Jeddi Fatemeh Rangraz, Momen-Heravi Mansooreh, Farrahi Razieh, Nabovati Ehsan, Akbari Hossein, Khodabandeh Maryam Edalati
Health Information Management Research Center, Kashan University of Medical Sciences, Kashan, Iran.
Infectious Diseases Research Center, Kashan University of Medical Sciences, Kashan, Iran.
BMC Med Educ. 2024 Dec 18;24(1):1463. doi: 10.1186/s12909-024-06453-4.
Acute respiratory infections are a common presentation in clinical practice and medical interns must learn proper diagnosis and antibiotic prescribing. Traditional lecture-based teaching may not provide sufficient opportunities for students to apply their knowledge in realistic scenarios, whereas computer case-based simulations offer an alternative approach that allows active learning and decision-making in simulated patient cases. This study investigated the effectiveness of computer case-based reasoning simulation versus traditional lectures for medical interns teaching of diagnosis and antibiotic prescribing for acute respiratory infections.
This comparative quasi-experimental study was conducted from 2020 to 2022 in the Department of Infectious Diseases at Shahid Beheshti Hospital, affiliated to Kashan University of Medical Sciences. The samples were selected using a convenience method and assigned to the intervention and control groups using a permuted block randomization approach. Over a period of ten months (Each month, an average of eight medical interns), a total of 40 medical interns received traditional lecture-based teaching, while another 40 medical interns were taught using a Computer Case-based Reasoning simulation. The medical interns' knowledge in both groups was assessed using pre- and post-tests. The collected data from the pre- and post-tests were then analyzed statistically using paired t-tests, independent t-tests, and ANCOVA.
The posttest scores of the medical interns in both groups were significantly higher than the pretest scores (P < 0.001). No statistically significant differences were observed between the two teaching methods regarding mean knowledge gains in diagnoses and antibiotic prescribing practices. (P > 0.21). The results of the ANCOVA, after controlling for pre-test scores, showed no statistically significant difference between the two teaching methods in their effect on medical interns' diagnostic and antibiotic prescribing performance (P > 0.33).
The study found that both computer case-based reasoning simulation and traditional lectures were effective in improving medical interns' knowledge of diagnosis and antibiotic prescribing practices for acute respiratory infections. However, no statistically significant differences were observed between the two teaching methods. Thus, computer- based simulation could replace face-to-face teaching when this method is impractical or computerized methods are more cost-effective.
急性呼吸道感染是临床实践中的常见病症，医学实习生必须学会正确诊断和合理使用抗生素。传统的基于讲座的教学可能无法为学生提供足够的机会在实际场景中应用知识，而基于计算机病例的模拟提供了一种替代方法，允许在模拟患者病例中进行主动学习和决策。本研究调查了基于计算机病例推理模拟与传统讲座在医学实习生急性呼吸道感染诊断和抗生素处方教学中的有效性。
这项比较性准实验研究于2020年至2022年在库姆医科大学附属的沙希德·贝赫什提医院传染病科进行。样本采用便利抽样法选取，并使用置换区组随机化方法分配到干预组和对照组。在十个月的时间里（每月平均有八名医学实习生），共有40名医学实习生接受基于传统讲座的教学，另外40名医学实习生采用基于计算机病例推理的模拟进行教学。两组医学实习生的知识水平通过前后测试进行评估。然后，使用配对t检验、独立t检验和协方差分析对前后测试收集的数据进行统计分析。
两组医学实习生的后测分数均显著高于前测分数（P < 0.001）。在诊断和抗生素处方实践的平均知识增益方面，两种教学方法之间未观察到统计学上的显著差异（P > 0.21）。在控制前测分数后，协方差分析结果显示，两种教学方法对医学实习生诊断和抗生素处方表现的影响没有统计学上的显著差异（P > 0.33）。
研究发现，基于计算机病例推理模拟和传统讲座在提高医学实习生急性呼吸道感染诊断和抗生素处方实践知识方面均有效。然而，两种教学方法之间未观察到统计学上的显著差异。因此，当面对面教学不切实际或计算机化方法更具成本效益时，基于计算机的模拟可以取代面对面教学。
