Data-Driven Model Validation Across Dimensions

Data-driven model validation across dimensions in mathematical and computational biology assumptions are often made (e.g., symmetry) to reduce the problem from three spatial dimensions (3D) to two (2D). However, some experimental datasets, such as cell counts obtained via flow cytometry, represent the entire 3D biological object. For purpose of model calibration and validation, it is sometimes necessary to compare these biological datasets with model outputs. We propose a methodology for scaling 2D model outputs to compare with 3D experimental datasets, and we discuss the application of this methodology to two examples: agent-based models of granuloma formation and skeletal muscle tissue. The accuracy of the method is evaluated in artificially generated scenarios.

Interval vs Massed Training

Objective

To compare 2 different training paradigms, massed vs interval training, when novice students learn a surgical procedure, myringotomy with ventilation tube insertion, on a validated surgical simulator.

Study Design

Medical students were randomized into 2 training groups: the interval group (n = 19) was trained to perform the procedure in 5 trials/d over 3 days, and the massed group (n = 21) was trained to perform the procedure in 15 trials all in 1 session. One week later, all students were tested in 5 additional final trials. Pre- and posttest surveys were administered.

Setting

Academic medical center.

Subjects and Methods

Forty medical students: 19 students in the interval group were compared with 21 students in the massed group. Time to complete the procedure and number and type of error made were recorded and compared between groups. Pre- and poststudy surveys examined confidence levels working under a microscope and with the procedure.

Results

Students in both groups had a significant decrease in time between practice and final trials. In the final 5 trials, there was no difference in average time to complete the procedure between the massed and interval training groups. No difference was observed in the number of errors committed per trial between initial and final trials (both groups) or between massed and interval training groups. The students’ confidence levels significantly increased across the trials, regardless of group.

Conclusion

Surgical training improves proficiency, but method of training had little impact on proficiency in performing a simulated surgical procedure in this setting.