There is little doubt that the present results are important to curriculum (re)designers and those interested in the evaluation of curriculum reforms.

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Objective Training in physical diagnostic skills is an important part of undergraduate medical education. The objective of this study was to study the outcome of skills training at four medical schools.Context At the time of the study, three schools had a traditional lecture-based curriculum and one school had a problem-based learning curriculum with a longitudinal skills training programme. All schools offer extended exposure to clerkships 1 1 .Method A cross-sectional study in four medical schools was performed, using a written test of skills that has good correlation with actual student performance. The scores attained from four student groups were compared within and between the four medical schools. A total of 859 volunteer students from the later four years at each medical school participated in the study. ResultsThe mean scores in the traditional medical schools increased with the start of skill training and the hands-on experience offered during the clerkships.Students from the school with the longitudinal skills training programme and the problem-based learning approach had signi®cantly higher mean scores at the start of the clerkships, and maintained their lead in the subsequent clinical years.Conclusions Longitudinal skills training seems to offer the students a superior preparation for clerkships as well as in¯uencing the students' learning abilities during the clerkships. The effect of the problem-based learning approach, also related to the innovative philosophy of the curriculum, could not be accounted for.

Longitudinal skills training seems to offer the students a superior preparation for clerkships as well as influencing the students' learning abilities during the clerkships. The effect of the problem-based learning approach, also related to the innovative philosophy of the curriculum, could not be accounted for.

Rationale From general practitioners to academic staff, clinicians continue to have difficulties in applying clinical epidemiology in their everyday work. They do not fully understand the logical rules behind the numbers and they do not recognize these rules in their work. We present a new model where the pre-test and the post-test probabilities are converted to log10 of odds, and the likelihood ratio (LR) to its own log10. Methods Following Bayes' theorem, adding the log10LR to the log10 pre-test odds gives the log10 post-test odds, which can easily be represented on a logarithmic scale. In addition, by rounding the log10LR to half the unit, we create classes of discriminative power of tests, close to intuitive estimation. This model generates also a user-friendly diagram, adding considerably to the understanding of Bayes' theorem. We evaluated the effect of the rounding, the current use of the classical model and the acceptability of the new model. Results Rounding 10 disease characteristics to half the unit gives an absolute error of less than half a unit. After six explanations of Bayes' theorem, only 6/16 medical students were capable of answering simple questions about predictive value. When asked about weight of disease characteristics, no one of the 50 clinicians mentioned sensitivity, specificity, predictive value or LR. With the new model, more than 80% of trainees found medical decision making easier to understand and recognized the theory in their practice. Conclusions We conclude that our model of diagnostic clinical epidemiology offers a logical environment for an easy and rapid assessment of the evolution of disease probability with consecutive tests, providing a scientific format for 'qualitative' clinical estimations.