Skip to main content

The St George’s Respiratory Questionnaire revisited: a psychometric evaluation

Quality of Life Research volume 24, pages 67–79 (2015)Cite this article

Abstract

Purpose

The St George’s Respiratory Questionnaire (SGRQ) has clearly acquired the status of legacy questionnaire for measuring health-related quality of life in patients with chronic obstructive pulmonary disease (COPD). The main aim of this study was to assess the underlying dimensionality of the SGRQ and to investigate the added value of the empirical weights used to calculate total scores.

Methods

The official Dutch translation of the SGRQ was completed by 444 COPD patients participating in two clinical studies. These data were used for secondary data analysis in this study. Three complementary statistical methods were used to assess dimensionality: Mokken scale analysis (MSA), parametric multidimensional item response theory (IRT) and bifactor analysis. Additionally, the original SGRQ weighting procedure was compared to IRT-based weighting.

Results

The results of the MSA and multidimensional item response theory (MIRT) pointed toward a unidimensional structure. The bifactor analyses indicated that there was a strong general factor, but the group factors did have additional value. Nineteen items performed poorly in the MSA, MIRT analysis or both. Shortening the scale from 50 to 31 items did not negatively impact measurement precision. SGRQ total score and IRT-derived scores correlated strongly, 0.90 for the one-parameter model and 0.99 for the two-parameter model.

Conclusion

The SGRQ contains some multidimensionality, but an abbreviated version can be used as a unidimensional tool in patients with COPD. Subscale scores should be used with care. SGRQ total scores correlated highly with IRT-based scores, and thus, the weighting methods may be used interchangeably to calculate total scores.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

43,34 €

Price includes VAT (Finland)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2

Notes

  1. Total scale: nine items showed poor fit under the 1PL model, five under the 2PL model. Shorter scale: 3 items showed poor fit under the 1PL model, 0 under the 2PL model.

  2. To obtain the discrimination parameter per category, the parameter estimate was multiplied by category number for polytomous items. This value was then used in calculating the correlations.

Abbreviations

1PL:

One-parameter logistic

2PL:

Two-parameter logistic

CFI:

Comparative fit index

COPD:

Chronic obstructive pulmonary disease

ECV:

Explained common variance

FA:

Factor analysis

GA:

Genetic algorithm

GPCM:

Generalized partial credit model

HRQoL:

Health-related quality of life

HS:

Health status

IRT:

Item response theory

MIRT:

Multidimensional item response theory

MSA:

Mokken scale analysis

PCA:

Principal component analysis

SGRQ:

St George’s Respiratory Questionnaire

SGRQ-C:

COPD-specific version of the St George’s Respiratory Questionnaire

TLI:

Tucker-Lewis index

QoL:

Quality of life

RSMEA:

Root mean square error of approximation

VAS:

Visual analogue scale

References

  1. Jones, P. W., Quirk, F. H., & Baveystock, C. M. (1991). The St George’s Respiratory Questionnaire. Respiratory Medicine, 85(Supplement 2), 25–31.

    PubMed  Article  Google Scholar 

  2. Jones, P. W., Quirk, F. H., Baveystock, C. M., & Littlejohns, P. (1992). A self-complete measure of health status for chronic airflow limitation. The St. George’s Respiratory Questionnaire. American Review of Respiratory Disease, 145(6), 1321–1327.

    CAS  PubMed  Article  Google Scholar 

  3. Quirk, F. H., & Jones, P. W. (1990). Patients’ perception of distress due to symptoms and effects of asthma on daily living and an investigation of possible influential factors. Clinical Science (London), 79(1), 17–21.

    CAS  Google Scholar 

  4. Barr, J. T., Schumacher, G. E., Freeman, S., LeMoine, M., Bakst, A. W., & Jones, P. W. (2000). American translation, modification, and validation of the St. George’s Respiratory Questionnaire. Clinical Therapeutics, 22(9), 1121–1145.

    CAS  PubMed  Article  Google Scholar 

  5. Meguro, M., Barley, E. A., Spencer, S., & Jones, P. W. (2007). Development and validation of an Improved, COPD-specific version of the St. George Respiratory Questionnaire. Chest, 132(2), 456–463.

    PubMed  Article  Google Scholar 

  6. Embretson, S. E., & Reise, S. (2000). Item response theory for psychologists. Mahwah, NJ: Erlbaum.

    Google Scholar 

  7. Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Chicalo, IL: University of Chicago Press.

    Google Scholar 

  8. Jones, P. W. (2009). St George’s Respiratory Questionnaire: Manual. London: Division of Cardiac and Vascular Science, St George’s, University of London.

    Google Scholar 

  9. Quirk, F. H., Baveystock, C. M., Wilson, R., & Jones, P. W. (1991). Influence of demographic and disease related factors on the degree of distress associated with symptoms and restrictions on daily living due to asthma in six countries. European Respiratory Journal, 4(2), 167–171.

    CAS  PubMed  Google Scholar 

  10. Monninkhof, E., van der Valk, P., van der Palen, J., van Herwaarden, C., & Zielhuis, G. (2003). Effects of a comprehensive self-management programme in patients with chronic obstructive pulmonary disease. European Respiratory Journal, 22(5), 815–820.

    CAS  PubMed  Article  Google Scholar 

  11. Christenhusz, L. C., Prenger, R., Pieterse, M. E., Seydel, E. R., & van der Palen, J. (2012). Cost-effectiveness of an intensive smoking cessation intervention for COPD outpatients. Nicotine & Tobacco Research, 14(6), 657–663.

    Article  Google Scholar 

  12. Mokken, R. J. (1971). A theory and procedure of scale analysis. The Hague: Mouton.

    Book  Google Scholar 

  13. Sijtsma, K., & Molenaar, I. W. (2002). Introduction to nonparametric item response theory (Vol. 5). Thousand Oaks: Sage Publications.

    Google Scholar 

  14. R Development Core Team. (2012). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.

  15. van der Ark, L. A. (2007). Mokken scale analysis in R. Journal of Statistical Software, 20(11), 1–19.

    Google Scholar 

  16. Paap, M. C. S., Kreukels, B. P. C., Cohen-Kettenis, P. T., Richter-Appelt, H., de Cuypere, G., & Haraldsen, I. R. (2011). Assessing the utility of diagnostic criteria: a multisite study on gender identity disorder. Journal of Sexual Medicine, 8(1), 180–190.

    PubMed  Article  Google Scholar 

  17. Sijtsma, K., Emons, W. H., Bouwmeester, S., Nyklicek, I., & Roorda, L. D. (2008). Nonparametric IRT analysis of Quality-of-Life Scales and its application to the World Health Organization Quality-of-Life Scale (WHOQOL-Bref). Quality of Life Research, 17(2), 275–290.

    PubMed Central  PubMed  Article  Google Scholar 

  18. Wismeijer, A. A. J. (2012). Dimensionality analysis of the thought suppression inventory: Combining EFA, MSA, and CFA. Journal of Psychopathology and Behavioral Assessment, 34(1), 116–125.

    Google Scholar 

  19. Watson, R., Deary, I. J., & Shipley, B. (2008). A hierarchy of distress: Mokken scaling of the GHQ-30. Psychological Medicine, 38(04), 575–579.

    Google Scholar 

  20. Watson, R., van der Ark, L. A., Lin, L.-C., Fieo, R., Deary, I. J., & Meijer, R. R. (2012). Item response theory: How Mokken scaling can be used in clinical practice. Journal of Clinical Nursing, 21(19–20), 2736–2746.

    Google Scholar 

  21. Paap, M. C. S., Meijer, R. R., Cohen-Kettenis, P. T., Richter-Appelt, H., de Cuypere, G., Kreukels, B. P. C., et al. (2012). Why the factorial structure of the SCL-90-R is unstable: Comparing patient groups with different levels of psychological distress using Mokken Scale Analysis. Psychiatry Research, 200(2–3), 819–826.

    PubMed  Article  Google Scholar 

  22. Beukers, F., Houtzager, B. A., Paap, M. C. S., Middelburg, K. J., Hadders-Algra, M., Bos, A. F., et al. (2012). Parental psychological distress and anxiety after a successful IVF/ICSI procedure with and without preimplantation genetic screening: Follow-up of a randomised controlled trial. Early Human Development, 88(9), 725–730.

    CAS  PubMed  Article  Google Scholar 

  23. Blom, E. H., Bech, P., Hogberg, G., Larsson, J. O., & Serlachius, E. (2012). Screening for depressed mood in an adolescent psychiatric context by brief self-assessment scales—testing psychometric validity of WHO-5 and BDI-6 indices by latent trait analyses. Health Qual Life Outcomes, 10(1), 149.

    PubMed Central  PubMed  Article  Google Scholar 

  24. Roorda, L. D., Green, J. R., Houwink, A., Bagley, P. J., Smith, J., Molenaar, I. W., et al. (2012). Item hierarchy-based analysis of the Rivermead Mobility Index resulted in improved interpretation and enabled faster scoring in patients undergoing rehabilitation after stroke. Archives of Physical Medicine and Rehabilitation, 93(6), 1091–1096.

    PubMed  Article  Google Scholar 

  25. Straat, J. H., van der Ark, L. A., & Sijtsma, K. (2013). Comparing optimization algorithms for item selection in Mokken scale analysis. Journal of Classification, 30(1), 75–99.

    Google Scholar 

  26. Reise, S. P., & Waller, N. G. (2009). Item response theory and clinical measurement. Annual Review of Clinical Psychology, 5(1), 27–48.

    PubMed  Article  Google Scholar 

  27. Muraki, E. (1992). A generalized partial credit model: Application of an EM algorithm. Applied Psychological Measurement, 16(2), 159–176.

    Article  Google Scholar 

  28. van den Berg, S. M., Heuven, H. C. M., van den Berg, L., Duffy, D. L., & Serpell, J. A. (2010). Evaluation of the C-BARQ as a measure of stranger-directed aggression in three common dog breeds. Applied Animal Behaviour Science, 124(3–4), 141–146.

    Google Scholar 

  29. van den Berg, S. M., Paap, M. C. S., Derks, E. M., et al. (2013). Using multidimensional modeling to combine self-report symptoms with clinical judgment of schizotypy. Psychiatry Research, 206(1), 75–80.

    Google Scholar 

  30. Glas, C. A. W. (2010). Preliminary manual of the software program multidimensional item response theory (MIRT). Enschede: Department of Research Methodology, Measurement and Data-Analysis, University of Twente.

  31. Reise, S. P., Morizot, J., & Hays, R. D. (2007). The role of the bifactor model in resolving dimensionality issues in health outcomes measures. Quality of Life Research, 16, 19–31.

    PubMed  Article  Google Scholar 

  32. Reise, S. P. (2012). The rediscovery of bifactor measurement models. Multivariate Behavioral Research, 47(5), 667–696.

    PubMed Central  PubMed  Article  Google Scholar 

  33. Reise, S. P., Moore, T. M., & Haviland, M. G. (2010). Bifactor models and rotations: Exploring the extent to which multidimensional data yield univocal scale scores. Journal of Personality Assessment, 92(6), 544–559.

    PubMed Central  PubMed  Article  Google Scholar 

  34. Gustafsson, J.-E., & Åberg-Bengtsson, L. (2010). Unidimensionality and interpretability of psychological instruments. In S. E. Embretson (Ed.), Measuring psychological constructs: Advances in model-based approaches (pp. 97–121). Washington, DC: American Psychological Association.

  35. Reise, S. P., Scheines, R., Widaman, K. F., & Haviland, M. G. (2013). Multidimensionality and structural coefficient bias in structural equation modeling: A bifactor perspective. Educational and Psychological Measurement, 73(1), 5–26.

    Google Scholar 

  36. Schmid, J., & Leiman, J. M. (1957). The development of hierarchical factor solutions. Psychometrika, 22, 53–61.

    Article  Google Scholar 

  37. Revelle, W. (2012). Psych: Procedures for psychological, psychometric, and personality research. R package version 1.1–10. Retrieved from http://personality-project.org/r/psych.manual.pdf.

  38. Muthén, L. K., & Muthén, B. O. (2006). Mplus user’s guide, 4th, 6th edns. Los Angeles, CA: Muthén & Muthén.

  39. Cook, K. F., Kallen, M. A., & Amtmann, D. (2009). Having a fit: impact of number of items and distribution of data on traditional criteria for assessing IRT’s unidimensionality assumption. Quality Life Research, 18(4), 447–460.

    Article  Google Scholar 

  40. Hu, L., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to unparameterized model misspecification. Psychological Methods, 3, 424–453.

    Article  Google Scholar 

  41. Jones, P. W. (2002). Interpreting thresholds for a clinically significant change in health status in asthma and COPD. European Respiratory Journal, 19(3), 398–404.

    CAS  PubMed  Article  Google Scholar 

  42. Jones, P. W. (2005). St. George’s Respiratory Questionnaire: MCID. COPD: Journal of Chronic Obstructive Pulmonary Disease, 2(1), 75–79.

    PubMed  Article  Google Scholar 

  43. Al-Shair, K., Atherton, G. T., Kennedy, D., Powell, G., Denning, D. W., & Caress, A. (2013). Validity and reliability of the St. George’s Respiratory Questionnaire in assessing health status in patients with chronic pulmonary aspergillosis. Chest, 144(2), 623–631.

    Google Scholar 

  44. Weldam, S. W., Schuurmans, M. J., Liu, R., & Lammers, J. W. (2013). Evaluation of Quality of Life instruments for use in COPD care and research: A systematic review. International Journal of Nursing Studies, 50(5), 688–707.

    Google Scholar 

  45. Bae, Y. J., Kim, Y. S., Park, C. S., Lee, Y. S., Chang, Y. S., Cho, Y. S., et al. (2011). Reliability and validity of the St George’s Respiratory Questionnaire for asthma. The International Journal of Tuberculosis and Lung Disease, 15(7), 966–971.

    PubMed  Article  Google Scholar 

  46. Tafti, S. F., Cheraghvandi, A., Mokri, B., & Talischi, F. (2011). Validity and specificity of the Persian version of the Saint George Respiratory Questionnaire. Journal of Asthma, 48(6), 589–592.

    PubMed  Article  Google Scholar 

  47. Liang, W.-M., Chen, J.-J., Chang, C.-H., Chen, H.-W., Chen, S.-L., Hang, L.-W., et al. (2008). An empirical comparison of the WHOQOL-BREF and the SGRQ among patients with COPD. Quality of Life Research, 17(5), 793–800.

    PubMed Central  PubMed  Article  Google Scholar 

  48. El Rhazi, K., Nejjari, C., Benjelloun, M. C., Bourkadi, J., Afif, H., Serhier, Z., et al. (2006). Validation of the St. George’s Respiratory Questionnaire in patients with COPD or asthma in Morocco. The International Journal of Tuberculosis and Lung Disease, 10(11), 1273–1278.

    PubMed  Google Scholar 

  49. Sanjuas, C., Alonso, J., Prieto, L., Ferrer, M., Broquetas, J. M., & Anto, J. M. (2002). Health-related quality of life in asthma: A comparison between the St George’s Respiratory Questionnaire and the Asthma Quality of Life Questionnaire. Quality of Life Research, 11(8), 729–738.

    PubMed  Article  Google Scholar 

  50. Engstrom, C. P., Persson, L. O., Larsson, S., & Sullivan, M. (1998). Reliability and validity of a Swedish version of the St George’s Respiratory Questionnaire. European Respiratory Journal, 11(1), 61–66.

    CAS  PubMed  Article  Google Scholar 

  51. Ferrer, M., Alonso, J., Prieto, L., Plaza, V., Monso, E., Marrades, R., et al. (1996). Validity and reliability of the St George’s Respiratory Questionnaire after adaptation to a different language and culture: the Spanish example. European Respiratory Journal, 9(6), 1160–1166.

    CAS  PubMed  Article  Google Scholar 

  52. Yu, D. T. W., Scudds, R. J., & Scudds, R. A. (2004). Reliability and validity of a Hong Kong Chinese Version of the St George’s Respiratory Questionnaire in Patients with COPD. Hong Kong Physiotherapy Journal, 22(1), 33–39.

    Article  Google Scholar 

  53. Rutten-van Molken, M., Roos, B., & Van Noord, J. A. (1999). An empirical comparison of the St George’s Respiratory Questionnaire (SGRQ) and the Chronic Respiratory Disease Questionnaire (CRQ) in a clinical trial setting. Thorax, 54(11), 995–1003.

    CAS  PubMed  Article  Google Scholar 

  54. Karpinski, N. (2005). Validierung von Lebensqualitäts-Assessments bei chronisch–obstruktiven Atemwegserkrankungen (validation of quality of life-assessments in patients with chronic obstructive pulmonary disease). Bremen: University of Bremen. Retrieved from http://d-nb.info/991362772/34.

  55. Paap, M. C. S. (2011). Examining the validity of the assessment of gender identity disorder: Diagnosis, self-reported psychological distress and strategy adjustment. Oslo: University of Oslo. Retrieved from https://www.duo.uio.no/bitstream/handle/10852/27940/dravhandling-paap.pdf.

  56. Wismeijer, A. A. J., Sijtsma, K., van Assen, M. A. L. M., & Vingerhoets, A. J. J. M. (2008). A comparative study of the dimensionality of the self-concealment scale using principal components analysis and Mokken scale analysis. Journal of Personality Assessment, 90(4), 323–334.

    PubMed  Article  Google Scholar 

  57. Nunnally, J. C. (1978). Psychometric theory. New York: McGraw-Hill.

    Google Scholar 

  58. Timmerman, M. E. (2005). Factor analysis. Retrieved March 7, 2013, from http://www.ppsw.rug.nl/~metimmer/.

  59. Emons, W. H. M., Sijtsma, K., & Pedersen, S. S. (2012). Dimensionality of the Hospital Anxiety and Depression Scale (HADS) in cardiac patients: Comparison of Mokken Scale analysis and factor analysis. Assessment, 19(3), 337–353.

    Google Scholar 

  60. Salaffi, F., Franchignoni, F., Giordano, A., Ciapetti, A., Gasparini, S., & Ottonello, M. (2013). Classical test theory and Rasch analysis validation of the recent-onset arthritis disability questionnaire in rheumatoid arthritis patients. Clinical Rheumatology, 32(2), 211–217.

    Google Scholar 

  61. Brouwer, D., Meijer, R. R., Weekers, A. M., & Baneke, J. J. (2008). On the dimensionality of the Dispositional Hope Scale. Psychological Assessment, 20(3), 310–315.

    PubMed  Article  Google Scholar 

  62. Sousa, R. M., Dewey, M. E., Acosta, D., Jotheeswaran, A. T., Castro-Costa, E., Ferri, C. P., et al. (2010). Measuring disability across cultures–the psychometric properties of the WHODAS II in older people from seven low- and middle-income countries. The 10/66 Dementia Research Group population-based survey. International Journal of Methods In Psychiatric Research, 19(1), 1–17.

    PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgments

We thank Dr. Straat for advising us on the use of the GA algorithm. This study was supported by Grant No. 3.4.11.004 from Lung Foundation Netherlands.

Author information

Affiliations

  1. Department of Research Methodology, Measurement, and Data-Analysis, Behavioral Sciences, University of Twente, P.O. Box 217, 7500, AE, Enschede, The Netherlands

    Muirne C. S. Paap, Cees A. W. Glas & Job van der Palen

  2. University of Twente, Enschede, The Netherlands

    Benjamin Forstreuter

  3. Department of Psychometrics and Statistics, Behavioral Sciences, University of Groningen, Groningen, The Netherlands

    Danny Brouwer

  4. Julius Center for Health and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands

    Evelyn M. Monninkhof

  5. Department of Psychology, Health and Technology, Behavioral Sciences, University of Twente, Enschede, The Netherlands

    Marcel E. Pieterse

  6. Medical School Twente, Medisch Spectrum Twente, Enschede, The Netherlands

    Job van der Palen

Authors
  1. Muirne C. S. Paap
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Danny Brouwer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Cees A. W. Glas
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Evelyn M. Monninkhof
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Benjamin Forstreuter
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Marcel E. Pieterse
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Job van der Palen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Muirne C. S. Paap.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 242 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Paap, M.C.S., Brouwer, D., Glas, C.A.W. et al. The St George’s Respiratory Questionnaire revisited: a psychometric evaluation. Qual Life Res 24, 67–79 (2015). https://doi.org/10.1007/s11136-013-0570-y

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-013-0570-y

Keywords

  • Multidimensional item response theory
  • Bifactor analysis
  • SGRQ
  • Mokken scale analysis
  • COPD