Evidence map›Paper›PMID 37975067›Full record

ArticleJournal of infection prevention2023

Competency assessment tools for infection preventionists: A scoping review.

Adriana M da Silva Felix, Erica G Pereira, Maria Clara Padoveze

Abstract readScoping Review
In one paragraph

Article in Journal of infection prevention, 2023. 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. Review
  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.

Adriana M da Silva FelixDepartment of Community Health Nursing, The School of Nursing, University of São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-3559-3729
Erica G PereiraDepartment of Community Health Nursing, The School of Nursing, University of São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0003-2873-4519
Maria Clara PadovezeDepartment of Community Health Nursing, The School of Nursing, University of São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-1912-7293

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Infection prevention competencies are critical for successful job performance, career progression and robust performance of infection prevention and control programs. Aim/objective: Identify competency assessment tools available to infection preventionists and describe their characteristics, validation processes and reliability. Methods: A scoping review was conducted on five databases and grey literature from 1999 to 2022. A descriptive synthesis approach was undertaken to analyse the data. Finding/results: Seven tools that meet the inclusion criteria were identified. Of those, one tool was reviewed twice. All tools were developed in the United Kingdom, Canada, China and the United States, and were published between 2009 and 2022. All tools use a rating scale; and the most used method to assess competencies was self-assessment. Levels of competency were cited by five tools. Two tools provided information on validation methods and reliability tests for internal consistency. Discussion: Few competency assessment tools are available in the literature, and there is a lack of information on their development process. A global effort to develop an assessment tool that allows comparison across countries and cultures can be a step forward to propel infection preventionists' careers and enhance the efficacy of Infection Prevention and Control Programs.

Indexed as

assessment toolscompetencyinfection preventionistscoping review

Identifiers

PMID37975067
PMCPMC10638954

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.