Psychosocial drivers of occupational stress in industrial employees: implications for workplace health management

Purpose Occupational stress represents a major challenge for workplace health management, particularly in industrial environments where employees are exposed to multiple psychosocial and organizational pressures. This study aimed to examine the underlying dimensions of occupational stress among industrial employees and to identify key workplace indicators associated with elevated stress levels using an integrated analytical framework. Design/methodology/approach The dataset contained questionnaire records from 98 male employees in an Iranian industrial organization. Occupational stress was assessed using the 23-item Cooper questionnaire, with items scored from 0 to 5. Factor analysis and classification included 86 employees with complete Cooper responses. Entropy weighting described distributional information, exploratory factor analysis examined shared item variation, and k-means clustering explored response-pattern groupings. Classification models used five prespecified demographic and occupational predictors and were evaluated using 20 repetitions of stratified five-fold cross-validation. Held-out SHapley Additive exPlanations’ contributions were used to interpret logistic-regression predictions. Findings Factor analysis suggested a three-factor solution accounting for 33.1% of total standardized item variance, while clustering identified two provisional response-pattern groupings. Mean Area Under the Curve (AUC) values were 0.705, 0.698 and 0.686 for logistic regression, random forest and gradient boosting, respectively. Mean classification accuracy was close to the majority-class baseline. Work shift and work experience had the largest mean absolute contributions to logistic-regression predictions. Originality/value The analyses provide an exploratory basis for organizing employee questionnaire findings and guiding subsequent workforce assessment and consultation. Independent replication, external validation and prospective evaluation are needed to establish their practical value for workplace health management.

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Publication Details

Journal
International Journal of Workplace Health Management
Published
2026-11-06
DOI
https://doi.org/10.1108/ijwhm-03-2026-0103
Primary Topic
Workplace Health and Well-being
Type
article
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article

Psychosocial drivers of occupational stress in industrial employees: implications for workplace health management

Parisa Moshashaei, Jalil Nazari, Daniel J. Amor
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International Journal of Workplace Health Management
Workplace Health and Well-being
article

Psychosocial drivers of occupational stress in industrial employees: implications for workplace health management

Parisa Moshashaei, Jalil Nazari, Daniel J. Amor
article en

Abstract

Purpose Occupational stress represents a major challenge for workplace health management, particularly in industrial environments where employees are exposed to multiple psychosocial and organizational pressures. This study aimed to examine the underlying dimensions of occupational stress among industrial employees and to identify key workplace indicators associated with elevated stress levels using an integrated analytical framework. Design/methodology/approach The dataset contained questionnaire records from 98 male employees in an Iranian industrial organization. Occupational stress was assessed using the 23-item Cooper questionnaire, with items scored from 0 to 5. Factor analysis and classification included 86 employees with complete Cooper responses. Entropy weighting described distributional information, exploratory factor analysis examined shared item variation, and k-means clustering explored response-pattern groupings. Classification models used five prespecified demographic and occupational predictors and were evaluated using 20 repetitions of stratified five-fold cross-validation. Held-out SHapley Additive exPlanations’ contributions were used to interpret logistic-regression predictions. Findings Factor analysis suggested a three-factor solution accounting for 33.1% of total standardized item variance, while clustering identified two provisional response-pattern groupings. Mean Area Under the Curve (AUC) values were 0.705, 0.698 and 0.686 for logistic regression, random forest and gradient boosting, respectively. Mean classification accuracy was close to the majority-class baseline. Work shift and work experience had the largest mean absolute contributions to logistic-regression predictions. Originality/value The analyses provide an exploratory basis for organizing employee questionnaire findings and guiding subsequent workforce assessment and consultation. Independent replication, external validation and prospective evaluation are needed to establish their practical value for workplace health management.

International Journal of Workplace Health Management
University of Technology Sydney (AU), Charles Sturt University (AU), Tabriz University of Medical Sciences (IR), University of Canberra (AU)
Decent work and economic growth, Good health and well-being
Openalex Percentile: Top 12%
Workplace Health and Well-being
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