Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-10T13:01:02.176Z Has data issue: false hasContentIssue false
  • English
  • Français

The Development of a Spanish Language Version of the Worn Out Scale of the General Well-Being Questionnaire (GWBQ)

Published online by Cambridge University Press:  10 April 2014

Tom Cox ,
Amparo Oliver ,
Eusebio Rial-González ,
José Manuel Tomás ,
Amanda Griffiths  and
Louise Thompson
Tom Cox
Affiliation:
Institute of Work, Health & Organizations, University of Nottingham (UK)
Amparo Oliver
Affiliation:
Universitat de València
Eusebio Rial-González
Affiliation:
Agencia Europea para la Seguridad y la Salud en el Trabajo, Bilbao (Spain)
José Manuel Tomás*
Affiliation:
Universitat de València
Amanda Griffiths
Affiliation:
Institute of Work, Health & Organizations, University of Nottingham (UK)
Louise Thompson
Affiliation:
Institute of Work, Health & Organizations, University of Nottingham (UK)
*
Correspondence concerning this article should be addressed to Dr José Manuel Tomás, Departament de Metodologia de les Ciències del Comportament, Facultat de Psicologia, Universitat de València, Av. Blasco Ibáñez, 21, 46010 Valencia, (Spain). E-mail: tomasjm@uv.es.
Get access Rights & Permissions [Opens in a new window]

Abstract

The paper describes the development of a short Spanish-language version of the General Well-Being Questionnaire (GWBQ; Cox & Gotts, 1987), based on the 12 items of its Worn Out scale. Research has shown the English-version Worn Out scale to be sensitive to aspects of the design and management of work. This study aimed to test its cross-cultural consistency in a Spanish-language workplace context. The data were collected from a sample of 229 workers in Valencia (Spain). Confirmatory Factor Analyses showed the factorial validity, reliability, and concurrent validity of the new Spanish version to be adequate. The sensitivity of the new measure to safety behavior and the reporting of accidents was also assessed and shown to be good. The new questionnaire extends the usefulness of the parent questionnaire to occupational health psychology research in the Spanish language by offering a short assessment tool appropriate for workplace studies.

El artículo describe el desarrollo de la versión corta en español del General Well-Being Questionnaire (GWBQ; Cox & Gotts, 1987; en español el “Cuestionario de Bienestar General”), basada en los 12 ítems de su subescala de “Agotamiento”. La investigación ha mostrado que la versión en inglés de la escala de Agotamiento es sensible a ciertos aspectos del diseño y gestión del trabajo. El propósito de este estudio fue comprobar la consistencia transcultural en un contexto de trabajo de habla española. Los datos se recogieron de una muestra de 229 trabajadores en Valencia (España). Análisis factoriales confirmatorios demostraron la adecuación de la validez factorial, la fiabilidad, y la validez concurrente de la nueva versión española. También se evaluó la sensibilidad de la nueva medida hacia la conducta de seguridad y distintas medidas de siniestralidad, comprobando asimismo su adecuación. El cuestionario nuevo amplía la utilidad del cuestionario original al ofrecerse como herramienta para los investigadores en psicología de la salud ocupacional en lengua española, ofreciendo un instrumento corto de evaluación apropiado para el lugar de trabajo.

Keywords

well-beingSpanish-languageoccupational healthworkplace researchbienestarespañolsalud ocupacionalinvestigación en psicología del trabajo
Type
Articles
Information
The Spanish Journal of Psychology , Volume 9 , Issue 1 , May 2006 , pp. 94 - 102
Copyright
Copyright © Cambridge University Press 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Babakus, E., Ferguson, C.E., & Jöreskog, K.G. (1987). The sensitivity of confirmatory factor maximum likelihood factor analysis to violations of measurement scale and distributional assumptions. Journal of Marketing Research, 37, 72–141.Google Scholar
Bagozzi, R P., & Heatherton, T.F. (1994). A general approach to representing multifaceted personality constructs: Application to state self-esteem. Structural Equation Modeling, 1, 35–67.CrossRefGoogle Scholar
Bentler, P.M. (1995). EQS for Macintosh user's guide. Encino, CA: Multivariate Software.Google Scholar
Bentler, P.M., & Bonett, D.G. (1980). Significance tests and goodness-of-fit in the analysis of covariance structures. Psychological Bulletin, 88, 588–606.CrossRefGoogle Scholar
Bollen, K.A. (1989). Structural equations with latent variables. New York: Wiley.CrossRefGoogle Scholar
Bollen, K.A., & Barb, K.H. (1981). Pearson's r and coarsely categorized measures. American Sociological Review, 46, 232–239.CrossRefGoogle Scholar
Boomsma, A. (1983). On the robustness of LISREL (maximum likelihood estimation) against small sample size and nonnormality. Unpublished doctoral dissertation, University of Gröningen, Gröningen (Germany).Google Scholar
Browne, M.W. (1984). Asymptotically distribution-free methods for the analysis of covariance structures. British Journal of Mathematical and Statistical Psychology, 37, 62–83.CrossRefGoogle ScholarPubMed
Browne, M.W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In Bollen, K.A. & Long, J.S. (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage.Google Scholar
Cox, T., & Gotts, G. (1987). The General Well-Being Questionnaire Manual. Nottingham, UK: University of Nottingham, Department of Psychology.Google Scholar
Cox, T., & Griffiths, A.J. (1996). The assessment of psychosocial hazards at work. In Schabracq, M.J.Winnubst, J.A.M., & Cooper, C.L. (Eds.), Handbook of work and health psychology. Chichester, UK: Wiley.Google Scholar
Cox, T., Griffiths, A.J., Barlow, C.A., Randall, R.J., Thomson, L.E., & Rial-González, E. (2000). Organisational interventions for work stress. Sudbury, UK: HSE Books.Google Scholar
Cox, T., Griffiths, A.J., & Rial-González, E. (2000). Research on work-related stress. Luxembourg: Office for Official Publications of the European Communities.Google Scholar
Cox, T., & Mackay, C.J. (1985). The measurement of self-reported stress and arousal. British Journal of Psychology, 76, 183–186.CrossRefGoogle ScholarPubMed
Cox, T., Thirlaway, M., Gotts, G., & Cox, S. (1983). The nature and assessment of general well-being. Journal of Psychosomatic Research, 27, 353–359.CrossRefGoogle ScholarPubMed
Crown, S., & Crisp, A.H. (1966). A short clinical diagnostic self rating scale for psychoneurotic patients. The Middlesex Hospital Questionnaire (MHQ). British Journal of Psychiatry, 112, 917–923.CrossRefGoogle Scholar
Daniel, C., & Wood, F.S. (1980). Fitting equations to data. New York: Wiley.Google Scholar
Dunn, G., Everitt, B., & Pickles, A. (1993). Modelling covariances and latent variables using EQS. London: Chapman and Hall.Google Scholar
Ferguson, E., & Cox, T. (1993). Exploratory factor analysis: A user's guide. International Journal of Selection and Assessment, 1, 84–94.CrossRefGoogle Scholar
Gerbing, D.W., & Anderson, J.C. (1993). Monte Carlo evaluations of goodness-of-fit indices for structural equation models. In Bollen, K.A. & Long, J.S. (Eds.), Testing structural equation models (pp. 40–65). Newbury Park, CA: Sage.Google Scholar
Goldberg, D.P. (1972). The detection of psychiatric illness by questionnaire [Maudsley Monograph no 21]. London: Oxford University Press.Google Scholar
Ho, J. (1996). School organizational health and teacher stress in Singapore. Unpublished doctoral dissertation, University of Nottingham, UK.Google Scholar
Hoyle, R.H. (1995). Structural equation modeling: Concepts, issues and applications. Newbury Park, CA: Sage.Google Scholar
Hoyle, R.H., & Panter, A.T. (1995). Writing about structural equation models. In Hoyle, R.H. (Ed.), Structural equation modeling: Concepts, issues and applications (pp. 158–176). Thousand Oaks, CA: Sage.Google Scholar
Hu, L.T., & Bentler, P.M. (1995). Evaluating model fit. In Hoyle, R.H. (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 76–99). Thousand Oaks, CA: Sage.Google Scholar
Hu, L.T., Bentler, P.M., & Kano, Y. (1992). Can test statistics in covariance structure analysis be trusted? Psychological Bulletin, 112, 351–362.CrossRefGoogle ScholarPubMed
Jöreskog, K.G., & Sörbom, D. (1984). LISREL VI user's guide (3rd ed.). Mooresville, IN: Scientific Software.Google Scholar
Loehlin, J.C. (1998). Latent variable models. New Jersey: Erlbaum.Google Scholar
Mackay, C.J., Cox, T.Burrows, G. & Lazzerini, T. (1978). An inventory for the measurement of self-reported stress and arousal. British Journal of Social and Clinical Psychology, 17, 283–284.CrossRefGoogle ScholarPubMed
Marsh, H.W., Balla, J.R., & Hau, K.T. (1996). An evaluation of incremental fit indices: A clarification of mathematical and empirical properties. In Marcoulides, G.A. & Schumacker, R.E. (Eds.), Advanced structural equation modeling: Issues and techniques (pp. 315–353). Mahwah, NJ: Erlbaum.Google Scholar
Marsh, H.W., Balla, J.R., & McDonald, R.P. (1988). Goodness-of-fit indices in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 102, 391–410.CrossRefGoogle Scholar
Maslach, C., & Jackson, S.E. (1981). Maslach Burnout Inventory. Palo Alto, CA: Consulting Psychologist Press.Google Scholar
Muthen, B. (1984). A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicators. Psychometrika, 49, 115–132.CrossRefGoogle Scholar
Muthen, B., & Kaplan, D. (1985). A comparison of methodologies for the factor analysis of non-normal Likert variables. British Journal of Mathematical and Statistical Psychology, 38, 171–189.CrossRefGoogle Scholar
Muthen, B., & Kaplan, D. (1992). A comparison of some methodologies for the factor analysis of non-normal Likert variables: A note on the size of the model. British Journal of Mathematical and Statistical Psychology, 45, 19–30.CrossRefGoogle Scholar
Nunnally, J.C., & Bernstein, I.H. (1994). Psychometric Theory (3rd ed.). New York: McGraw-Hill.Google Scholar
Oliver, A., Sancerni, M.D., Tomás, J.M. & Lis, R. (1995). Métodos de estimación y tamaños muestrales en análisis factorial confirmatorio: Implicaciones en la validez factorial del GHQ. Psicológica, 16, 101–114.Google Scholar
Oliver, A., & Tomás, J.M. (1995). Índices de ajuste absolutos e incrementales: comportamiento en análisis factorial confirmatorio con muestras pequeñas Psicológica, 16, 1, pp.49–64.Google Scholar
Rogers, E.H. (1960). The ecology of health. New York: MacMillan.Google Scholar
Ruey-Fa, L. (1994). Organisational healthiness, stress, and well-being. Unpublished doctoral dissertation, University of Nottingham, UK.Google Scholar
Satorra, A. (1990). Robustness issues in structural equation modeling: A review of recent developments. Quality and Quantity, 24, 367–386.CrossRefGoogle Scholar
Schaufeli, W. & Maslach, C., & Marek, T. (Eds.) (1993). Professional burnout: Recent developments in theory and research. New York: Hemisphere.Google Scholar
Tanaka, J.S. (1993). Multifaceted conceptions of fit in structural equation models. In Bollen, K.A. & Long, J.S. (Eds.), Testing structural equation models (pp. 10–39). Newbury Park, CA: Sage.Google Scholar
West, S.G., Finch, J.F., & Curran, P.J. (1995). Structural equation models with non-normal variables. In Hoyle, R.H. (Ed.), Structural equation modeling: Concepts, issues and applications, (pp.56–75). Thousand Oaks, CA: Sage.Google Scholar
Wilson, J., & Corlett, N. (1995). The evaluation of human work: A practical ergonomics methodology. London: Taylor and Francis.Google Scholar
World Health Organization (1946). World Health Organization: Basic Documents (26th ed.). Geneva: World Health Organization.Google Scholar