Trial reportJournal of the American Medical Informatics Association : JAMIA
Predictors of student success in graduate biomedical informatics training: introductory course and program success.
Trial report in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Underrepresented racial minorities in biomedical informatics doctoral programs: graduation trends and academic placement (2002-2017).Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Demystifying Graduate School: Navigating a PhD in Neuroscience and Beyond.Journal of undergraduate neuroscience education : JUNE : a publication of FUN, Faculty for Undergraduate Neuroscience · 2018Article
- Sequential incoherence in a multi-party synchronous computer mediated communication for an introductory Health Informatics course.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2010Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
objectiveTo predict student performance in an introductory graduate-level biomedical informatics course from application data.
designA predictive model built through retrospective review of student records using hierarchical binary logistic regression with half of the sample held back for cross-validation. The model was also validated against student data from a similar course at a second institution. MEASUREMENTS: Earning an A grade (Mastery) or a C grade (Failure) in an introductory informatics course.
resultsThe authors analyzed 129 student records at the University of Texas School of Health Information Sciences at Houston (SHIS) and 106 at Oregon Health and Science University Department of Medical Informatics and Clinical Epidemiology (DMICE). In the SHIS cross-validation sample, the Graduate Record Exam verbal score (GRE-V) correctly predicted Mastery in 69.4%. Undergraduate grade point average (UGPA) and underrepresented minority status (URMS) predicted 81.6% of Failures. At DMICE, GRE-V, UGPA, and prior graduate degree significantly correlated with Mastery. Only GRE-V was a significant independent predictor of Mastery at both institutions. There were too few URMS students and Failures at DMICE to analyze. Course Mastery strongly predicted program performance defined as final cumulative GPA at SHIS (n=19, r=0.634, r2=0.40, p=0.0036) and DMICE (n=106, r=0.603, r2=0.36, p<0.001).
conclusionsThe authors identified predictors of performance in an introductory informatics course including GRE-V, UGPA and URMS. Course performance was a very strong predictor of overall program performance. Findings may be useful for selecting students for admission and identifying students at risk for Failure as early as possible.
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