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Leymann Inventory of Psychological Terror Scale: Development and Validation for Portuguese Accounting Professionals

Author

Listed:
  • Rui Silva

    (Department of Economy, Sociology and Management, University of Trás-os-Montes e Alto Douro—CETRAD, 5000-801 Vila Real, Portugal)

  • Margarida Simões

    (Department of Education and Psychology, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal)

  • Ana Paula Monteiro

    (Department of Education and Psychology, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal)

  • António Dias

    (Department of Economy, Sociology and Management, University of Trás-os-Montes e Alto Douro—CETRAD, 5000-801 Vila Real, Portugal)

Abstract

This research aims to adapt the Leymann Inventory of Psychological Terror and its use on Portuguese Accounting Professionals. Leymann scale was applied in a final sample of 478 accountants aged between 28 and 68, of which 47.5% were men and 52.5% women. We used a quantitative methodology by applying a questionnaire survey whose results were, in the following research phase, analyzed using the statistical packages SPSS 26 and AMOS 27. We used SPSS 26 for the Descriptive Statistical Analysis and AMOS 27 to estimate the structural equation model that validated the scale. After the scale had been adapted and changed, it was validated in psychometric terms to be applied to and used in studies involving this type of professionals. The Accountants Leymann Inventory of Psychological Terror that resulted from adapting the original model was tested using structural equation modelling. Thus, the new scale produced significant results similar to those of the original scale, which means that it is valid and can be applied to other contexts. The validity and statistical reliability of the new scale made it possible to measure mobbing problems among accounting professionals reliably and robustly. The present research is an important contribution to the literature. Although it has been applied in several contexts, it is the first time it is being developed, adapted, and validated for accounting professionals who work in this area of management.

Suggested Citation

  • Rui Silva & Margarida Simões & Ana Paula Monteiro & António Dias, 2021. "Leymann Inventory of Psychological Terror Scale: Development and Validation for Portuguese Accounting Professionals," Economies, MDPI, vol. 9(3), pages 1-15, June.
    • Handle: RePEc:gam:jecomi:v:9:y:2021:i:3:p:94-:d:580211
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    References listed on IDEAS

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    1. Salin, Denise, 2006. "Organizational Measures Taken against Workplace Bullying: The Case of Finnish Municipalities," Working Papers 521, Hanken School of Economics.
    2. Hanafiah Haji Hasin & Normah Haji Omar, 2007. "An Empirical Study on Job Satisfaction, Job‐Related Stress and Intention to Leave Among Audit Staff in Public Accounting Firms in Melaka," Journal of Financial Reporting and Accounting, Emerald Group Publishing Limited, vol. 5(1), pages 21-39, December.
    3. Hanafiah Haji Hasin & Normah Haji Omar, 2007. "An Empirical Study on Job Satisfaction, Job‐Related Stress and Intention to Leave Among Audit Staff in Public Accounting Firms in Melaka," Journal of Financial Reporting and Accounting, Emerald Group Publishing Limited, vol. 5(1), pages 21-39, December.
    4. Colin Cameron, A. & Windmeijer, Frank A. G., 1997. "An R-squared measure of goodness of fit for some common nonlinear regression models," Journal of Econometrics, Elsevier, vol. 77(2), pages 329-342, April.
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