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Nonrestorative sleep scale: reliable and valid for the Chinese population

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Abstract

Purpose

To conduct a linguistic and psychometric evaluation of a Chinese version of the Nonrestorative Sleep Scale (NRSS).

Methods

The Chinese NRSS was created from a standard forward–backward translation and trialed on 10 Chinese adults. Telephone interviews were then conducted with 100 adults, who completed the Chinese NRSS, the Pittsburgh Sleep Quality Index (PSQI), the Athens Insomnia Scale (AIS), the Center for Epidemiological Studies Depression Scale (CES-D), and the Toronto Hospital Alertness Test (THAT). A household survey was conducted with 20 subjects, followed by a confirmatory factor analysis (CFA), and a bifactor model was developed to evaluate the reliability and validity of the NRSS.

Results

The bifactor model had the root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), and comparative fit index (CFI) of 0.06, 0.06, and 0.97, respectively. Convergent validity was shown from the moderate associations with PSQI (r = − 0.66, P < 0.01), AIS (r = − 0.65, P < 0.01), CES-D (r = − 0.54, P < 0.01), and THAT (r = 0.68, P < 0.01). The coefficient omega (0.92), omega hierarchical (0.81), factor determinacy (0.93), H value (0.91), explained common variance (0.63), and percentage of uncontaminated correlations (0.80) derived from the bifactor CFA supported the essential unidimensionality of NRSS.

Conclusions

The Chinese NRSS is a valid and reliable essential unidimensional tool for the assessment of nonrestorative sleep in the Chinese population.

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References

  1. Stone, K. C., Taylor, D. J., McCrae, C. S., Kalsekar, A., & Lichstein, K. L. (2008). Nonrestorative sleep. Sleep Medicine Reviews, 12(4), 275–288. https://doi.org/10.1016/j.smrv.2007.12.002.

    Article  PubMed  Google Scholar 

  2. American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed). Washington, DC: American Psychiatric Association.

    Google Scholar 

  3. Sateia, M. J. (2014). International classification of sleep disorders-third edition: Highlights and modifications. Chest, 146(5), 1387–1394. https://doi.org/10.1378/chest.14-0970.

    Article  PubMed  Google Scholar 

  4. Sarsour, K., Van Brunt, D. L., Johnston, J. A., Foley, K. A., Morin, C. M., & Walsh, J. K. (2010). Associations of nonrestorative sleep with insomnia, depression, and daytime function. Sleep Medicine, 11(10), 965–972. https://doi.org/10.1016/j.sleep.2010.08.007.

    Article  PubMed  Google Scholar 

  5. American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders (5th ed). Arlington: American Psychiatric Association.

    Book  Google Scholar 

  6. Roth, T., Jaeger, S., Jin, R., Kalsekar, A., Stang, P. E., & Kessler, R. C. (2006). Sleep problems, comorbid mental disorders, and role functioning in the national comorbidity survey replication. Biological Psychiatry, 60(12), 1364–1371. https://doi.org/10.1016/j.biopsych.2006.05.039.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Ohayon, M. M. (2005). Prevalence and correlates of nonrestorative sleep complaints. Archives of Internal Medicine, 165(1), 35–41. https://doi.org/10.1001/archinte.165.1.35.

    Article  PubMed  Google Scholar 

  8. Chiu, H. Y., Wang, M. Y., Chang, C. K., Chen, C. M., Chou, K. R., Tsai, J. C., et al. (2014). Early morning awakening and nonrestorative sleep are associated with increased minor non-fatal accidents during work and leisure time. Accident Analysis & Prevention, 71, 10–14. https://doi.org/10.1016/j.aap.2014.05.002.

    Article  Google Scholar 

  9. Kawada, T. (2012). Feeling refreshed by sleep can predict psychological wellbeing assessed using the general health questionnaire in male workers: A 3-year follow-up study. Psychiatry Investigation, 9(4), 418–421. https://doi.org/10.4306/pi.2012.9.4.418.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Liedberg, G. M., Bjork, M., & Borsbo, B. (2015). Self-reported nonrestorative sleep in fibromyalgia: Relationship to impairments of body functions, personal function factors, and quality of life. Journal of Pain Research, 8, 499–505. https://doi.org/10.2147/JPR.S86611.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Park, J. H., Yoo, J. H., & Kim, S. H. (2013). Associations between non-restorative sleep, short sleep duration and suicidality: Findings from a representative sample of Korean adolescents. Psychiatry and Clinical Neurosciences, 67(1), 28–34. https://doi.org/10.1111/j.1440-1819.2012.02394.x.

    Article  PubMed  Google Scholar 

  12. Okamoto, M., Kobayashi, Y., Nakamura, F., & Musha, T. (2017). Association between nonrestorative sleep and risk of diabetes: A cross-sectional study. Behavioural Sleep Medicine, 15(6), 483–490. https://doi.org/10.1080/15402002.2016.1163701.

    Article  Google Scholar 

  13. Zhang, J., Lam, S. P., Li, S. X., Li, A. M., & Wing, Y. K. (2012). The longitudinal course and impact of non-restorative sleep: A five-year community-based follow-up study. Sleep Medicine, 13(6), 570–576. https://doi.org/10.1016/j.sleep.2011.12.012.

    Article  PubMed  Google Scholar 

  14. Mariman, A. N., Vogelaers, D. P., Tobback, E., Delesie, L. M., Hanoulle, I. P., & Pevernagie, D. A. (2013). Sleep in the chronic fatigue syndrome. Sleep Medicine Reviews, 17(3), 193–199. https://doi.org/10.1016/j.smrv.2012.06.003.

    Article  PubMed  Google Scholar 

  15. Vernon, M. K., Dugar, A., Revicki, D., Treglia, M., & Buysse, D. (2010). Measurement of non-restorative sleep in insomnia: A review of the literature. Sleep Medicine Reviews, 14(3), 205–212. https://doi.org/10.1016/j.smrv.2009.10.002.

    Article  PubMed  Google Scholar 

  16. Wilkinson, K., & Shapiro, C. (2012). Nonrestorative sleep: symptom or unique diagnostic entity? Sleep Medicine, 13(6), 561–569. https://doi.org/10.1016/j.sleep.2012.02.002.

    Article  PubMed  Google Scholar 

  17. Wilkinson, K., & Shapiro, C. (2013). Development and validation of the Nonrestorative Sleep Scale (NRSS). Journal of Clinical Sleep Medicine, 9(9), 929–937. https://doi.org/10.5664/jcsm.2996.

    Article  PubMed  PubMed Central  Google Scholar 

  18. National Sleep Foundation. (2010). Sleep differences among ethnic groups revealed in new poll. ScienceDaily. Retrieved March 27, 2010 from https://www.sciencedaily.com/releases/2010/03/100308081740.htm.

  19. Chen, X., Wang, R., Zee, P., Lutsey, P. L., Javaheri, S., Alcantara, C., et al. (2015). Racial/ethnic differences in sleep disturbances: The multi-ethnic study of atherosclerosis (MESA). Sleep, 38(6), 877–888. https://doi.org/10.5665/sleep.4732.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Anthoine, E., Moret, L., Regnault, A., Sebille, V., & Hardouin, J. B. (2014). Sample size used to validate a scale: A review of publications on newly-developed patient reported outcomes measures. Health and Quality Life Outcomes, 12, 176. https://doi.org/10.1186/s12955-014-0176-2.

    Article  Google Scholar 

  21. Tsang, S., Royse, C. F., & Terkawi, A. S. (2017). Guidelines for developing, translating, and validating a questionnaire in perioperative and pain medicine. Saudi Journal of Anaesthesia, 11(Suppl 1), S80–S89. https://doi.org/10.4103/sja.SJA_203_17.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Chong, A. M. L., & Cheung, C.-K. (2012). Factor structure of a Cantonese-version pittsburgh sleep quality index. Sleep and Biological Rhythms, 10(2), 118–125. https://doi.org/10.1111/j.1479-8425.2011.00532.x.

    Article  Google Scholar 

  23. Chung, K. F., Kan, K. K., & Yeung, W. F. (2011). Assessing insomnia in adolescents: Comparison of Insomnia Severity Index, Athens Insomnia Scale and Sleep Quality Index. Sleep Medicine, 12(5), 463–470. https://doi.org/10.1016/j.sleep.2010.09.019.

    Article  PubMed  Google Scholar 

  24. Soldatos, C. R., Dikeos, D. G., & Paparrigopoulos, T. J. (2000). Athens Insomnia Scale: Validation of an instrument based on ICD-10 criteria. Journal of Psychosomatic Research, 48(6), 555–560. https://doi.org/10.1016/S0022-3999(00)00095-7.

    Article  CAS  PubMed  Google Scholar 

  25. Chin, W. Y., Choi, E. P., Chan, K. T., & Wong, C. K. (2015). The psychometric properties of the center for epidemiologic studies depression scale in Chinese primary care patients: factor structure, construct validity, reliability, sensitivity and responsiveness. PLoS ONE, 10(8), e0135131. https://doi.org/10.1371/journal.pone.0135131.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Vilagut, G., Forero, C. G., Barbaglia, G., & Alonso, J. (2016). Screening for depression in the general population with the center for epidemiologic studies depression (CES-D): A systematic review with meta-analysis. PLoS ONE, 11(5), e0155431. https://doi.org/10.1371/journal.pone.0155431.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Shapiro, C. M., Auch, C., Reimer, M., Kayumov, L., Heslegrave, R., Huterer, N., et al. (2006). A new approach to the construct of alertness. Journal of Psychosomatic Research, 60(6), 595–603. https://doi.org/10.1016/j.jpsychores.2006.04.012.

    Article  PubMed  Google Scholar 

  28. Terwee, C. B., Bot, S. D., de Boer, M. R., et al. (2007). Quality criteria were proposed for measurement properties of health status questionnaires. Journal of Clinical Epidemiology, 60(1), 34–42. https://doi.org/10.1016/j.jclinepi.2006.03.012.

    Article  PubMed  Google Scholar 

  29. Anastasios, S., Theodoros, A. K., Vasiliki, Y., & Konstantina, P. (2018). Using bifactor EFA, bifactor CFA and exploratory structural equation modeling to validate factor structure of the meaning in life questionnaire, Greek version. Psychology, 9(3), 348–371. https://doi.org/10.4236/psych.2018.93022.

    Article  Google Scholar 

  30. Fong, D. Y., Lam, C. L., Mak, K. K., Lo, W. S., Lai, Y. K., Ho, S. Y., et al. (2010). The Short Form-12 Health Survey was a valid instrument in Chinese adolescents. Journal of Clinical Epidemiology, 63(9), 1020–1029. https://doi.org/10.1016/j.jclinepi.2009.11.011.

    Article  PubMed  Google Scholar 

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

    Article  Google Scholar 

  32. Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016). Applying bifactor statistical indices in the evaluation of psychological measures. Journal of Personality Assessment, 98(3), 223–237. https://doi.org/10.1080/00223891.2015.1089249.

    Article  PubMed  Google Scholar 

  33. Gu, H. L., Wen, Z. L., & Fan, X. T. (2017). Structural validity of the Machiavellian Personality Scale: A bifactor exploratory structural equation modeling approach. Personality and Individual Differences, 105, 116–123. https://doi.org/10.1016/j.paid.2016.09.042.

    Article  Google Scholar 

  34. Rosseel, Y., Oberski, D., Vanbrabant, L., Vanbrabant, L., Savalei, V., Merkle, E., et al.(2012). Package ‘lavaan’. R package version 0.6-3. Retrieved from https://cran.r-project.org/web/packages/lavaan/lavaan.pdf.

  35. Dueber, D. M. (2017). Bifactor Indices Calculator: A Microsoft Excel-based tool to calculate various indices relevant to bifactor CFA models. https://doi.org/10.13023/edp.tool.01. Retrieved from http://sites.education.uky.edu/apslab/resources/.

  36. 2016 Population By-census Office Census and Statistics Department. (2017). 2016 Population By-census-Main Results. Hong Kong, HKSAR: Website of the Census and Statistics Department, 2017. Retrieved from https://www.bycensus2016.gov.hk/data/16bc-main-results.pdf.

  37. Nunnally, J. N. (1978). Psychometric Theory (2nd edn.). New York: McGraw-Hill.

    Google Scholar 

  38. Wilkinson, K. (2012). The Psychometric Properties of the Nonrestorative Sleep Scale and a Prospective Observational Study of the Physiological Correlates of Nonrestorative Sleep. University of Toronto. Retrieved from https://tspace.library.utoronto.ca/bitstream/ 1807/32639/6/Wilkinson_Caitlin_20126_MSc_thesis.pdf.

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Acknowledgements

Miss Tiffany Kwok and Mr Cecil Wong, respectively, conducted the forward and backward translations, and are gratefully acknowledged.

Funding

This study was financially supported by a Seed Funding for Basic Research Grant (201511159061) from The University of Hong Kong.

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Correspondence to D. Y. T. Fong.

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Li, S., Fong, D.Y.T., Wong, J.Y.H. et al. Nonrestorative sleep scale: reliable and valid for the Chinese population. Qual Life Res 28, 1685–1692 (2019). https://doi.org/10.1007/s11136-019-02134-8

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