Skip to main content
Log in

The Pittsburgh Sleep Quality Index in a multi-ethnic Asian population contains a three-factor structure

Sleep and Breathing Aims and scope Submit manuscript

Abstract

Purpose

The Pittsburgh Sleep Quality Index (PSQI) is a widely used measure for assessing sleep impairment. Although it was developed as a unidimensional instrument, there is much debate that it contains multidimensional latent constructs. We examined the dimensionality of the underlying factor structure of PSQI in Singapore, a rapidly industrialising Asian country with multi-ethnicities representing the Chinese, Malays and Indians.

Methods

The PSQI was administered through an interviewer-based questionnaire in two separate population-based cross-sectional surveys. An explanatory factor analysis (EFA) was first used to explore the underlying construct of the PSQI in both studies. Then, a confirmatory factor analysis (CFA) was conducted to evaluate an optimal factor model by comparing against other possible models identified in EFA.

Results

There are three correlated yet distinguishable factors that account for an individual’s sleep experience from the same best-fit model obtained in both studies: perceived sleep quality, daily disturbances and sleep efficiency. Our three-factor structure of PSQI is superior to the originally intended unidimensional model. Our model also shows the best-fit indices when compared to the previously reported single-factor, two-factor and three-factor (by Cole et al.) models in a multi-ethnic Asian population.

Conclusion

There is strong evidence that the PSQI contains a three-factor rather than a unidimensional structure in a multi-ethnic Asian population. Scoring the PSQI along their multidimensional perspectives may provide a more accurate understanding of the relationship between sleep impairment and health conditions rather than using a single global score.

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

Access this article

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Ohayon MM (2008) Nocturnal awakenings and comorbid disorders in the American general population. J Psychiatr Res 43(1):48–54

    Article  PubMed  Google Scholar 

  2. Kim K, Uchiyama M, Okawa M, Liu X, Ogihara R (2000) An epidemiological study of insomnia among the Japanese general population. Sleep 23(1):41–47

    CAS  PubMed  Google Scholar 

  3. Weyerer S, Dilling H (1991) Prevalence and treatment of insomnia in the community: results from the Upper Bavarian Field Study. Sleep 14(5):392–398, Epub 1991/10/01

    CAS  PubMed  Google Scholar 

  4. Hohagen F, Rink K, Kappler C, Schramm E, Riemann D, Weyerer S et al (1993) Prevalence and treatment of insomnia in general practice. A longitudinal study. Eur Arch Psychiatry Clin Neurosci 242(6):329–336

    Article  CAS  PubMed  Google Scholar 

  5. Yeo BK, Perera IS, Kok LP, Tsoi WF (1996) Insomnia in the community. Singap Med J 37(3):282–284

    CAS  Google Scholar 

  6. Budhiraja R, Roth T, Hudgel DW, Budhiraja P, Drake CL (2011) Prevalence and polysomnographic correlates of insomnia comorbid with medical disorders. Sleep 34(7):859–867

    Article  PubMed Central  PubMed  Google Scholar 

  7. Sarsour K, Morin CM, Foley K, Kalsekar A, Walsh JK (2010) Association of insomnia severity and comorbid medical and psychiatric disorders in a health plan-based sample: insomnia severity and comorbidities. Sleep Med 11(1):69–74

    Article  PubMed  Google Scholar 

  8. Maia Q, Grandner MA, Findley J, Gurubhagavatula I (2013) Short and long sleep duration and risk of drowsy driving and the role of subjective sleep insufficiency. Accid Anal Prev 59:618–22

  9. Nakashima M, Morikawa Y, Sakurai M, Nakamura K, Miura K, Ishizaki M et al (2011) Association between long working hours and sleep problems in white-collar workers. J Sleep Res 20(1 Pt 1):110–116

    Article  PubMed  Google Scholar 

  10. Buysee DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ (1989) The Pittsburgh Sleep Quality Index: a new instrument for psychiatry practice and research. Psychiatr Res 28:198–213

    Google Scholar 

  11. Jimenez-Genchi A, Monteverde-Maldonado E, Nenclares-Portocarrero A, Esquivel-Adame G, de la Vega-Pacheco A (2008) Reliability and factorial analysis of the Spanish version of the Pittsburg Sleep Quality Index among psychiatric patients. Gac Med Mex 144:491–496

    PubMed  Google Scholar 

  12. Magee CA, Caputi P, Iverson DC, Huang X-F (2008) An investigation of the dimensionality of the Pittsburgh Sleep Quality Index in Australian adults. Sleep Biol Rhythms 6:222–227

    Article  Google Scholar 

  13. Carpenter JS, Andrykowski MA (1998) Psychometric evaluation of the Pittsburgh Sleep Quality Index. J Psychosom Res 45:5–13

    Article  CAS  PubMed  Google Scholar 

  14. Cole JC, Motivala SJ, Buysse DJ, Oxman MN, Levin MJ, Irwin MR (2006) Validation of a 3-factor scoring model for the Pittsburgh Sleep Quality Index in older adults. Sleep 29:112–116

    PubMed  Google Scholar 

  15. Aloba OO, Adewuya AO, Ola BA, Mapayi BM (2007) Validity of the Pittsburgh Sleep Quality Index (PSQI) among Nigerian university students. Sleep Med 8:266–270

    Article  PubMed  Google Scholar 

  16. Panayides et al (2013) Using Rasch measurement to create a quality of sleep scale for a non-clinical sample based on the Pittsburgh Sleep Quality Index (PSQI). Eur J Psychol 9(1):113–135

    Article  Google Scholar 

  17. Pittsburgh Sleep Quality Index (PSQI), Sleep Medicine Institute, University of Pittsburgh. http://www.sleep.pitt.edu/content.asp?id=1484&subid=2316 Accessed 16 May 2014

  18. Stevens JP (1992) Applied multivariate statistics for the social sciences, 2nd edn. Erlbaum, Hillsdale, NJ

    Google Scholar 

  19. Lê S, Josse J, Husson F (2008) FactoMineR: An R package for multivariate analysis. J Stat Softw 25(1):1–18

    Article  Google Scholar 

  20. Bollen KA, Long JS (1993) Testing structural equation models. Sage, Newbury Park, CA

    Google Scholar 

  21. Bentler PM, Bonett DG (1980) Significance tests and goodness-of-fit in the analysis of covariance structures. Psychol Bull 88:588–606

    Article  Google Scholar 

  22. Hu L, Bentler PM (1998) Fit indices in covariance structure modeling: sensitivity to underparameterized model misspecification. Psychol Methods 3:424–453

    Article  Google Scholar 

  23. Schumacker RE, Lomax RG (2004) A beginner’s guide to structural equation modeling, 2nd edn. Lawrence Erlbaum Associates, Inc, Mahwa, NJ

    Google Scholar 

  24. Long JS (1983) Confirmatory factor analysis. Sage, Newbury Park, CA

    Google Scholar 

  25. Raftery AE (1993) Bayesian model selection in structural equation models. In: Bollen KA, Long JS (eds) Testing structural equation models. Sage, Newbury Park, CA, pp 163–180

    Google Scholar 

  26. R Core Development Team: R: A language and environment for statistical computing. http://www.R-project.org Accessed 16 May 2014

  27. Cronbach LJ (1951) Coefficient Alpha and the internal structure of tests. Psychometrika 16:297–334

    Article  Google Scholar 

  28. Cortina JM (1993) What is coefficient alpha? An examination of theory and applications. J Appl Psychol 78:98–104

    Article  Google Scholar 

  29. Mariman A, Vogelaers D, Hanoulle I, Delesie L, Tobback E, Pevernagie D (2012) Validation of the three-factor model of the PSQI in a large sample of chronic fatigue syndrome (CFS) patients. J Psychosom Res 72(2):111–113. doi:10.1016/j.jpsychores.2011.11.004

    Article  PubMed  Google Scholar 

  30. Weng FC (2010) National Health Survey 2010, Singapore: Epidemiology & Disease Control Division, Ministry of Health. http://www.moh.gov.sg/content/moh_web/home/Publications/Reports/2011/national_health_survey2010.html. Accessed 16 May 2014

Download references

Acknowledgments

The Singapore Health (SH) survey is funded by the Ministry of Health, Singapore. The funder did not play a role in the design, conduct or analysis of the study as well as the drafting of this manuscript. The authors would also like to thank the group of Community Health Project (CHP) medical students of year 2012 from the National University of Singapore (NUS) for going out to conduct the surveys to collect data for the Queenstown study. We would also like to gratefully acknowledge Dr. Choi Hyungwon (NUS) for reading and providing editorial comments for our manuscript.

Ethical standards

Ethics review requirement was waived by the National University of Singapore (NUS) Institutional Review Board (IRB) as anonymous data was collected for the Queenstown study. For SH 2012, ethics was reviewed and approved by the NUS IRB prior to implementation. All subjects had given their informed consent prior to their inclusion in the study.

Conflict of interest

The authors declare that they have no competing interests.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hiromi W. L. Koh.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Koh, H.W.L., Lim, R.B.T., Chia, K.S. et al. The Pittsburgh Sleep Quality Index in a multi-ethnic Asian population contains a three-factor structure. Sleep Breath 19, 1147–1154 (2015). https://doi.org/10.1007/s11325-015-1130-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11325-015-1130-1

Keywords

Navigation