Evidence map›Paper›PMID 39654769›Full record

ArticleHeliyon2024

Development of a work systems stress questionnaire to predict job burnout: A mixed methods study based on a macroergonomics approach.

Rahman Zare, Reza Kazemi, Alireza Choobineh, Rosanna Cousins, Andrew Smith, Hamidreza Mokarami

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

The trial behind it

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Rahman ZareStudent Research Committee, Department of Occupational Health and Safety Engineering, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran.
Reza KazemiDepartment of Ergonomics, School of Health, Shiraz University of Medical Sciences, Iran.
Alireza ChoobinehResearch Center for Health Sciences, Shiraz University of Medical Sciences, Iran.
Rosanna CousinsDepartment of Psychology, Liverpool Hope University, Liverpool, UK.
Andrew SmithSchool of Psychology, Centre for Occupational and Health Psychology, Cardiff University, UK.
Hamidreza MokaramiDepartment of Ergonomics, School of Health, Shiraz University of Medical Sciences, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Job burnout is a stress-related phenomenon that is a significant threat to the health and performance of organizations and employees. Interventions to ameliorate potentials for burnout have been limited by the lack of a comprehensive tool that considers work system stressors. Thus, the aim of this study was to develop a questionnaire for predicting job burnout based on the macroergonomics work system approach. The setting was a petrochemical company in South Iran. In the qualitative phase of this sequential exploratory mixed methods research, 971 meaning codes were extracted from fourteen one-to-one and seven focus group interviews (n = 59). The codes were subject to Directed Content Analysis, which yielded three themes and 15 dimensions, which were used to inform the development of reliable and valid questionnaire. Items for each of the dimensions were sourced from exiting scales. To test the developed Work System Stress Questionnaire (WSSQ) in terms of its ability to predict burnout, a survey which included demographic items, the WSSQ, and the Maslach Burnout Inventory was completed by 359 employees. Hierarchical linear regression modelling of the data indicated that Task Significance, Job Demands, Work-Life Conflict, and Work Schedule predicted Emotional Exhaustion, and altogether explained 58 % variance. Task Significance, Violence and Harassment, Work-Life Conflict, and Job Insecurity predicted the Depersonalization and explained 29 % variance. Decision Latitude, Welfare and Financial Facilities, Task Significance, and Structural Problems predicted Personal Accomplishment and explained 26 % variance. All 15 dimensions were valid (CVI range .73-.90) and reliable (Cronbach's alpha range .71-.93). The results confirm the ability of the WSSQ to explain more variance regarding job burnout than previous studies. In turn, the WSSQ will enable remedial actions to be put into place. It may also be useful for understanding the consequences associated with other organizational ergonomic variables that are related to job stress.

Indexed as

Occupational burnoutOrganizational ergonomicsSequential exploratory designSociotechnical systemWork-related stress

Identifiers

PMID39654769
PMCPMC11626067

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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.