Evidence map›Paper›PMID 35517832›Full record

ArticleBMJ simulation & technology enhanced learning2017

Classifying simulation-based studies using the description, justification and clarification framework: a review of simulation conference abstracts.

Alastair Campbell Graham, Helen Rachael Church, Deborah G Murdoch-Eaton

Abstract read
In one paragraph

Article in BMJ simulation & technology enhanced learning, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. It is time to celebrate the importance of evaluation in medical education.International journal of medical education · 2018
    Article
  3. An overview of realist evaluation for simulation-based education.Advances in simulation (London, England) · 2018
    Article
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

3 authors.

Alastair Campbell GrahamAcademic Unit of Medical Education, The Medical School, The University of Sheffield, Sheffield, UK.
Helen Rachael ChurchAcademic Unit of Medical Education, The Medical School, The University of Sheffield, Sheffield, UK.ORCID 0000-0003-0455-9576
Deborah G Murdoch-EatonAcademic Unit of Medical Education, The Medical School, The University of Sheffield, Sheffield, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Simulation-based medical education (SBME) is an accepted learning methodology with an ever-expanding evidence base. Concerns have been expressed that research output in SBME lacks explicit links to educational theory. Using the 'Description, Justification and Clarification' framework we have investigated the extent to which SBME conference abstracts declare the educational theory underpinning their studies. Methods: Abstracts from four major international SBME conferences (for 2014 and 2015) were reviewed. Abstracts were classified using the framework offered by Cook Results: We reviewed 1398 conference abstracts which we classified as Description 54.4%, Justification 36.3% and Clarification 9.3%. The two most frequently declared educational theories were Cognitive Theories and Experiential Learning. Conclusion: The low proportion of Clarification studies found in the SBME conference abstracts reflects previous findings highlighting the lack of medical education studies that establish how and why SBME works. Researchers should be encouraged to declare their underpinning educational theories when presenting their work. Conference organisers play an important role in facilitating this through allowing sufficient word count in their submission criteria.

Indexed as

Conference AbstractsEducationHealthcareResearchSimulation

Identifiers

PMID35517832
PMCPMC8936684

What OpenQuestion holds

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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.