Rationale and Objectives
The aim of this study was to verify earlier work on learning and retaining chest radiographic anatomy introduced during preclinical education and revisited in the clinical years by comparing the initial clinical group to clinical students in a second setting who had no preclinical exposure.
Materials and Methods
One hundred thirty-seven clinical medical students were pretested and posttested on the same 10 items as were used in the first study. Scores on these 10-item standardized pretests and posttests were compared and assessed for statistical significance.
Results
Although the clinical students with preclinical exposure scored significantly higher on the pretest than the students without preclinical exposure (mean, 4.42 vs 4.09), there was a much larger significant difference in posttest improvement (mean, 8.65 vs 6.09). Isolating only the senior students to control for clinical experience (pretest, 4.42 vs 4.38; posttest, 8.65 vs 6.09) did not significantly affect outcomes.
Conclusions
Many medical schools are revising curricula and incorporating new models of learning. It may be important to recognize that older approaches such as memorization and testing are still necessary to start building the enormous “filing cabinet” of facts that must be cross-linked, revisited, and retrievable to contribute to a usable fund of medical knowledge.
As medical schools across the country examine educational methods and redesign curricula, it has become increasingly important to understand multiple aspects of medical students’ learning. How students acquire and retain knowledge and how they may then best transfer temporary or short-term “learned” or memorized acquisitions to longer term memory remain central to the process of acquiring knowledge and stimulating lifelong learning over increasingly longer and more complex careers. The preclinical years expose medical students to thousands (if not millions) of facts, many of which must be meaningfully integrated or “stored” to be retrievable over the clinical years and carried into future careers. In our ardor to advance education and learning and to embrace newer models of educational organization such as team-based learning and problem-based learning, it will be important to identify, preserve, and integrate some aspects of older learning models if they have demonstrable utility in the new paradigms.
We have previously demonstrated that preclinical second-year medical students (MS-IIs) required to participate in a radiology anatomy course could effectively memorize and learn certain specific chest radiographic landmarks but that 2 years later, their pretest recall of this information prior to starting a fourth-year elective was poor . However, although not adequately retained the first time, the early (MS-II) learning experience seemed to contribute to “rebound” learning, with the fourth-year medical students’ (MS-IV) end-of-rotation retest (posttest) scores higher than both the MS-IVs’ pretest scores and the original MS-IIs’ posttest scores .
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Materials and methods
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Results
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Table 1
Comparison of JHUSOM Clinical Student Performance and USUHS MS-IV Performance
JHUSOM MS-IIs (Q4), MS-IIIs, and MS-IVs USUHS MS-IVs Mean Difference_P_ Pretest overall score 4.09 ± 1.45 4.42 ± 1.34 0.33 .826 Sample size 133 555 Posttest overall score 6.66 ± 1.39 8.65 ± 1.24 1.99 <.001 Sample size 118 74
JHUSOM, Johns Hopkins University School of Medicine; MS-II, second-year medical student; MS-III, third-year medical student; MS-IV, fourth-year medical student; USUHS, Uniformed Services University of the Health Sciences.
Data are expressed as mean ± SD or as number.
Table 2
Comparison of JHUSOM MS-IV Performance and USUHS MS-IV Performance
JHUSOM MS-IVs USUHS MS-IVs Mean Difference_P_ Pretest overall score 4.38 ± 1.21 4.42 ± 1.34 0.04 .012 Sample size 59 555 Posttest overall score 6.09 ± 1.39 8.65 ± 1.24 2.56 <.001 Sample size 43 74
JHUSOM, Johns Hopkins University School of Medicine; MS-IV, fourth-year medical student; USUHS, Uniformed Services University of the Health Sciences.
Data are expressed as mean ± SD or as number.
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Discussion
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References
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