Skip to main content
SpringerLink
Log in

Testing gender invariance of the Hospital Anxiety and Depression Scale using the classical approach and Bayesian approach

  • Published:
Quality of Life Research Aims and scope Submit manuscript

Abstract

Purpose

Measurement invariance is an important attribute for the Hospital Anxiety and Depression Scale (HADS). Most of the confirmatory factor analysis studies on the HADS adopt the classical maximum likelihood approach. The restrictive assumptions of exact-zero cross-loadings and residual correlations in the classical approach can lead to inadequate model fit and biased parameter estimates. The present study adopted both the classical approach and the alternative Bayesian approach to examine the measurement and structural invariance of the HADS across gender.

Methods

A Chinese sample of 326 males and 427 females was used to examine the two-factor model of the HADS across gender. Configural and scalar invariance of the HADS were evaluated using the classical approach with the robust-weighted least-square estimator and the Bayesian approach with zero-mean, small-variance informative priors to cross-loadings and residual correlations.

Results

Acceptable and excellent model fits were found for the two-factor model under the classical and Bayesian approaches, respectively. The two-factor model displayed scalar invariance across gender using both approaches. In terms of structural invariance, females showed a significantly higher mean in the anxiety factor than males under both approaches.

Conclusion

The HADS demonstrated measurement invariance across gender and appears to be a well-developed instrument for assessment of anxiety and depression. The Bayesian approach is an alternative and flexible tool that could be used in future invariance studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Zigmond, A. S., & Snaith, R. P. (1983). The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica, 67(6), 361–370.

    Article  CAS  PubMed  Google Scholar 

  2. Bjelland, I., Dahl, A. A., Haug, T. T., & Neckelmann, D. (2002). The validity of the Hospital Anxiety and Depression Scale: An updated literature review. Journal of Psychosomatic Research, 52(2), 69–77. doi:10.1016/s0022-3999(01)00296-3.

    Article  PubMed  Google Scholar 

  3. Herrmann, C. (1997). International experiences with the hospital anxiety and depression scale—A review of validation data and clinical results. Journal of Psychosomatic Research, 42(1), 17–41. doi:10.1016/s0022-3999(96)00216-4.

    Article  CAS  PubMed  Google Scholar 

  4. Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. doi:10.1177/109442810031002.

    Article  Google Scholar 

  5. Schmitt, N., & Kuljanin, G. (2008). Measurement invariance: Review of practice and implications. Human Resource Management Review, 18(4), 210–222. doi:10.1016/j.hrmr.2008.03.003.

    Article  Google Scholar 

  6. Hunt-Shanks, T., Blanchard, C., Reid, R., Fortier, M., & Cappelli, M. (2010). A psychometric evaluation of the Hospital Anxiety and Depression Scale in cardiac patients: Addressing factor structure and gender invariance. British Journal of Health Psychology, 15, 97–114. doi:10.1348/135910709x432745.

    Article  PubMed  Google Scholar 

  7. Gale, C. R., Allerhand, M., Sayer, A. A., Cooper, C., Dennison, E. M., Starr, J. M., et al. (2010). The structure of the Hospital Anxiety and Depression Scale in four cohorts of community-based, healthy older people: The HALCyon program. International Psychogeriatrics, 22(4), 559–571. doi:10.1017/s1041610210000256.

    Article  PubMed  Google Scholar 

  8. Annunziata, M. A., Muzzatti, B., & Altoe, G. (2011). Defining Hospital Anxiety and Depression Scale (HADS) structure by confirmatory factor analysis: A contribution to validation for oncological settings. Annals of Oncology, 22(10), 2330–2333. doi:10.1093/annonc/mdq750.

    Article  CAS  PubMed  Google Scholar 

  9. Markland, D. (2007). The golden rule is that there are no golden rules *: A commentary on Paul Barrett’s recommendations for reporting model fit in structural equation modelling. Personality and Individual Differences, 42(5), 851–858. doi:10.1016/j.paid.2006.09.023.

    Article  Google Scholar 

  10. Yuan, K. H., & Bentler, P. M. (2004). On Chi square difference and z tests in mean and covariance structure analysis when the base model is misspecified. Educational and Psychological Measurement, 64(5), 737–757. doi:10.1177/0013164404264853.

    Article  Google Scholar 

  11. Millsap, R. E. (2007). Structural equation modeling made difficult. Personality and Individual Differences, 42(5), 875–881. doi:10.1016/j.paid.2006.09.021.

    Article  Google Scholar 

  12. Kolenikov, S. (2011). Biases of parameter estimates in misspecified structural equation models. Sociological methodology, 41, 119–157. doi:10.1111/j.1467-9531.2011.01236.x.

  13. Cole, D. A., Ciesla, J. A., & Steiger, J. H. (2007). The insidious effects of failing to include design-driven correlated residuals in latent-variable covariance structure analysis. Psychological Methods, 12(4), 381–398. doi:10.1037/1082-989x.12.4.381.

    Article  PubMed  Google Scholar 

  14. Muthen, B., & Asparouhov, T. (2012). Bayesian structural equation modeling: A more flexible representation of substantive theory. Psychological Methods, 17(3), 313–335. doi:10.1037/a0026802.

    Article  PubMed  Google Scholar 

  15. Kaplan, D., & Depaoli, S. (2012). Bayesian structural equation modeling. In R. Hoyle (Ed.), Handbook of structural equation modeling. New York, NY: Guilford Press.

    Google Scholar 

  16. Fong, T. C. T., & Ho, R. T. H. (2013). Factor analyses of the Hospital Anxiety and Depression Scale: A Bayesian structural equation modeling approach. Quality of Life Research, 1–7. doi:10.1007/s11136-013-0429-2.

  17. Leung, C. M., Wing, Y. K., Kwong, P. K., Lo, A., & Shum, K. (1999). Validation of the Chinese-Cantonese version of the Hospital Anxiety and Depression Scale and comparison with the Hamilton Rating Scale of Depression. Acta Psychiatrica Scandinavica, 100(6), 456–461.

    Article  CAS  PubMed  Google Scholar 

  18. Muthen, L. K., & Muthen, B. (1998–2012). Mplus user’s guide (7th ed.). Los Angeles, CA: Muthen & Muthen.

  19. Schmitt, T. A. (2011). Current methodological considerations in exploratory and confirmatory factor analysis. Journal of Psychoeducational Assessment, 29(4), 304–321. doi:10.1177/0734282911406653.

    Article  Google Scholar 

  20. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. doi:10.1080/10705519909540118.

    Article  Google Scholar 

  21. Asparouhov, T., & Muthen, B. (2010). Bayesian analysis of latent variable models using Mplus (Technical report). Los Angeles, CA: Muthen & Muthen.

    Google Scholar 

  22. Lee, S. Y., & Song, X. Y. (2012). Basic and advanced Bayesian structural equation modeling: With applications in the medical and behavioral sciences. Chichester, UK: Wiley.

    Google Scholar 

  23. Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2004). Bayesian data analysis (2nd ed.). Boca Raton, FL: Chapman & Hall.

    Google Scholar 

  24. Verhagen, A. J., & Fox, J. P. (2012). Bayesian tests of measurement invariance. British Journal of Mathematical and Statistical Psychology,. doi:10.1111/j.2044-8317.2012.02059.x.

    PubMed  Google Scholar 

  25. Muthen, B., & Asparouhov, T. (2013). BSEM measurement invariance analysis. Mplus Web Notes, 17, 1–48.

    Google Scholar 

  26. MacCallum, R. C., Edwards, M. C., & Cai, L. (2012). Hopes and cautions in implementing Bayesian structural equation modeling. Psychological Methods, 17(3), 340–345. doi:10.1037/a0027131.

    Article  PubMed  Google Scholar 

  27. Rindskopf, D. (2012). Next steps in Bayesian structural equation models: Comments on, variations of, and extensions to Muthen and Asparouhov (2012). Psychological Methods, 17(3), 336–339. doi:10.1037/a0027130.

    Article  PubMed  Google Scholar 

  28. Muthen, B., & Asparouhov, T. (2012). Rejoinder to MacCallum, Edwards, and Cai (2012) and Rindskopf (2012): Mastering a new method. Psychological Methods, 17(3), 346–353. doi:10.1037/a0029214.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Centre on Behavioral Health, 2/F, The Hong Kong Jockey Club Building for Interdisciplinary Research, 5 Sassoon Road, Pokfulam, Hong Kong, SAR

    Ted C. T. Fong

  2. Centre on Behavioral Health and Department of Social Work and Social Administration, The University of Hong Kong, Pokfulam, Hong Kong, SAR

    Rainbow T. H. Ho

Authors
  1. Ted C. T. Fong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rainbow T. H. Ho
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ted C. T. Fong.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Fong, T.C.T., Ho, R.T.H. Testing gender invariance of the Hospital Anxiety and Depression Scale using the classical approach and Bayesian approach. Qual Life Res 23, 1421–1426 (2014). https://doi.org/10.1007/s11136-013-0594-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-013-0594-3

Keywords

Search

Navigation