Evidence map›Paper›PMID 33110816›Full record

ArticleJournal of family medicine and primary care2020

Evaluating the relationship between information literacy and evidence-based nursing and their impact on knowledge and attitude of nurses working in hospitals affiliated to Kerman University of Medical Sciences on medication errors.

Mohammad Azami, Hamid Sharifi, Saiedeh Alvandpur

Abstract read
In one paragraph

Article in Journal of family medicine and primary care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Pooled it
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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.

Mohammad AzamiMedical Informatics Research Center, Institute of Futures Studies in Health, Kerman Medical University, Kerman, Iran.
Hamid SharifiHIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Kerman, Iran.
Saiedeh AlvandpurModeling in Health Research Center, Institute of Futures Studies in Health, Kerman Medical University, Kerman, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introduction and purposeNowadays, due to the importance of information literacy in obtaining documented and credible information, the necessity of nurses to achieve high levels of information literacy to improve their performance in accessing documentary and scientific information has become more evident.

objectiveThe aim of this study was to investigate information literacy, evidence-based nursing, nurses 'attitudes, nurses' knowledge, medication errors, Kerman University of Medical Sciences. METHODOLOGY: This study was a survey study. The study units were 164 nurses working in 4 hospitals of Kerman University of Medical Sciences. The participants were chosen by simple random sampling. The instrument used included four sections: demographic information, information literacy, evidence-based practice, and medication errors. Data were analyzed using software SPSS 22.

resultsThe results of this study showed that nurses were familiar with the terminology used in evidence-based medicine (

conclusionsThe result findings of the normal distribution of samples showed that 29% were male and 71% were female. The results show that there is a significant relationship between information literacy and evidence-based nursing. The direction of the relationship is positive (

Indexed as

Evidence-based nursinginformation literacyKerman University of Medical Sciencesmedication errornurses attitude and knowledgeprimary health care

Identifiers

PMID33110816
PMCPMC7586513

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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.