Evidence map›Paper›PMID 39200600›Full record

ArticleInternational journal of environmental research and public health2024

Manager-Team (Dis)agreement on Stress-Preventive Behaviours: Relationship with Psychosocial Work Environment and Employees' Well-Being.

Stefano Toderi, Glauco Cioffi, Joanna Yarker, Rachel Lewis, Jonathan Houdmont, Cristian Balducci

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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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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

4 citing papers in PubMed.

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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

6 authors.

Stefano ToderiDepartment of Psychology, University of Bologna, 40127 Bologna, Italy.ORCID 0000-0003-1015-556X
Glauco CioffiDepartment of Psychology, University of Bologna, 40127 Bologna, Italy.ORCID 0009-0006-7516-4730
Joanna YarkerAffinity Health at Work, London SW12 9NW, UK.
Rachel LewisAffinity Health at Work, London SW12 9NW, UK.
Jonathan HoudmontFaculty of Medicine & Health Sciences, University of Nottingham, Nottingham NG7 2RD, UK.ORCID 0000-0001-5174-2619
Cristian BalducciDepartment for Life Quality Studies, University of Bologna, 47921 Rimini, Italy.ORCID 0000-0002-5998-9971

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The "Management Competencies to Prevent and Reduce Stress at Work" (MCPARS) approach focuses on identifying the stress-preventive managers' competencies able to optimise the employees' well-being through the management of the psychosocial work environment. Considering leadership as contextualised in complex social dynamics, the self-other agreement (SOA) investigation of the MCPARS may enhance previous findings, as it allows for exploring the manager-team perceptions' (dis)agreement and its potential implications. However, no studies have tested the MCPARS using the SOA and multisource data. Grounded in Yammarino and Atwater's SOA reference theory, we conducted an in-depth investigation on the MCPARS's theoretical framework by examining the implications of manager-team (dis)agreement, regarding managers' competencies, on employees' psychosocial environment (H1-H2) and affective well-being (H3). Data from 36 managers and 475 employees were analysed by performing several polynomial regressions, response surface, and mediation analyses. The results reveal a significant relationship between SOA on MCPARS and employees' perceptions of the psychosocial environment (H1). Employees report better perceptions when supervised by

Indexed as

Occupational StressWorkplaceAdultFemaleHumansMaleMiddle AgedOccupational HealthStress, PsychologicalSurveys and QuestionnairesWorking Conditionsmanagement competenciespolynomial regressionpsychosocial work environmentself–other agreementwell-beingwork-related stress

Identifiers

PMID39200600
PMCPMC11354095

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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.