Evidence map›Paper›PMID 37465838›Full record

ArticlePRiMER (Leawood, Kan.)2023

Remote Synchronous Laceration Repair Instruction With Summary Feedback.

Stephen K Stacey, Christopher L Boswell, Karen K Cowan, Anthony J Furlano, Mark D McEleney, Erin F Morcomb, Christopher J Tookey

Abstract read
In one paragraph

Article in PRiMER (Leawood, Kan.), 2023. 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

7 authors.

Stephen K StaceyFamily Health Clinic, Mayo Clinic Health System - Southwest Wisconsin Region, La Crosse, WI.
Christopher L BoswellMayo Family Clinic Kasson, Kasson, MN.
Karen K CowanFamily Health Clinic Mayo Clinic Health System - Southwest Wisconsin Region, La Crosse, WI.
Anthony J FurlanoMayo Clinic Health System, Eau Claire, WI.
Mark D McEleneyMayo Clinic Health System, La Crosse, WI.
Erin F MorcombMayo Clinic Health System - Franciscan Healthcare of La Crosse, La Crosse, WI.
Christopher J TookeyGundersen Health System, Sparta, WI.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Social distancing and quarantine requirements imposed during the COVID-19 pandemic necessitated remote training in many learning situations that formerly focused on traditional in-person training. In this context, we developed an adaptive approach to teaching laceration repair remotely while allowing for synchronous instruction and feedback. Methods: In April 2020, 35 family medicine residents from 4 programs in the Midwest United States participated in a real-time, remotely-delivered, 2-hour virtual procedure workshop of instruction in suture techniques for laceration repair. Paired-sample Results: All residents completed the pre- and posttests. The posttest scores for self-confidence across the participants showed significant improvement for all suture techniques. Of the 67 short-answer responses, 38 responses (56.7%) were positive; 9 (13.4%) negative; 8 (11.9%) neutral; and 12 (17.9%) a combination of positive and negative. The workshop was rated by 34 residents (97.1%) as either "about the same as prior training experiences," "better than prior training experiences," or "much better than prior training experiences." Conclusion: Learners reported that a remotely-delivered, real-time, synchronous suture technique workshop was a valuable experience. Further research is needed to establish the efficacy of this platform to promote procedural competence.

Identifiers

PMID37465838
PMCPMC10351430

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.