Computer-based-Training (CBT): Fallorientiertes Lernen am PC mit dem CASUS/ProMediWeb-System

Fischer, Maike; Aulinger, B.; Baehring, Th.

doi:10.1055/s-2007-1024550

Cited by 11 publications

(5 citation statements)

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“…Elearning has also been utilized in residency and fellowship training programs with great success [4]. Even though computer-based training has been established as an effective and constructive learning module [2,6,9], there is still skepticism among students and instructors. Gorman et al have pointed out that "the future of medical education is no longer blood and guts, it is bits and bytes" [12].…”

Section: Introductionmentioning

confidence: 99%

An internet based learning tool in orthopaedic surgery: Preliminary experiences and results

Citak

Calafi

Kendoff

et al. 2009

THC

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Today universities can offer a variety of educational resources to their students through the internet. These may include lecture notes, PowerPoint presentations, or even an entire recording of a lecture in video format. At the Hannover Medical School (Hannover, Germany), the Trauma Surgery Department in collaboration with the Institute of Medical Informatics has developed an alternative method of "E-learning". We created a web-based multimedia resource center for Trauma Surgery using the Content-Management-System (CMS) Schoolbook application, which was initially developed by the Institute of Medical Informatics. The so called "Trauma Surgery Schoolbook" was first adopted in October of 2005 and has since been used and evaluated by medical students at our institution.The evaluation results for the academic year 2005/06 are reported in this paper. The majority of students enrolled in the Trauma Surgery rotation utilized the Schoolbook, which they regarded as a helpful and effective study tool. Our students embraced the possibility of being able to prepare for lectures and use the Schoolbook for independent home studying purposes. Over time, there was a steady increase in the utilization of the Schoolbook by the students from 67% in the first trimester to 93% in the third trimester. The majority of the surveyed students (79.6%) found the Schoolbook to be constructive and helpful. 8.1% did not have any opinion, and only 12.3% found it to not be helpful. The instructors also found this web-based training program to be both constructive and practical, and were able to utilize its multimedia components to complement their lectures.Overall, our experience with this computer-aided learning program demonstrated that web-based technologies can improve the quality of medical education, benefiting both the students and the instructors.

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Section: Introductionmentioning

confidence: 99%

An internet based learning tool in orthopaedic surgery: Preliminary experiences and results

Citak

Calafi

Kendoff

et al. 2009

THC

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“…Participants first completed a sociodemographic questionnaire. Subsequently they diagnosed the five simulated internal medicine (endocrine) clinical cases (Table 1 ) on the online based platform CASUS [ 23 ]. This platform (details are shown in the supplement Fig.…”

Section: Methodsmentioning

confidence: 99%

Insights into diagnostic errors in endocrinology: a prospective, case-based, international study

Frey,

Braun,

Handgriff

et al. 2023

BMC Med Educ

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Background Diagnostic errors in internal medicine are common. While cognitive errors have previously been identified to be the most common contributor to errors, very little is known about errors in specific fields of internal medicine such as endocrinology. This prospective, multicenter study focused on better understanding the causes of diagnostic errors made by general practitioners and internal specialists in the area of endocrinology. Methods From August 2019 until January 2020, 24 physicians completed five endocrine cases on an online platform that simulated the diagnostic process. After each case, the participants had to state and explain why they chose their assumed diagnosis. The data gathering process as well as the participants’ explanations were quantitatively and qualitatively analyzed to determine the causes of the errors. The diagnostic processes in correctly and incorrectly solved cases were compared. Results Seven different causes of diagnostic error were identified, the most frequent being misidentification (mistaking one diagnosis with a related one or with more frequent and similar diseases) in 23% of the cases. Other causes were faulty context generation (21%) and premature closure (17%). The diagnostic confidence did not differ between correctly and incorrectly solved cases (median 8 out of 10, p = 0.24). However, in incorrectly solved cases, physicians spent less time on the technical findings (such as lab results, imaging) (median 250 s versus 199 s, p < 0.049). Conclusions The causes for errors in endocrine case scenarios are similar to the causes in other fields of internal medicine. Spending more time on technical findings might prevent misdiagnoses in everyday clinical practice.

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“…Figure 2 shows the 2 × 2 × 4 study design: 2 (information format: probabilities v. natural frequencies) × 2 (visualization: double-tree v. net diagram) × 4 (contexts: minor aim of the study). To solve the tasks, the electronic case simulation platform CASUS 37 was used. First, each student completed a general sociodemographic questionnaire (age, gender, clinical semester, school examination grade, grade of the first medical examination, number of clinical clerkships, as potential control variables that may influence participants’ performance) and read an introductory text.…”

Section: Methodsmentioning

confidence: 99%

Improving Diagnostic Efficiency with Frequency Double-Trees and Frequency Nets in Bayesian Reasoning

Kunzelmann

Binder

Fischer³

et al. 2022

MDM Policy & Practice

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Background. Medical students often have problems with Bayesian reasoning situations. Representing statistical information as natural frequencies (instead of probabilities) and visualizing them (e.g., with double-trees or net diagrams) leads to higher accuracy in solving these tasks. However, double-trees and net diagrams (which already contain the correct solution of the task, so that the solution could be read of the diagrams) have not yet been studied in medical education. This study examined the influence of information format (probabilities v. frequencies) and visualization (double-tree v. net diagram) on the accuracy and speed of Bayesian judgments. Methods. A total of 142 medical students at different university medical schools (Munich, Kiel, Goettingen, Erlangen, Nuremberg, Berlin, Regensburg) in Germany predicted posterior probabilities in 4 different medical Bayesian reasoning tasks, resulting in a 3-factorial 2 × 2 × 4 design. The diagnostic efficiency for the different versions was represented as the median time divided by the percentage of correct inferences. Results. Frequency visualizations led to a significantly higher accuracy and faster judgments than did probability visualizations. Participants solved 80% of the tasks correctly in the frequency double-tree and the frequency net diagram. Visualizations with probabilities also led to relatively high performance rates: 73% in the probability double-tree and 70% in the probability net diagram. The median time for a correct inference was fastest with the frequency double tree (2:08 min) followed by the frequency net diagram and the probability double-tree (both 2:26 min) and probability net diagram (2:33 min). The type of visualization did not result in a significant difference. Discussion. Frequency double-trees and frequency net diagrams help answer Bayesian tasks more accurately and also more quickly than the respective probability visualizations. Surprisingly, the effect of information format (probabilities v. frequencies) on performance was higher in previous studies: medical students seem also quite capable of identifying the correct solution to the Bayesian task, among other probabilities in the probability visualizations. Highlights Frequency double-trees and frequency nets help answer Bayesian tasks not only more accurately but also more quickly than the respective probability visualizations. In double-trees and net diagrams, the effect of the information format (probabilities v. natural frequencies) on performance is remarkably lower in this high-performing sample than that shown in previous studies.

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Computer-based-Training (CBT): Fallorientiertes Lernen am PC mit dem CASUS/ProMediWeb-System

Cited by 11 publications

References 0 publications

An internet based learning tool in orthopaedic surgery: Preliminary experiences and results

An internet based learning tool in orthopaedic surgery: Preliminary experiences and results

Insights into diagnostic errors in endocrinology: a prospective, case-based, international study

Improving Diagnostic Efficiency with Frequency Double-Trees and Frequency Nets in Bayesian Reasoning

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