Evidence map›Paper›PMID 39149068›Full record

ArticleHeliyon2024

The effect of COVID-19 anxiety on nurses' productivity determinants through perceived workload and individual job performance: A Bayesian mediation analysis.

Maryam Rafiee, Tahereh Eskandari, Evan Abdulkareem Mahmood, Mojtaba Zokaei, Mohsen Falahati, Mohammad Hossein Khalilzadeh Naghneh

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Article in Heliyon, 2024. 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

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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

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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

6 authors.

Maryam RafieeSchool of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Tahereh EskandariDepartment of Occupational Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.
Evan Abdulkareem MahmoodMedical Laboratory Sciences Department, College of Health Sciences, University of Human Development, Sulaymaniyah, Iraq.
Mojtaba ZokaeiSocial Determinants of Health Research Center, Saveh University of Medical Sciences, Saveh, Iran.
Mohsen FalahatiSocial Determinants of Health Research Center, Saveh University of Medical Sciences, Saveh, Iran.
Mohammad Hossein Khalilzadeh NaghnehDepartment of Medical Emergency, Saveh University of Medical Sciences, Saveh, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to predict how COVID-19 anxiety affects productivity determinants by examining the role of perceived workload and individual job performance as mediators using Bayesian mediation analysis. To achieve the study's objectives, all nurses working at Imam Reza Hospital were recruited to participate. To gather data, all eligible and voluntary nurses were asked to complete questionnaires that included the Corona Disease Anxiety Scale (CDAS), Individual Job Performance Questionnaire (IJPQ), NASA Task Load Index (NASA-TLX), and Workforce Productivity Questionnaire. Of the total number of nurses employed, 222 (126 women and 96 men) nurses fully completed the questionnaires. Out of these, 140 individuals were married and 82 were single. The mean ± standard deviation (SD) of the age and experience were 28.56 ± 5.78 and 8.49 ± 6.50, respectively. GeNIe software version 2.0 utilized to analyze the Bayesian network. The results showed that for the high COVID-19 anxiety and high workload states, with a probability of 100 %, the probability of high evaluation and high environment increased by 16.6 % and 16.3 %, respectively, but low evaluation and low environment decreased by 22.4 % and 22 %, respectively. In the high COVID-19 anxiety and low IJP states with a probability of 100 %, most change was related to the high ability (6 % increase), low evaluation (3.9 % increase), high incentive (3.8 % increase), low ability (4.6 % decrease) and low support (2 % decrease). Regarding COVID-19 anxiety (high 100 %), workload (high 100 %) and IJP (low 100 %), most of the increase was related to high environment and high evaluation by an increase of 17.3 and 17.2 %, respectively. Also, the value of low evaluation and low environment was reduced by 24 and 23.4 %, respectively. The study's findings confirm that nurses have been more productive during the COVID-19 pandemic, despite facing high workloads and the COVID-19 anxiety.

Indexed as

AnxietyBayes theoremCOVID-19ProductivityWorkloadWork performance

Identifiers

PMID39149068
PMCPMC11324830

What Socratic holds

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LicenceCC BY-NC-ND
Read underepoch 390

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 Socratic graph.