Evidence map›Paper›PMID 25039083›Full record

ArticleAdvances in physiology education2014

Mechanisms in cardiovascular diseases: how useful are medical textbooks, eMedicine, and YouTube?

Samy A Azer

Abstract readComparative StudyEvaluation Study
In one paragraph

Article in Advances in physiology education, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

1 author.

Samy A Azer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to assess the contents of medical textbooks, eMedicine (Medscape) topics, and YouTube videos on cardiovascular mechanisms. Medical textbooks, eMedicine articles, and YouTube were searched for cardiovascular mechanisms. Using appraisal forms, copies of these resources and videos were evaluated independently by three assessors. Most textbooks were brief in explaining mechanisms. Although the overall average percentage committed to cardiovascular mechanisms in physiology textbooks (n=7) was 16.1% and pathology textbooks (n=4) was 17.5%, there was less emphasis on mechanisms in most internal medicine textbooks (n=6), with a total average of 6.9%. In addition, flow diagrams explaining mechanisms were lacking. However, eMedicine topics (n=48) discussed mechanisms adequately in 22.9% (11 of 48) topics, and the percentage of content allocated to cardiovascular mechanisms was higher (15.8%, 46.2 of 292) compared with that of any internal medicine textbooks. Only 29 YouTube videos fulfilled the inclusion criteria. Of these, 16 YouTube were educationally useful, scoring 14.1 ± 0.5 (mean ± SD). The remaining 13 videos were not educationally useful, scoring 6.1 ± 1.7. The concordance between the assessors on applying the criteria measured by κ score was in the range of 0.55–0.96. In conclusion, despite the importance of mechanisms, most textbooks and You-Tube videos were deficient in cardiovascular mechanisms. eMedicine topics discussed cardiovascular mechanisms for some diseases, but there were no flow diagrams or multimedia explaining mechanisms. These deficiencies in learning resources could add to the challenges faced by students in understanding cardiovascular mechanisms.

Indexed as

Cardiovascular DiseasesInternetTextbooks as TopicVideo RecordingAccess to InformationBooks, IllustratedComprehensionComputer-Assisted InstructionEducation, MedicalHumansLearningMedical IllustrationTeaching

Identifiers

PMID25039083
PMCPMC4056178

What OpenQuestion holds

Textmetadata
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Registered trials

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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.