Choi, H.S.; Cade, B.E.; Tan, J.; Broadaway, K.A.; Williamson, A.; Kamali, Z.; Cui, J.; Thangam, M.; Adair, L.S.; Adeyemo, A.; Aguilar-Salinas, C.A.; Ahluwalia, T.S.; Anand, S.S.; Bertoni, A.; Bork-Jensen, J.; Brandslund, I.; Buchanan, T.A.; Burant, C.F.; Butterworth, A.S.; Canouil, M.; Chan, J.C.N.; Chang, L.C.; Chee, M.L.; Chen, J.; Chen, S.H.; Chen, Y.T.; Chen, Z.; Chuang, L.M.; Cushman, M.; Danesh, J.; Das, S.K.; de Silva, H.J.; Dedoussis, G.; Dimitrov, L.; Doumatey, A.P.; Du, S.; Duan, Q.; Eckardt, K.U.; Emery, L.S.; Evans, D.S.; Evans, M.K.; Fischer, K.; Floyd, J.S.; Ford, I.; Franco, O.H.; Frayling, T.M.; Freedman, B.I.; Genter, P.; Gerstein, H.C.; Giedraitis, V.; González-Villalpando, C.; González-Villalpando, M.E.; Gordon-Larsen, P.; Gross, M.; Guare, L.A.; Hackinger, S.; Hakaste, L.; Han, S.; Hattersley, A.T.; Herder, C.; Horikoshi, M.; Howard, A.; Hsueh, W.; Huang, M.; Huang, W.; Hung, Y.; Hwang, M.Y.; Hwu, C.; Ichihara, S.; Ikram, M.A.; Ingelsson, M.; Islam, M.T.; Isono, M.; Jang, H.; Jasmine, F.; Jiang, G.; Jonas, J.B.; Jørgensen, T.; Kamanu, F.K.; Kandeel, F.R.; Kasturiratne, A.; Katsuya, T.; Kaur, V.; Kawaguchi,T.; Keaton, J.M.; Kho, A.N.; Khor, C.; Kibriya, M.G.; Kim, D.; Kronenberg, F.; Kuusisto , J.; Läll, K.; Lange, L.A.; Lee, K.M.; Lee, M.; Lee, N.R.; Leong, A.; Li, L.; Li, Y.; Li-Gao, R.; Ligthart, S.; Lindgren, C.M.; Linneberg, A.; Liu, C.; Liu, J.; Locke, A.E.; Louie, T.; Luan, J.; Luk, A.O.; Luo, X.; Lv, J.; Lynch, J.A.; Lyssenko, V.; Maeda, S.; Mamakou, V.; Mansuri, S.R.; Matsuda, K.; Meitinger, T.; Melander, O.; Metspalu, A.; Mo, H.; Morris, A.D.; Moura, F.A.; Nadler, J.L.; Nalls, M.A.; Nayak, U.; Ntalla, I.; Okada, Y.; Orozco, L.; Patel, S.R.; Patil, S.; Pei, P.; Pereira, M.A.; Peters, A.; Pirie, F.J.; Polikowsky, H.G.; Porneala, B.; Prasad, G.; Rasmussen-Torvik, L.J.; Reiner, A.P.; Roden, M.; Rohde, R.; Roll, K.; Sabanayagam, C.; Sandow, K.; Sankareswaran , A.; Sattar,N.; Schönherr, S.; Shahriar, M.; Shen , B.; Shi, J.; Shin, D.M.; Shojima, N.; Smith, J.A.; So, W.Y.; Stančáková, A.; Steinthorsdottir, V.; Stilp, A.M.; Strauch, K.; Taylor, K.D.; Thorand, B.; Thorsteinsdottir, U.; Tomlinson, B.; Tran, T.C.; Tsai, F.; Tuomilehto, J.; Tusie-Luna, T.; Udler , M.S.; Valladares-Salgado, A.; Dam, R.M.V.; Klinken, J.B.V.; Varma, R.; Wacher-Rodarte, N.; Wheeler,E.; Wickremasinghe, A.R.; Dijk, K.W.V.; Witte, D.R.; Yajnik, C.S.; Yamamoto, K.; Yamamoto, K.; Yoon, K.; Yu, C.; Yuan, J.; Yusuf, S.; Zawistowski, M.; Zhang, L.; Zheng, W.; Raffel, L.J.; Igase, M.; Ipp, E.; Redline, S.; Cho, Y.S.; Lind, L.; Province, M.A.; Fornage, .M.; Hanis, C.L.; Ingelsson, E.; Zonderman, A.B.; Psaty, B.M.; Wang, Y.; Rotimi, C.N.; Becker,D.M.; Matsuda,F.; Liu, Y.; Yokota,M.; Kardia, S.L.R.; Peyser, P.A.; Pankow, J.S.; Engert, J.C.; Bonnefond, A.; Froguel, P.; Wilson, J.G.; Sheu, W.H.H.; Wu, J.; Hayes, M.G.; Ma, R.C.W.; Wong, T.; Mook-Kanamori, D.O.; Tuomi, T.; Chandak, G.R.; Collins, F.S.; Bharadwaj, D.; Paré, G.; Sale, M.M.; Ahsan, H.; Motala, A.A.; Shu , X.; Park, K.; Jukema, J.W.; Cruz, M.; Chen, Y.I.; Rich, S.S.; McKean-Cowdin, R.; Grallert, H.; Cheng, C.; Ghanbari,M.; Tai , E.; Dupuis, J.; Kato, N.; Laakso, M.; Köttgen, A.; Koh, W.; Bowden, D.W.; Palmer, C.N.A.; Kooner, J.S.; Kooperberg, C.; Liu, S.; North, K.E.; Saleheen, D.; Hansen, T.; Pedersen, O.; Wareham, N.J.; Lee, J.; Kim, B.; Millwood , I.Y.; Walters, R.G.; Stefansson, K.; Ahlqvist, E.; Goodarzi, M.O.; Mohlke, K.L.; Langenberg, C.; Haiman, C.A.; Loos, R.J.F.; Florez, J.C.; Rader, D.J.; Ritchie, M.D.; Zöllner, S.; Mägi, R.; Marston, N.A.; Ruff, C.T.; Heel , D.A.V.; Finer, S.; Denny, J.C.; Yamauchi, T.; Kadowaki, T.; Chambers, J.C.; Ng, M.C.Y.; Sim, X.; Below, J.E.; Tsao, P.S.; Chang, K.; McCarthy, M.I.; Meigs, J.B.; Mahajan, A.; Spracklen, C.N.; Mercader, J.M.; Boehnke, M.; Rotter, J.I.; Vujkovic, M.; Voight, B.F.; Morris, A.P.; Zeggini, E.
    Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.
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