ArticleJournal of education and health promotion2021
The feasibility of simulation-based high-stakes assessment in emergency medicine settings: A scoping review.
Article in Journal of education and health promotion, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Facilitated interactive video versus simulation-based training after a standardized lecture for basic life support in medical students: a randomized trial.BMC medical education · 2026Trial
- Effectiveness of hybrid simulation training on medical student performance in whole-task consultation of cardiac patients: The ASSIMILATE EXCELLENCE randomized waitlist-controlled trial.Advances in simulation (London, England) · 2024Article
- Teaching basic life support for medical students: Assessment of learning and knowledge retention.Journal of education and health promotion · 2023Article
- Simulation-based clinical assessment identifies threshold competence to practise physiotherapy in Australia: a crossover trial.Advances in simulation (London, England) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Using simulation in high-stakes assessments has been evolving as a method to improve the assessment process. There is a concurrent need to address challenges and establish best practices to ensure the best quality when implementing high-stakes evaluations. The aim of this study is to provide an insight for stakeholders about using multiple modalities of simulation in high-stakes evaluations by presenting challenges, best practices, and future directions described in the relevant literature. A scoping review of original studies (from the year 1994-2021) including the use of common modalities (standardized patients, high-fidelity mannequins, part-task trainers, virtual simulation, and hybrid simulation) was conducted. The search covered the common databases: PubMed, Education Resource Information Center, Cumulative Index to Nursing and Allied Health Literature, and the Cochrane library. Initial screening in the databases resulted in 111,253 articles. After the application of a refining search strategy, 47 articles were included for comprehensive evaluation. Most articles were about credentialing/licensure purposes of assessment. Many articles were specialty-specific, especially focusing on anesthesia. Most challenges described were related to the validity of the assessment that should be considered in the planning phase. Best practices were mostly related to planning for measures to assure the validity of the assessment tools and process. The use of multimodality simulation for high-stakes assessment is growing despite challenges; this growth is associated with the accumulation of experience shared in literature. This growth will help to improve planning, practices, and goals achievement from such an application.
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Registered trials
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.