Evidence map›Paper›PMID 38437056›Full record

ArticleJournal of the American Academy of Orthopaedic Surgeons. Global research & reviews2024

An Analysis of Participant Preferences Regarding Virtual Versus In-person Format of Orthopaedic Surgery Educational Materials in Low- and Middle-Income Countries.

Michael J Flores, Kelsey E Brown, Madeline C MacKechnie, Jamieson M O'Marr, Patricia Rodarte, David W Shearer

Abstract read
In one paragraph

Article in Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Michael J FloresFrom the Institute for Global Orthopaedics and Traumatology, University of California San Francisco, San Francisco, CA.
Kelsey E Brown
Madeline C MacKechnie
Jamieson M O'Marr
Patricia Rodarte
David W Shearer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe University of California, San Francisco Institute for Global Orthopaedics and Traumatology Surgical Management and Reconstructive Training (SMART) course has instructed orthopaedic surgeons from low-resource countries on soft-tissue reconstruction. Before the COVID-19 pandemic, the course was conducted in-person; however, it was transitioned to a virtual format during the pandemic. The aim of this study was to determine participant preferences regarding a virtual or in-person SMART course format.

methodsSurvey data were collected via e-mail after each SMART course using RedCap or Qualtrics. Statistical analyses were conducted using Stata.

resultsThere were 247 survey respondents from 44 countries representing all world regions, with Africa (125, 51%) the most represented. Of those who attended both an in-person and virtual course, most (82%) preferred the in-person format. In addition, all measured course outcomes were significantly better for participants attending the in-person course. The most common reason for not attending an in-person course was the cost of travel (38, 51%). DISCUSSION: This study demonstrated a preference toward in-person learning for the SMART course. In addition, those surgeons participating in the in-person course endorsed increased positive outcomes from the course. Increased emphasis should be placed on in-person surgical skills training for low-resource surgeons.

Indexed as

Orthopedic ProceduresOrthopedicsAcademies and InstitutesDeveloping CountriesHumansPandemics

Identifiers

PMID38437056
PMCPMC10906641

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.