Evidence map›Paper›PMID 36674044›Full record

ArticleInternational journal of environmental research and public health2023

Predicting Challenge and Threat Appraisal of Job Demands among Nurses: The Role of Matching Job Resources.

Martha Fernandez de Henestrosa, Philipp E Sischka, Georges Steffgen

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2023. 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

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

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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

3 authors.

Martha Fernandez de HenestrosaDepartment of Behavioural and Cognitive Sciences, University of Luxembourg, L-4366 Esch-sur-Alzette, Luxembourg.ORCID 0000-0002-9222-0793
Philipp E SischkaDepartment of Behavioural and Cognitive Sciences, University of Luxembourg, L-4366 Esch-sur-Alzette, Luxembourg.ORCID 0000-0001-8414-0817
Georges SteffgenDepartment of Behavioural and Cognitive Sciences, University of Luxembourg, L-4366 Esch-sur-Alzette, Luxembourg.ORCID 0000-0002-0171-6786

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

(1) Background: Empirical studies have started to examine employees' subjective appraisals of job demands and their relations to employees' health. However, knowledge of working conditions, which might contribute to how employees appraise specific job demands, is scarce. The present study aimed to examine predictors of nurses' appraisals of job demands (i.e., time pressure, emotional demands, physical demands, and role ambiguity) as challenges and/or threats among corresponding job resources (i.e., autonomy, social support, physical resources, participation in decision-making). It also examined moderating effects of these predictors. (2) Methods: Cross-sectional data were collected via an online survey in a sample of 425 nurses working in Luxembourg. (3) Results: Multiple regression analyses indicated that matching job resources predicted nurses' appraisal of job demands as challenging. Threat appraisal was predicted by three out of four kinds of job resources (i.e., autonomy, physical resources, participation in decision-making). However, the current study did not find any moderating effects between job demands and job resources on challenge/threat appraisals. (4) Conclusions: The present study identified domain-specific job resources that contribute to how employees perceive selected job demands. Accordingly, we encourage scholars and practitioners to align job demands with matching job resources to prevent nurses' threat appraisal of job demands, and to promote their challenge appraisals.

Indexed as

Burnout, ProfessionalCross-Sectional StudiesHumansJob SatisfactionRegression AnalysisSurveys and QuestionnairesWorkloadchallenge appraisaljob demandsjob resourcesmatching principlethreat appraisal

Identifiers

PMID36674044
PMCPMC9859003

What OpenQuestion holds

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LicenceCC BY
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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.