Literature DB >> 25039731

How much evidence does it take? A cumulative meta-analysis of outcomes of simulation-based education.

David A Cook1.   

Abstract

CONTEXT: Studies that investigate research questions that have already been resolved represent a waste of resources. However, the failure to collect sufficient evidence to resolve a given question results in ambiguity.
OBJECTIVES: The present study was conducted to reanalyse the results of a meta-analysis of simulation-based education (SBE) to determine: (i) whether researchers continue to replicate research studies after the answer to a research question has become known, and (ii) whether researchers perform enough replications to definitively answer important questions.
METHODS: A systematic search of multiple databases to May 2011 was conducted to identify original research evaluating SBE for health professionals in comparison with no intervention or any active intervention, using skill outcomes. Data were extracted by reviewers working in duplicate. Data synthesis involved a cumulative meta-analysis to illuminate patterns of evidence by sequentially adding studies according to a variable of interest (e.g. publication year) and re-calculating the pooled effect size with each addition. Cumulative meta-analysis by publication year was applied to 592 comparative studies using several thresholds of 'sufficiency', including: statistical significance; stable effect size classification and magnitude (Hedges' g ± 0.1), and precise estimates (confidence intervals of less than ± 0.2).
RESULTS: Among studies that compared the outcomes of SBE with those of no intervention, evidence supporting a favourable effect of SBE on skills existed as early as 1973 (one publication) and further evidence confirmed a quantitatively large effect of SBE by 1997 (28 studies). Since then, a further 404 studies were published. Among studies comparing SBE with non-simulation instruction, the effect initially favoured non-simulation training, but the addition of a third study in 1997 brought the pooled effect to slightly favour simulation, and by 2004 (14 studies) this effect was statistically significant (p < 0.05) and the magnitude had stabilised (small effect). A further 37 studies were published after 2004. By contrast, evidence from studies evaluating repetition continued to show borderline statistical significance and wide confidence intervals in 2011.
CONCLUSIONS: Some replication is necessary to obtain stable estimates of effect and to explore different contexts, but the number of studies of SBE often exceeds the minimum number of replications required.
© 2014 John Wiley & Sons Ltd.

Mesh:

Year:  2014        PMID: 25039731     DOI: 10.1111/medu.12473

Source DB:  PubMed          Journal:  Med Educ        ISSN: 0308-0110            Impact factor:   6.251


  22 in total

Review 1.  Randomized controlled trials of simulation-based interventions in Emergency Medicine: a methodological review.

Authors:  Anthony Chauvin; Jennifer Truchot; Aida Bafeta; Dominique Pateron; Patrick Plaisance; Youri Yordanov
Journal:  Intern Emerg Med       Date:  2017-11-16       Impact factor: 3.397

2.  ASPiH standards for simulation-based education: process of consultation, design and implementation.

Authors:  Makani Purva; Jane Nicklin
Journal:  BMJ Simul Technol Enhanc Learn       Date:  2018-07-09

3.  Author response to published editorials on ASPiH standards for simulation-based education.

Authors:  Makani Purva; Jane Patricia Nicklin
Journal:  BMJ Simul Technol Enhanc Learn       Date:  2018-07-09

4.  Effects of simulation for gynaecological ultrasound scan training: a systematic review.

Authors:  Natalie Jane Woodhead; Ayesha Mahmud; Justin Clark
Journal:  BMJ Simul Technol Enhanc Learn       Date:  2020-11-01

5.  Reporting guidelines for health care simulation research: Extensions to the CONSORT and STROBE statements.

Authors:  Adam Cheng; David Kessler; Ralph Mackinnon; Todd P Chang; Vinay M Nadkarni; Elizabeth A Hunt; Jordan Duval-Arnould; Yiqun Lin; David A Cook; Martin Pusic; Joshua Hui; David Moher; Matthias Egger; Marc Auerbach
Journal:  BMJ Simul Technol Enhanc Learn       Date:  2016-07-24

6.  Applying Educational Theory and Best Practices to Solve Common Challenges of Simulation-based Procedural Training in Emergency Medicine.

Authors:  Michael Cassara; Kimberly Schertzer; Michael J Falk; Ambrose H Wong; Sara M Hock; Suzanne Bentley; Glenn Paetow; Lauren W Conlon; Patrick G Hughes; Ryan T McKenna; Michael Hrdy; Charles Lei; Miriam Kulkarni; Colleen M Smith; Amanda Young; Ernesto Romo; Michael D Smith; Jessica Hernandez; Christopher G Strother; Alise Frallicciardi; Nur-Ain Nadir
Journal:  AEM Educ Train       Date:  2019-12-27

7.  Medical education in cyberspace: critical considerations in the health system.

Authors:  Shahram Yazdani; Zohreh Khoshgoftar; Soleiman Ahmady; Hassan Rastegarpour; Seyed Abbas Foroutan
Journal:  J Adv Med Educ Prof       Date:  2017-01

8.  A Mixed-methods Comparison of Participant and Observer Learner Roles in Simulation Education.

Authors:  Mark J Bullard; Anthony J Weekes; Randolph J Cordle; Sean M Fox; Catherine M Wares; Alan C Heffner; Lisa D Howley; Deborah Navedo
Journal:  AEM Educ Train       Date:  2018-12-21

9.  Motivation to learn: an overview of contemporary theories.

Authors:  David A Cook; Anthony R Artino
Journal:  Med Educ       Date:  2016-10       Impact factor: 6.251

10.  Reporting guidelines for health care simulation research: extensions to the CONSORT and STROBE statements.

Authors:  Adam Cheng; David Kessler; Ralph Mackinnon; Todd P Chang; Vinay M Nadkarni; Elizabeth A Hunt; Jordan Duval-Arnould; Yiqun Lin; David A Cook; Martin Pusic; Joshua Hui; David Moher; Matthias Egger; Marc Auerbach
Journal:  Adv Simul (Lond)       Date:  2016-07-25
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