Evidence map›Paper›PMID 35524979›Full record

ReviewClinical anatomy (New York, N.Y.)2022

An approach to determining, delivering, and assessing essential course content in a medical human anatomy course.

John P McNamara, Michael F Nolan

Abstract readReview
In one paragraph

Review in Clinical anatomy (New York, N.Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

John P McNamaraDepartment of Basic Science Education, Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA.ORCID https://orcid.org/0000-0002-5178-7750
Michael F NolanDepartment of Basic Science Education, Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA.ORCID https://orcid.org/0000-0002-9177-4276

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Learning objectives typically indicate subject matter judged to be important or that represents essential material to be learned during a course. We report here on our efforts to identify essential course content and determine our effectiveness teaching and assessing this content in our preclinical human anatomy course. Using a consensus driven approach, we identified anatomical structures, relationships, and functional concepts judged to represent essential material in our unit on the thorax that students were expected to be familiar with. We then determined performance on specific examination questions that focused directly on the essential material. Thirty-seven of 48 students (77%) correctly answered all 34 of 51 questions that directly focused on content we defined as essential. The remaining 11 students answered the majority of these questions correctly. The overall mean score was 86% (range 61%-98%). Our review of student performance on the End of Block thorax examination confirmed our belief that we were successful in helping students learn material we defined as essential. We found the process described here to be helpful in defining essential content and for helping focus and improve medical education and learning assessment based on that material. We believe the idea of defining essential content that can be efficiently taught and effectively learned within a proscribed period of time is an important and necessary objective. We believe the approach used here might be successfully utilized in other programs in efforts aimed at quality improvement.

Indexed as

AnatomyEducation, MedicalEducation, Medical, UndergraduateStudents, MedicalAchievementCurriculumEducational MeasurementHumansLearninganatomymedical educationquality improvementthorax

Identifiers

PMID35524979
PMCPMC9545502

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.