Quality of Life Research

, Volume 27, Issue 6, pp 1635–1645 | Cite as

Psychometric properties of the Chinese version of resilience scale specific to cancer: an item response theory analysis

  • Zeng Jie Ye
  • Mu Zi Liang
  • Hao Wei Zhang
  • Peng Fei Li
  • Xue Ren Ouyang
  • Yuan Liang Yu
  • Mei Ling Liu
  • Hong Zhong Qiu
Article

Abstract

Objective

Classic theory test has been used to develop and validate the 25-item Resilience Scale Specific to Cancer (RS-SC) in Chinese patients with cancer. This study was designed to provide additional information about the discriminative value of the individual items tested with an item response theory analysis.

Methods

A two-parameter graded response model was performed to examine whether any of the items of the RS-SC exhibited problems with the ordering and steps of thresholds, as well as the ability of items to discriminate patients with different resilience levels using item characteristic curves.

Results

A sample of 214 Chinese patients with cancer diagnosis was analyzed. The established three-dimension structure of the RS-SC was confirmed. Several items showed problematic thresholds or discrimination ability and require further revision.

Conclusions

Some problematic items should be refined and a short-form of RS-SC maybe feasible in clinical settings in order to reduce burden on patients. However, the generalizability of these findings warrants further investigations.

Keywords

Cancer Oncology Resilience RS-SC Psychometrics Item response theory 

Notes

Acknowledgements

The authors acknowledge the valuable information provided by the patients who participated in this study.

Author Contributions

ZJY, MZL, HZQ—conceptualized and designed the study, carried out the initial analyses, supervised data collection, drafted the initial manuscript, and approved the final manuscript as submitted. HWZ, PFL, XRO, MLL, YLY—coordinated data collection, critically reviewed the manuscript, drafted the initial manuscript, and approved the final manuscript as submitted.

Compliance with ethical standards

Conflict of interest

The authors have no conflicts of interest to disclose.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Supplementary material

11136_2018_1835_MOESM1_ESM.pdf (174 kb)
Supplementary material 1 (PDF 173 KB)
11136_2018_1835_MOESM2_ESM.pdf (105 kb)
Supplementary material 2 (PDF 105 KB)

References

  1. 1.
    Blows, E., Bird, L., Seymour, J., & Cox, K. (2012). Liminality as a framework for understanding the experience of cancer survivorship: A literature review. Journal of Advanced Nursing, 68(10), 2155–2164.CrossRefPubMedGoogle Scholar
  2. 2.
    Deshields, T. L., Heiland, M. F., Kracen, A. C., et al. (2016). Resilience in adults with cancer: Development of a conceptual model. Psycho-Oncology, 25(1), 11–18.CrossRefPubMedGoogle Scholar
  3. 3.
    Connor, K. M., & Davidson, J. R. (2003). Development of a new resilience scale: The Connor-Davidson Resilience Scale (CD-RISC). Depress and Anxiety, 18(2), 76–82.CrossRefPubMedGoogle Scholar
  4. 4.
    Chen, E., & Miller, G. E. (2012). “Shift-and-persist” strategies: Why low socioeconomic status isn’t always bad for health. Perspectives on Psychological Science, 7(2), 135–158.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Ye, Z. J., Liu, Q. C., & Liang, M. Z. (2016). The exploratory evaluation of resilience model for breast cancer (RM-BC) among patients with breast cancer diagnosis. Medicine & Philosophy, 12(B), 75–79.Google Scholar
  6. 6.
    Ye, Z. J., Liang, M. Z., Qiu, H. Z., et al. (2016). Effect of a multidiscipline mentor-based program, be resilient to breast cancer (BRBC), on female breast cancer survivors in mainland China-A randomized, controlled, theoretically-derived intervention trial. Breast Cancer Research and Treatment, 158(3), 509–522.CrossRefPubMedGoogle Scholar
  7. 7.
    Ye, Z. J., Qiu, H. Z., Liang, M. Z., et al. (2017). New resilience instrument for patients with cancer. Quality of Life Research.  https://doi.org/10.1007/s11136-017-1736-9.Google Scholar
  8. 8.
    Ye, Z. J., Qiu, H. Z., Liang, M. Z., et al. (2017). Effect of a mentor-based, supportive-expressive program, be resilient to breast cancer, on survival in metastatic breast cancer—A randomized, controlled intervention trial. British Journal of Cancer, 117(10), 1486–1494.CrossRefPubMedGoogle Scholar
  9. 9.
    Lord, F. M. (1980). Applications of item response theory to practical testing problems (vol. 1, p. 274). Hillsdale, NJ: Lawrence Erlbaum Ass.Google Scholar
  10. 10.
    Crocker, L., & Algina, J. (1986). Introduction to classical and modern test theory (p. 527). Orlando, FL: Sea Harbor Drive.Google Scholar
  11. 11.
    Leung, C. M., Ho, S., & Kan, C. S. (1993). Evaluation of the Chinese version of the Hospital Anxiety and Depression Scale: A cross-cultural perspective. International Journal of Psychosomatics, 40, 29–34.PubMedGoogle Scholar
  12. 12.
    Zheng, L. L., Wang, Y. L., & Li, H. C. (2003). The application of Hospital Anxiety and Depression Scale in the general hospitals. Shanghai Archives of Psychiatry Medicine, 5, 264–266.Google Scholar
  13. 13.
    Baker, F. (2001). The basics of item response theory, ERIC clearinghouse on assessment and evaluation. College Park, MD: University of Maryland.Google Scholar
  14. 14.
    Embretson, S., & Reise, S. (2000). Item response theory for psychologists, L. Mahwah, NJ: Erlbaum Associates.Google Scholar
  15. 15.
    Samejima, F. (2005). Graded response model. In Encyclopedia Social Measurement (pp. 145–153). New York: SpringerCrossRefGoogle Scholar
  16. 16.
    Andrich, D., Sheridan, B., & Luo, G. (2000). RUMM2010: A windows interactive program for analysing data with Rasch unidimensional models for measurement. Perth, WA: RUMM Laboratory.Google Scholar
  17. 17.
    Hambleton, R. K., Swaminathan, H., & Rogers, H. J. Fundamentals of item response theory. Newbury Park: Sage.Google Scholar
  18. 18.
    Reeve, B. B., Hays, R. D., Bjorner, J. B., et al. (2007). Psychometric evaluation and calibration of health-related quality of life item banks: Plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Medical Care, 45(5), S22–S31.CrossRefPubMedGoogle Scholar
  19. 19.
    De Ayala, R. J., Kim, S. H., Stapleton, L. M., & Dayton, C. M. (1999). A reconceptualization of differential item functioning. Montreal, Quebec, Canada: Annual Meeting of the American Educational Research Association; April 19–23.Google Scholar
  20. 20.
    Wolfe, E. W., & Smith E. V. Jr. (2007). Instrument development tools and activities for measure validation using Rasch models: Part II-validation activities. Journal of Applied Measurement, 8(2), 204–234.PubMedGoogle Scholar
  21. 21.
    Holland, P. W., & Wainer, H. (2012). Differential item functioning. Abingdon: Routledge.Google Scholar
  22. 22.
    Ye, Z. J., Guan, H. J., Wu, L. H., et al. (2015). The resilience and psychosocial function among mainland Chinese parents of children with cancer: A cross-sectional survey. Cancer Nursing, 38(6), 466–474.CrossRefPubMedGoogle Scholar
  23. 23.
    Scali, J., Gandubert, C., Ritchie, K., Soulier, M., Ancelin, M. L., & Chaudieu, I. (2012). Measuring resilience in adult women using the 10-items Connor-Davidson Resilience Scale (CD-RISC): Role of trauma exposure and anxiety disorders. PLoS ONE, 7(6), e39879.CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Ye, Z. J., Qiu, H. Z., Li, P. F., et al. (2017). Predicting changes in quality of life and emotional distress in Chinese patients with lung, gastric, and colon-rectal cancer diagnoses: The role of psychological resilience. Psycho-Oncology, 26(6), 829–835.CrossRefPubMedGoogle Scholar
  25. 25.
    Gotay, C. C., Ransom, S., & Pagano, I. S. (2007). Quality of life in survivors of multiple primary cancers compared with cancer survivor controls. Cancer, 110(9), 2101–2109.CrossRefPubMedGoogle Scholar
  26. 26.
    Ye, Z. J., Qiu, H. Z., Li, P. F., et al. (2017). Validation and application of the chinese version of the 10-item Connor-Davidson Resilience Scale (CD-RISC-10) among parents of children with cancer diagnosis. European Journal of Oncology Nursing, 27, 36–44.CrossRefPubMedGoogle Scholar
  27. 27.
    Ye, Z. J., Qiu, H. Z., Li, P. F., et al. (2017). Resilience model for parents of children with cancer in mainland China-An exploratory study. European Journal of Oncology Nursing, 27, 9–16.CrossRefPubMedGoogle Scholar
  28. 28.
    Julious, S. A. (2010). Sample sizes for clinical trials. Boca Raton: CRC Press.Google Scholar
  29. 29.
    Sébille, V., Hardouin, J. B., Le Néel, T., et al. (2010). Methodological issues regarding power of classical test theory (CTT) and item response theory (IRT)-based approaches for the comparison of patient-reported outcomes in two groups of patients-a simulation study. BMC Medical Research Methodology, 10, 24.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Draxler, C. (2010). Sample size determination for Rasch model tests. Psychometrika, 75, 708–724.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Zeng Jie Ye
    • 1
  • Mu Zi Liang
    • 1
    • 2
  • Hao Wei Zhang
    • 3
  • Peng Fei Li
    • 1
  • Xue Ren Ouyang
    • 4
  • Yuan Liang Yu
    • 5
  • Mei Ling Liu
    • 6
  • Hong Zhong Qiu
    • 7
  1. 1.Guangzhou University of Chinese MedicineGuangzhouChina
  2. 2.Guangdong Academy of Population DevelopmentGuangzhouChina
  3. 3.Harbin Medical University- DaqingDaqingChina
  4. 4.The First Affiliated HospitalGuangzhou University of Chinese MedicineGuangzhouChina
  5. 5.South China University of TechnologyGuangzhouChina
  6. 6.Sun Yat-sen University Cancer CenterGuangzhouChina
  7. 7.College of Economics and ManagementGuangzhou University of Chinese MedicineGuangzhouChina

Personalised recommendations