An Introductory, Computer-Based Learning Module for Interpreting Noncontrast Head Computed Tomography
Introduction New radiology and other residents must quickly assimilate a vast amount of anatomic and pathologic information when learning to interpret noncontrast head computed tomography (CT). No interactive, computer-based module using a search-pattern approach to provide new residents with the gr...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Association of American Medical Colleges
2018-06-01
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| Series: | MedEdPORTAL |
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| Online Access: | http://www.mededportal.org/doi/10.15766/mep_2374-8265.10721 |
| _version_ | 1819112886910320640 |
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| author | Kara Gaetke-Udager Zachary N London Sean Woolen Hemant Parmar Janet E. Bailey Daniel C. Barr |
| author_facet | Kara Gaetke-Udager Zachary N London Sean Woolen Hemant Parmar Janet E. Bailey Daniel C. Barr |
| author_sort | Kara Gaetke-Udager |
| collection | DOAJ |
| description | Introduction New radiology and other residents must quickly assimilate a vast amount of anatomic and pathologic information when learning to interpret noncontrast head computed tomography (CT). No interactive, computer-based module using a search-pattern approach to provide new residents with the groundwork for interpretation of noncontrast head CT previously existed. Methods We developed such a learning module using PowerPoint. First-year radiology residents completed the module prior to their neuroradiology rotation, and neurology residents completed it during orientation. Residents took 20-question pre- and posttests to assess knowledge and a postmodule survey. Each resident was randomized to one of two pretests and took the opposite as the posttest. Scores were collected over 5 years for radiology residents and 4 years for neurology residents. Statistical analysis of scores was performed using t tests. Results Forty-seven first-year radiology residents and 31 neurology residents completed the module and the pre- and posttests. Scores for all residents either stayed the same or increased, regardless of the order of the versions of the pre- or posttests; the mean score increase was 4 (p < .0001) out of 20. Radiology residents had higher mean scores than neurology residents on the pre- and posttests, which were statistically significant (p < .04 and .0004, respectively). Feedback on the survey was overwhelmingly positive. Discussion This computerized learning module is effective for teaching basic interpretation skills to new radiology and neurology residents. The module allows for asynchronous, programmed learning and the use of a step-by-step search-pattern approach. |
| first_indexed | 2024-12-22T04:20:38Z |
| format | Article |
| id | doaj.art-a2b46346567b4ca4876fab003f510b28 |
| institution | Directory Open Access Journal |
| issn | 2374-8265 |
| language | English |
| last_indexed | 2024-12-22T04:20:38Z |
| publishDate | 2018-06-01 |
| publisher | Association of American Medical Colleges |
| record_format | Article |
| series | MedEdPORTAL |
| spelling | doaj.art-a2b46346567b4ca4876fab003f510b282022-12-21T18:39:18ZengAssociation of American Medical CollegesMedEdPORTAL2374-82652018-06-011410.15766/mep_2374-8265.10721An Introductory, Computer-Based Learning Module for Interpreting Noncontrast Head Computed TomographyKara Gaetke-Udager0Zachary N London1Sean Woolen2Hemant Parmar3Janet E. Bailey4Daniel C. Barr5Assistant Professor, Department of Radiology, University of Michigan Medical School; Residency Program Director, Department of Radiology, University of Michigan Medical SchoolAssociate Professor, Department of Neurology, University of Michigan Medical School; Residency Program Director, Department of Neurology, University of Michigan Medical SchoolRadiology Resident, Department of Radiology, University of Michigan Medical SchoolProfessor, Department of Radiology, University of Michigan Medical SchoolProfessor, Department of Radiology, University of Michigan Medical School; Associate Chair of Education, Department of Radiology, University of Michigan Medical SchoolRadiologist, Veterans Administration Medical Center, Salisbury, NC; Assistant Chief of Imaging, Veterans Administration Medical Center, Salisbury, NCIntroduction New radiology and other residents must quickly assimilate a vast amount of anatomic and pathologic information when learning to interpret noncontrast head computed tomography (CT). No interactive, computer-based module using a search-pattern approach to provide new residents with the groundwork for interpretation of noncontrast head CT previously existed. Methods We developed such a learning module using PowerPoint. First-year radiology residents completed the module prior to their neuroradiology rotation, and neurology residents completed it during orientation. Residents took 20-question pre- and posttests to assess knowledge and a postmodule survey. Each resident was randomized to one of two pretests and took the opposite as the posttest. Scores were collected over 5 years for radiology residents and 4 years for neurology residents. Statistical analysis of scores was performed using t tests. Results Forty-seven first-year radiology residents and 31 neurology residents completed the module and the pre- and posttests. Scores for all residents either stayed the same or increased, regardless of the order of the versions of the pre- or posttests; the mean score increase was 4 (p < .0001) out of 20. Radiology residents had higher mean scores than neurology residents on the pre- and posttests, which were statistically significant (p < .04 and .0004, respectively). Feedback on the survey was overwhelmingly positive. Discussion This computerized learning module is effective for teaching basic interpretation skills to new radiology and neurology residents. The module allows for asynchronous, programmed learning and the use of a step-by-step search-pattern approach.http://www.mededportal.org/doi/10.15766/mep_2374-8265.10721Learning ModuleNoncontrast Head Computed TomographySearch Pattern |
| spellingShingle | Kara Gaetke-Udager Zachary N London Sean Woolen Hemant Parmar Janet E. Bailey Daniel C. Barr An Introductory, Computer-Based Learning Module for Interpreting Noncontrast Head Computed Tomography MedEdPORTAL Learning Module Noncontrast Head Computed Tomography Search Pattern |
| title | An Introductory, Computer-Based Learning Module for Interpreting Noncontrast Head Computed Tomography |
| title_full | An Introductory, Computer-Based Learning Module for Interpreting Noncontrast Head Computed Tomography |
| title_fullStr | An Introductory, Computer-Based Learning Module for Interpreting Noncontrast Head Computed Tomography |
| title_full_unstemmed | An Introductory, Computer-Based Learning Module for Interpreting Noncontrast Head Computed Tomography |
| title_short | An Introductory, Computer-Based Learning Module for Interpreting Noncontrast Head Computed Tomography |
| title_sort | introductory computer based learning module for interpreting noncontrast head computed tomography |
| topic | Learning Module Noncontrast Head Computed Tomography Search Pattern |
| url | http://www.mededportal.org/doi/10.15766/mep_2374-8265.10721 |
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