Evidence map›Paper›PMID 37818153›Full record

ArticleAfrican journal of emergency medicine : Revue africaine de la medecine d'urgence2023

Introduction of WHO BEC course for nurses at Bugando Medical Center in Mwanza, Tanzania.

Nita Avrith, Young Suh, Ramona Sunderwirth, Shahzmah Suleman, Ally Munir Akrabi

Abstract read
In one paragraph

Article in African journal of emergency medicine : Revue africaine de la medecine d'urgence, 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

5 authors.

Nita AvrithMount Sinai Morningside Hospital, New York, New York, USA.
Young SuhMount Sinai Morningside Hospital, New York, New York, USA.
Ramona SunderwirthMount Sinai Morningside Hospital, New York, New York, USA.
Shahzmah SulemanBugando Medical Center, Mwanza, Tanzania.
Ally Munir AkrabiBugando Medical Center, Mwanza, Tanzania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The Basic Emergency Care (BEC) course is an open-access training designed for frontline providers in low resource settings which focuses on recognizing and managing emergent conditions. This study describes the implementation of the BEC course for nurses at Bugando Medical Center (BMC) in Mwanza, Tanzania in March 2020 as part of an educational initiative to improve nurses' knowledge and confidence in providing emergency care. Methods: This is a 2-week educational intervention with pre-post measurements. 12 nurses (cohort 1) received BEC training from in-country facilitators over the course of 4 days. A training-of-trainers (ToT) course followed immediately and the 5 newly trained facilitators then taught the BEC course to 12 additional nurses (cohort 2). Pre- and post-BEC knowledge was assessed with a standardized 25-question multiple choice (MCQ) exam; confidence levels were evaluated using a 4-point Likert scale survey; and qualitative feedback obtained was examined by thematic analysis. Results: 24 participants completed the BEC course, 5 of which completed a ToT to become BEC facilitators. For the combined group, knowledge assessment scores improved significantly from 63.8% to 85.2% with a mean difference of 21.5% (t Conclusion: Implementation of the BEC course at BMC led to an improvement in nursing emergency care knowledge and self-confidence. The course was well received and the ToT model was successful, giving the nurses the ability to train additional local nurses.

Indexed as

Basic Emergency CareTanzaniaTraining of trainers

Identifiers

PMID37818153
PMCPMC10560998

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.