ArticleOccupational medicine (Oxford, England)2025
A psychometric analysis of the Stress Management Competency Indicator Tool.
Article in Occupational medicine (Oxford, England), 2025. 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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6 authors.
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Abstract
backgroundWork-related stress is a growing concern in the UK, negatively impacting both employee well-being and organizational effectiveness. Addressing work-related stress through effective managerial practices is essential, however, existing tools are often lengthy and impractical for routine use.
aimsThe study aimed to develop and validate a shortened version of the 36-item Stress Management Competency Indicator Tool (SMCIT) to enhance its practicality and relevance to changing working practices, while maintaining reliability and validity in assessing stress management competencies.
methodsA secondary data analysis was undertaken using data from 224 line managers across 12 organizations. Principle component analysis was applied to reduce the SMCIT from 36 to 19 items. Psychometric analysis, including Cronbach's alpha, factor loadings and total variance explained, was used to ensure the shortened tool retained its measurement rigour.
resultsThe 19-item SMCIT retained four latent constructs: respectful/ responsible, managing the individual within the team, conflict/problem management and organizational resources. The revised tool explained 46% of the variance, compared to 37% for the original, and showed factor loadings ranging from point 0.43 to 0.86. Reliability scores ranged from 0.65 to 0.69, indicating moderate internal consistency. We conclude that the shortened tool enhances measurement efficiency by removing redundant items, while maintaining key competencies.
conclusionsThe shortened SMCIT is a reliable and practical tool for evaluating line management competencies, reducing response burden while improving data quality and relevance to hybrid working. We recommend further validation through confirmatory factor analysis and expert review to enhance its application in occupational settings.
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