A psychometric analysis of the Stress Management Competency Indicator Tool
T Dulal-Arthur1,2, J Hassard2, W Wang1
1Schools of Medicine & Health Sciences, University of Nottingham, Nottingham, UK, NG7 2UH.
Occupational Medicine (Oxford, England)
|May 27, 2025
Summary
A new, shortened Stress Management Competency Indicator Tool (SMCIT) offers a practical solution for assessing managerial stress competencies. This validated 19-item tool maintains rigor while improving efficiency for workplace well-being initiatives.
Area of Science:
- Occupational Health Psychology
- Organizational Behavior
- Management Science
Background:
- Work-related stress is a significant UK concern, impacting employees and organizations.
- Current assessment tools for managerial stress competencies are often impractical for regular use.
- Effective managerial practices are crucial for mitigating workplace stress.
Purpose of the Study:
- To develop and validate a shortened version of the 36-item Stress Management Competency Indicator Tool (SMCIT).
- To enhance the practicality and relevance of the SMCIT for contemporary working environments.
- To ensure the shortened tool maintains reliability and validity in assessing stress management competencies.
Main Methods:
- Secondary data analysis of 224 line managers across 12 organizations.
- Principle component analysis used to reduce the SMCIT from 36 to 19 items.
- Psychometric analysis (Cronbach's alpha, factor loadings, variance explained) to ensure measurement rigor.
Main Results:
- The 19-item SMCIT retained four key constructs: respectful/responsible, managing individuals within teams, conflict/problem management, and organizational resources.
- The revised tool explained 46% of variance (vs. 37% original), with factor loadings from 0.43 to 0.86.
- Reliability scores (0.65–0.69) indicated moderate internal consistency.
Conclusions:
- The shortened SMCIT is a reliable and practical tool for evaluating line management competencies.
- It reduces response burden and improves data quality, relevant for hybrid working models.
- Further validation via confirmatory factor analysis and expert review is recommended for occupational settings.
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