Evidence map›Paper›PMID 34141919›Full record

ArticleHeliyon2021

Use of a 3D virtual app and academic performance in the study of the anatomy of the musculoskeletal system among Peruvian medical students.

Sol J de La Barrera-Cantoni, Melanni L Lizarbe-Lezama, Jhoel E Rodriguez-Macedo, Tammy S Carrillo-Levin, Maria F Jaramillo-Ocharan, Carlos J Toro-Huamanchumo

Abstract read
In one paragraph

Article in Heliyon, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

  1. Pooled it
  2. Trial
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

6 authors.

Sol J de La Barrera-CantoniUniversidad Peruana de Ciencias Aplicadas, Lima, Peru.
Melanni L Lizarbe-LezamaUniversidad Peruana de Ciencias Aplicadas, Lima, Peru.
Jhoel E Rodriguez-MacedoUniversidad Peruana de Ciencias Aplicadas, Lima, Peru.
Tammy S Carrillo-LevinUniversidad Peruana de Ciencias Aplicadas, Lima, Peru.
Maria F Jaramillo-OcharanUniversidad Peruana de Ciencias Aplicadas, Lima, Peru.
Carlos J Toro-HuamanchumoUniversidad Peruana de Ciencias Aplicadas, Lima, Peru.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the association between the use of a 3D virtual App and academic performance among Peruvian medical students. In addition, factors associated with academic performance were also assessed.

methodsWe conducted an analytical cross-sectional study in students enrolled in the Musculoskeletal System course during the first semester of 2019. Students filled out a data collection form and the "Self-directed learning readiness scale" (SDLRS) questionnaire adapted by

resultsA total of 187 medical students were included. The 61% were female and the median age was 21 [20-22] years. The average grade was 13.5 ± 2 and 21% reported an adequate use of a 3D App. No association was found between the use of the 3D App and academic performance in the adjusted model (aβ = 0.17; 95% CI: -0.45 to 0.80). We found that age (aβ = -0.22; 95% CI: -0.39 to -0.06), performing extracurricular activities (aβ = 0.75, 95% CI: 0.25 to 1.24) and having failed an anatomy/physiology course before (aβ = -2.11 to 95% CI: -2.9 to -1.8) were factors associated with academic performance.

conclusionThe adequate use of a 3D application to study the anatomy of the musculoskeletal system was not significantly associated with better academic performance.

Indexed as

Academic performanceAnatomyEducationMedical (MeSH NLM)Self-directed learning

Identifiers

PMID34141919
PMCPMC8187966

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.