Evidence map›Paper›PMID 27106583›Full record

ArticleJournal of medical systems2016

Acquisition of Competencies by Medical Students in Neurological Emergency Simulation Environments Using High Fidelity Patient Simulators.

M J Sánchez-Ledesma, J A Juanes, C Sáncho, M Alonso-Sardón, J Gonçalves

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In one paragraph

Article in Journal of medical systems, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 23% of its field
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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. 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

5 authors at 1 institution in 1 country.

M J Sánchez-LedesmaDepartment of Surgery, University of Salamanca, Avda Alfonso X El Sabio s/n, 37007, Salamanca, Spain. mledesma@usal.es.
J A JuanesDepartment of Anatomy, University of Salamanca, Salamanca, Spain.
C SánchoDepartment of Pharmacology, University of Salamanca, Salamanca, Spain.
M Alonso-SardónDepartment of Statistical Sciences, University of Salamanca, Salamanca, Spain.
J GonçalvesDepartment of Surgery, University of Salamanca, Avda Alfonso X El Sabio s/n, 37007, Salamanca, Spain.
Universidad de Salamanca · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The training of medical students demands practice of skills in scenarios as close as possible to real ones that on one hand ensure acquisition of competencies, and on the other, avoid putting patients at risk. This study shows the practicality of using high definition mannequins (SimMan 3G) in scenarios of first attention in neurological emergencies so that medical students at the Faculty of Medicine of the University of Salamanca could acquire specific and transversal competencies. The repetition of activities in simulation environments significantly facilitates the acquisition of competencies by groups of students (p < 00.5). The greatest achievements refer to skills whereas the competencies that demand greater integration of knowledge seem to need more time or new sessions. This is what happens with the competencies related to the initial diagnosis, the requesting of tests and therapeutic approaches, which demand greater theoretical knowledge.

Indexed as

EmergenciesSimulation TrainingStudents, MedicalClinical CompetenceHumansManikinsNervous System DiseasesHigh fidelity patient simulatorLearning settingMannequinMedical educationSimulation

Identifiers

PMID27106583
OpenAlexW2341311834

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.