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创新评估策略:针对放射科研究生学员的基于图像的关键特征问题

Innovative assesment strategies: image based key feature questions for radiology postgraduate trainees.

作者信息

Naz Nasreen, Hussain K, Bari V, Rafiq Nida, Afzal A

机构信息

Dow Institute of Radiology, Dow University of Health Sciences, Karachi, Pakistan.

School of Health Professions Education, CMH Lahore Medical College and Institute of Dentistry, Lahore, Pakistan.

出版信息

BMC Med Educ. 2025 Apr 7;25(1):488. doi: 10.1186/s12909-024-06487-8.

Abstract

BACKGROUND

Innovative assessment strategies are essential for determining clinical understanding in the evolving field of health profession education. Key feature questions (KFQs) have been developed as assessment tools to assess the clinical understanding of students. The purpose of this study is to determine the effectiveness of image-based key feature questions (IBKFQs) compared with traditional multiple-choice questions (MCQs) in radiology examinations. Additionally, this study aims to determine the correlation between test scores obtained in both test formats.

METHOD

This quasi experimental, correlation study was conducted from September to December 2021 at a public medical university in Karachi, Pakistan. Thirty radiology residents from various training years participated in the study. Each resident completed a comprehensive written assessment comprising 50 MCQs and 50 IB-KFQs as part of their internal evaluation at the end of a module.

RESULTS

Out of thirty residents, 28 (93.3%) were females. The reliability score and Cronbach's alpha were 0.944 for the MCQs and 0.881 for the IB-KFQs. Spearman's correlation coefficient revealed a positive correlation between the MCQ and IB-KFQ scores (rho = 0.823, p < 0.001). The mean scores were similar for the IB-KFQs (29.24 ± 6.31) and MCQs (28.93 ± 11.41).

CONCLUSION

The findings of this study indicate that incorporating IB-KFQs alongside MCQs in written assessments of radiology residents is feasible. IB-KFQs offer a focused evaluation of critical skills such as film analysis, interpretation, and report writing. By complementing traditional MCQs, IB-KFQs enhance the assessment process.

摘要

背景

创新的评估策略对于确定健康职业教育不断发展领域中的临床理解至关重要。关键特征问题(KFQs)已被开发为评估学生临床理解的评估工具。本研究的目的是确定在放射学考试中,基于图像的关键特征问题(IBKFQs)与传统多项选择题(MCQs)相比的有效性。此外,本研究旨在确定两种考试形式获得的考试成绩之间的相关性。

方法

这项准实验性相关性研究于2021年9月至12月在巴基斯坦卡拉奇的一所公立医科大学进行。来自不同培训年份的30名放射科住院医师参与了该研究。作为模块结束时内部评估的一部分,每位住院医师完成了一项综合书面评估,其中包括50道MCQs和50道IB-KFQs。

结果

30名住院医师中,28名(93.3%)为女性。MCQs的可靠性得分和克朗巴哈系数为0.944,IB-KFQs为0.881。斯皮尔曼相关系数显示MCQ和IB-KFQ分数之间呈正相关(rho = 0.823,p < 0.001)。IB-KFQs(29.24 ± 6.31)和MCQs(28.93 ± 11.41)的平均分数相似。

结论

本研究结果表明,在放射科住院医师的书面评估中,将IB-KFQs与MCQs一起纳入是可行的。IB-KFQs提供了对诸如胶片分析、解读和报告撰写等关键技能的重点评估。通过补充传统的MCQs,IB-KFQs增强了评估过程。

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本文引用的文献

1
Teaching clinical reasoning to medical students: A brief report of case-based clinical reasoning approach.
J Educ Health Promot. 2024 Feb 26;13:42. doi: 10.4103/jehp.jehp_355_23. eCollection 2024.
2
Modern techniques of teaching and learning in medical education: a descriptive literature review.
MedEdPublish (2016). 2021 Jan 21;10:18. doi: 10.15694/mep.2021.000018.1. eCollection 2021.
3
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BMC Med Educ. 2023 Aug 25;23(1):609. doi: 10.1186/s12909-023-04525-5.
4
Differences in clinical reasoning between female and male medical students.
Diagnosis (Berl). 2022 Nov 18;10(2):100-104. doi: 10.1515/dx-2022-0081. eCollection 2023 May 1.
6
Characteristics of expert search behavior in volumetric medical image interpretation.
J Med Imaging (Bellingham). 2021 Jul;8(4):041208. doi: 10.1117/1.JMI.8.4.041208. Epub 2021 Jul 14.
8
Validation and perception of a key feature problem examination in neurology.
PLoS One. 2019 Oct 18;14(10):e0224131. doi: 10.1371/journal.pone.0224131. eCollection 2019.
9
Analysis of Perceptual Expertise in Radiology - Current Knowledge and a New Perspective.
Front Hum Neurosci. 2019 Jun 25;13:213. doi: 10.3389/fnhum.2019.00213. eCollection 2019.
10
Perceptual and Interpretive Error in Diagnostic Radiology-Causes and Potential Solutions.
Acad Radiol. 2019 Jun;26(6):833-845. doi: 10.1016/j.acra.2018.11.006. Epub 2018 Dec 14.

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