Evidence map›Paper›PMID 36060420›Full record

ArticleJournal of multidisciplinary healthcare2022

The Need for Speed: A Qualitative Study on Nurse Recruitment and Management Amidst the COVID-19 Pandemic in Indonesia.

Ferry Efendi, Gading Ekapuja Aurizki, Ilmiawan Auwalin, Lisa McKenna

Abstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2022. 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. Article
  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

4 authors.

Ferry EfendiFaculty of Nursing, Universitas Airlangga, Surabaya, Indonesia.ORCID 0000-0001-7988-9196
Gading Ekapuja AurizkiFaculty of Nursing, Universitas Airlangga, Surabaya, Indonesia.ORCID 0000-0002-9458-8241
Ilmiawan AuwalinFaculty of Economics and Business, Universitas Airlangga, Surabaya, Indonesia.
Lisa McKennaSchool of Nursing and Midwifery, La Trobe University, Melbourne, Victoria, Australia.ORCID 0000-0002-0437-6449

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Nursing workforce is a pivotal element in tackling the COVID-19 pandemic. However, this has not been comprehensively discussed, particularly in Indonesia. This study aimed to explore stakeholders' perspectives on Indonesian nursing workforce recruitment and management during the COVID-19 pandemic. Methods: This study employed a qualitative design with an exploratory descriptive approach. Stakeholders who recruited and managed nursing resources in Indonesia were involved. In-depth interviews and focus group discussions with stakeholders representing eight different institutions were undertaken. Data were analysed using thematic analysis. Eight key stakeholders were interviewed. Results: Three themes emerged, namely uncertain recruitment system, nursing labour market situation, and workforce management dynamics. COVID-19 caused reduced workforce capacity and increased demands for health professionals, especially nurses. Conclusion: Uncertainty and volatility happened at the recruitment and management of nursing human resources during the pandemic. Stakeholders were not convinced of overall quality of local nurses recruited to care for COVID-19 patients given workforce was dominated by new graduates and nurses without specialistic qualifications. Employers gave new staff more training to ease their deployment to COVID-19 units to make up for the nurses' lack of expertise and experience.

Indexed as

adaptive managementCOVID-19health workerlabour marketpandemicpersonnel management

Identifiers

PMID36060420
PMCPMC9431772

What OpenQuestion holds

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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.