Quantitative bias analysis can accurately estimate the magnitude and direction of potential biases, thereby helping researchers assess the robustness of findings against potential biases. To enhance students' professional competencies, the School of Public Health in Fudan University has developed a course on epidemiological bias analysis techniques since 2013 to master's and doctoral students in medical-related disciplines. The curriculum integrates theoretical lectures, case studies, and computer-based operations to combine theoretical knowledge with practical application. Analysis of 75 student presentations and take-home exams from 2020 to 2024 indicated that most students could accurately identify bias types, construct causal diagrams, and appropriately apply quantitative bias analysis methods. Examination performance was strongly associated with students' backgrounds in epidemiology and biostatistics. Results from an anonymous online teaching evaluation survey conducted in 2024 (26 valid responses) indicated overall satisfaction score of 9.0±1.3, self-rated theoretical mastery score of 8.3±1.4, self-rated technical application score of 7.8±1.7, and 10 students (38.4%) reported plans to incorporate bias analysis into their research projects or theses. This course has demonstrated positive outcomes in improving students' abilities in bias analysis, though practical application skills warrant further strengthening. Future course development will increase practical exercises and refine course content to continuously improve teaching quality.
Ding Yingying
,
Yu Yongfu
,
Zheng Yingjie
. Curriculum development and exploration of epidemiological bias analysis techniques[J]. Chinese Journal of Medical Education, 2025
, 45(11)
: 822
-826
.
DOI: 10.3760/cma.j.cn115259-20241231-01381
[1] Fox MP, MacLehose RF,Lash TL. Applying quantitative bias analysis to epidemiologic data[M]. New York:Springer,2021:13-32.
[2] Brown JP, Hunnicutt JN, Ali MS, et al. Quantifying possible bias in clinical and epidemiological studies with quantitative bias analysis: common approaches and limitations[J]. BMJ, 2024,385:e076365. DOI: 10.1136/bmj-2023-076365.
[3] Petersen JM, Ranker LR, Barnard-Mayers R, et al. A systematic review of quantitative bias analysis applied to epidemiological research[J]. Int J Epidemiol, 2021,50(5):1708-1730. DOI: 10.1093/ije/dyab061.
[4] Davis LE, Banack HR, Calderon-Anyosa R, et al. Probabilistic bias analysis for exposure misclassification of household income by neighbourhood in a cohort of individuals with colorectal cancer[J]. Int J Epidemiol, 2024,53(6): dyae135.DOI: 10.1093/ije/dyae135.
[5] Shi L, Zhu Q, Wang Y, et al. Incident dementia and long-term exposure to constituents of fine particle air pollution: a national cohort study in the United States[J]. Proc Natl Acad Sci USA, 2023,120(1):e2211282119. DOI: 10.1073/pnas.2211282119.
[6] Pearl J. Probabilistic reasoning in intelligence systems[M].San Francisco, CA:Morgan Kaufmann,1988:1-466.
[7] Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research[J]. Epidemiology, 1999,10(1):37-48.
[8] University of Toronto. Advanced analytic methods for bias in epidemiologic studies[EB/OL]. https://www.dlsph.utoronto.ca/course/advanced-analytic-methods-for-bias-in-epidemiologic-studies/.
[9] Fox M. Quantitative bias analysis methods for epidemiologic research[EB/OL].[2025-07-11].https://www.bu.edu/academics/sph/courses/sph-ep-861/.
[10] Mora A, Kiang C, Lash T. Applied quantitative bias analysis to epidemiological research[EB/OL].[2025-07-11]. https://sph.emory.edu/degrees-programs/msph/epidemiology/key-courses.
[11] Hughes R,Kawabata E. Introduction to quantitative bias analysis[EB/OL].[2025-07-11].https://www.bristol.ac.uk/medical-school/study/short-courses/courses/quantitative-bias-analysis/.
[12] Blakely T, Aitken Z. Contemporary epidemiology[EB/OL].[2025-07-11]. https://ecommerce.unimelb.edu.au/aea-contemporary-epidemiology-course-1.
[13] Henan M.Causal diagrams[EB/OL].[2025-07-11]. https://pll.harvard.edu/course/causal-diagrams-draw-your-assumptions-your-conclusions.
[14] Shahar E, Shahar DJ. Causal diagrams and three pairs of biases[M]//Lunet N. Epidemiology-current perspectives on research and practice. Rijeka: IntechOpen, 2012:31-62.
