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Les déterminants du stress professionnel ressenti : une estimation par la méthode des équations d’estimation généralisées

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  • Lisa Bellinghausen
  • Nicolas Vaillant

Abstract

[eng] We study the explanatory factors for self-reported stress levels of employees in a large French firm, using the ten-item “ subjective stress scale ”. Applying the generalized estimating equations (GEE) method, we obtain two results. First, there are many gender-related differences in subjective stress. Second, the use of a stress score - constructed as a linear combination of scores obtained for each item - proves debatable. Despite the information obtained in the analysis, the fact remains that many exogenous factors can influence the subjective stress level. Sometimes, these factors are hard to measure. Examples include physiological predispositions and the influence of social and work partners. [fre] Cet article étudie les facteurs explicatifs du niveau de stress auto-déclaré des salariés d’une grande firme française. L’échelle dite de Stress Perçu à 10 items est utilisée. Sur la base de la méthodologie GEE (Generalized Estimating Equations), nous obtenons deux résultats. Tout d’abord, il existe de nombreuses différences de stress perçu liées au genre. En outre, l’utilisation d’un score de stress construit comme une combinaison linéaire des scores obtenus à chaque item se révèle discutable. En dépit des informations obtenues dans l’analyse, il reste qu’il existe de nombreux facteurs exogènes susceptibles de jouer sur le niveau de stress ressenti, parfois difficiles à mesurer (prédispositions physiologiques, influence des partenaires sociaux et professionnels, etc .).

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  • Lisa Bellinghausen & Nicolas Vaillant, 2010. "Les déterminants du stress professionnel ressenti : une estimation par la méthode des équations d’estimation généralisées," Économie et Prévision, Programme National Persée, vol. 195(4), pages 67-82.
    • Handle: RePEc:prs:ecoprv:ecop_0249-4744_2010_num_195_4_8061
    DOI: 10.3406/ecop.2010.8061
    Note: DOI:10.3406/ecop.2010.8061
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    1. Li, Yonghai & Schafer, Daniel W., 2008. "Likelihood analysis of the multivariate ordinal probit regression model for repeated ordinal responses," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3474-3492, March.
    2. Brent A. Coull & Alan Agresti, 2000. "Random Effects Modeling of Multiple Binomial Responses Using the Multivariate Binomial Logit-Normal Distribution," Biometrics, The International Biometric Society, vol. 56(1), pages 73-80, March.
    3. Cécile Bourreau-Dubois & Olivier Guillot & Éliane Jankeliowitch-Laval, 2001. "Le travail à temps partiel féminin et ses déterminants," Économie et Statistique, Programme National Persée, vol. 349(1), pages 41-61.
    4. Nores, Maria Laura & Diaz, Maria del Pilar, 2008. "Some properties of regression estimators in GEE models for clustered ordinal data," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3877-3888, March.
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    1. Rahma Daly & Marc-Arthur Diaye, 2017. "Do Performance Appraisals Decrease Employees’ Perception of Their Psychosocial Risks?," Documents de recherche 17-04, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.

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