Evidence map›Paper›PMID 25806640›Full record

ArticleRevista latino-americana de enfermagem

The contribution of distance learning to the knowledge of nursing lecturers regarding assessment of chronic wounds.

Márcia Beatriz Berzoti Gonçalves, Soraia Assad Nasbine Rabeh, César Augusto Sangaletti Terçariol

Abstract read
In one paragraph

Article in Revista latino-americana de enfermagem. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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

2 citing papers in PubMed.

  1. Observational
  2. 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

3 authors.

Márcia Beatriz Berzoti GonçalvesEscola de Enfermagem de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil.
Soraia Assad Nasbine RabehEscola de Enfermagem de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil.
César Augusto Sangaletti TerçariolCentro Universitário Barão de Mauá, Ribeirão Preto, SP, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveto identify the contribution made by a refresher course on the assessment of chronic wounds, offered through the Moodle virtual learning environment (VLE), to the knowledge relating to this issue of nursing lecturers and nurses linked to higher education.

methoda prospective, quasi-experimental study, with data collection before and after the educational intervention. The study was undertaken in three stages using the Moodle VLE. The sample was made up of 28 participants who answered the pre-test on the knowledge, devised in accordance with international guidelines on chronic wounds. Afterwards, the refresher course was offered (intervention) and was accessed in accordance with individuals' schedules, during the established time period. At the end of the course, 26 participants answered the post-test. Those who did not participate in the post-tests were excluded from the study, as it is pairwise analysis of the sample.

resultthe participants obtained, on average, 55.5% of correct answers in the pre-test on their knowledge, and 73.4% in the post-test, this difference being statistically significant. There was a negative correlation between the time of experience in lecturing and the performance in the test on their knowledge.

conclusionthe participation in the online refresher course contributed to improving the lecturers' performance in the test on their knowledge, in relation to the recommendations for assessing chronic wounds, based in scientific evidence.

Indexed as

Education, DistanceFaculty, NursingAdultChronic DiseaseFemaleHumansProspective StudiesSkin Ulcer

Identifiers

PMID25806640
PMCPMC4376040

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LicenceCC BY
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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.