Advertisement

Quality of Life Research

, Volume 23, Issue 10, pp 2819–2830 | Cite as

Assessing the invariance of a culturally competent multi-lingual unmet needs survey for immigrant and Australian-born cancer patients: a Rasch analysis

  • J. A. McGrane
  • P. N. Butow
  • M. Sze
  • M. Eisenbruch
  • D. Goldstein
  • M. T. King
Article

Abstract

Purpose

The purpose of this study was to assess the invariance of a culturally competent multi-lingual unmet needs survey.

Methods

A cross-sectional study was conducted among immigrants of Arabic-, Chinese- and Greek-speaking backgrounds, and Anglo-Australian-born controls, recruited through Cancer Registries (n = 591) and oncology clinics (n = 900). The survey included four subscales, with newly developed items addressing unmet need in culturally competent health information and patient support (CCHIPS), and items adapted from existing questionnaires addressing physical and daily living (PDL), sexuality (SEX) and survivorship (SURV) unmet need. The survey was translated into Arabic, Chinese and Greek. Rasch analysis was carried out on the four domains.

Results

Whilst many items were mistargeted to less prevalent areas of unmet need, causing substantial floor effects in person estimates, reliability indices were acceptable. The CCHIPS domain showed differential item functioning (DIF) for cultural background and language, and the PDL domain showed DIF for treatment phase and gender. The results for SEX and SURV domains were limited by floor effects and missing responses. All domains showed adequate fit to the model after DIF was resolved and a small number of items were deleted.

Conclusions

The study highlights the intricacies in designing a culturally competent survey that can be applied to culturally and linguistically diverse groups across different treatment contexts. Overall, the results demonstrate that this survey is somewhat invariant with respect to these factors. Future refinements are suggested to enhance the survey’s cultural competence and general validity.

Keywords

Unmet needs Cancer Immigrants Cultural competence Rasch analysis Differential item functioning 

References

  1. 1.
    Bonevski, B., Sanson-Fisher, R., Girgis, A., Burton, L., Cook, P., et al. (2000). Evaluation of an instrument to assess the needs of patients with cancer. Supportive care review group. Cancer, 88(1), 217–225.PubMedCrossRefGoogle Scholar
  2. 2.
    Au, A., Lam, W. W., Kwong, A., Suen, D., Tsang, J., et al. (2011). Validation of the Chinese version of the short-form Supportive Care Needs Survey Questionnaire (SCNS-SF34-C). Psycho-Oncology, 20(12), 1292–1300.PubMedCrossRefGoogle Scholar
  3. 3.
    Boyes, A., Girgis, A., & Lecathelinais, C. (2009). Brief assessment of adult cancer patients’ perceived needs: Development and validation of the 34-item Supportive Care Needs Survey (SCNS-SF34). Journal of Evaluation in Clinical Practice, 15(4), 602–606.PubMedCrossRefGoogle Scholar
  4. 4.
    Hodgkinson, K., Butow, P., Hunt, G. E., Pendlebury, S., Hobbs, K. M., et al. (2007). The development and evaluation of a measure to assess cancer survivors’ unmet supportive care needs: The CaSUN (Cancer Survivors’ Unmet Needs measure). Psycho-Oncology, 16(9), 796–804.PubMedCrossRefGoogle Scholar
  5. 5.
    Chu, K. C., Miller, B. A., & Springfield, S. A. (2007). Measures of racial/ethnic health disparities in cancer mortality rates and the influence of socioeconomic status. Journal of the National Medical Association, 99(10), 1092–1104.PubMedCentralPubMedGoogle Scholar
  6. 6.
    Colagiuri, B., King, M. T., Butow, P. N., McGrane, J. A., Luckett, T., et al. (2012). A comparison of the FACT-G and the Supportive Care Needs Survey (SCNS) in women with ovarian cancer: Unidimensionality of constructs. Quality of Life Research, 21(5), 887–897.PubMedCrossRefGoogle Scholar
  7. 7.
    Butow, P. N., Sze, M., Duggal-Beri, P., Mikhail, M., Eisenbruch, M., et al. (2011). From inside the bubble: Migrants’ perceptions of communication with the cancer team. Supportive Care in Cancer, 19(2), 281–290.CrossRefGoogle Scholar
  8. 8.
    Goldstein, D., Thewes, B., & Butow, P. (2002). Communicating in a multicultural society. II: Greek community attitudes towards cancer in Australia. Internal Medicine Journal, 32(7), 289–296.PubMedCrossRefGoogle Scholar
  9. 9.
    Moore, R., & Butow, P. (2005). Culture and oncology: Impact of context effects. In D. Speigel (Ed.), Cancer, communication and culture. New York: Kluwer Academic.Google Scholar
  10. 10.
    Ali, N. S., Khalil, H. Z., & Yousef, W. (1993). A comparison of American and Egyptian cancer patients’ attitudes and unmet needs. Cancer Nursing, 16(3), 193–203.PubMedCrossRefGoogle Scholar
  11. 11.
    Guthrie, B. (2005). Bridging health care disparities: Addressing unmet needs of women of color. Journal of Obstetric, Gynecologic, and Neonatal Nursing, 34(3), 385.PubMedCrossRefGoogle Scholar
  12. 12.
    Custers, J. W., Hoijtink, H., van der Net, J., & Helders, P. J. (2000). Cultural differences in functional status measurement: Analyses of person fit according to the Rasch model. Quality of Life Research, 9(5), 571–578.PubMedCrossRefGoogle Scholar
  13. 13.
    Tennant, A., Penta, M., Tesio, L., Grimby, G., Thonnard, J.-L., et al. (2004). Assessing and adjusting for cross-cultural validity of impairment and activity limitation scales through differential item functioning within the framework of the Rasch model: The PRO-ESOR project. Medical Care, 42(1), I37–I48.PubMedGoogle Scholar
  14. 14.
    Pallant, J. F., & Tennant, A. (2007). An introduction to the Rasch measurement model: An example using the Hospital Anxiety and Depression Scale (HADS). British Journal of Clinical Psychology, 46, 1–18.PubMedCrossRefGoogle Scholar
  15. 15.
    Andrich, D. (1988). Rasch models for measurement. Beverly Hills: Sage Publications Inc.Google Scholar
  16. 16.
    Pagano, I. S., & Gotay, C. C. (2005). Ethnic differential item functioning in the assessment of quality of life in cancer patients. Health and Quality of Life Outcomes, 3(1), 60.PubMedCentralPubMedCrossRefGoogle Scholar
  17. 17.
    Teresi, J. A., & Fleishman, J. A. (2007). Differential item functioning and health assessment. Quality of Life Research, 16(1), 33–42.PubMedCrossRefGoogle Scholar
  18. 18.
    Tesio, L., & Tennant, A. (2005). Psychometric properties of the mini-mental state examination in patients with acquired brain injury in Turkey. Journal of Rehabilitation Medicine, 37, 306–311.PubMedCrossRefGoogle Scholar
  19. 19.
    Geyh, S., Fellinghauer, B., Kirchberger, I., & Post, M. (2010). Cross-cultural validity of four quality of life scales in persons with spinal cord injury. Health and Quality of Life Outcomes, 8, 94.PubMedCentralPubMedCrossRefGoogle Scholar
  20. 20.
    Choi, Y., Mericle, A., & Harachi, T. W. (2006). Using Rasch analysis to test the cross-cultural item equivalence of the Harvard Trauma Questionnaire and the Hopkins Symptom Checklist across Vietnamese and Cambodian immigrant mothers. Journal of Applied Measurement, 7(1), 16.PubMedCentralPubMedGoogle Scholar
  21. 21.
    Baranik, L. E., Meade, A. W., Lakey, C. E., Lance, C. E., Hu, C., et al. (2008). Examining the differential item functioning of the Rosenberg Self-Esteem Scale across eight countries. Journal of Applied Social Psychology, 38(7), 1867–1904.CrossRefGoogle Scholar
  22. 22.
    Zumbo, B. D. (2003). Does item-level DIF manifest itself in scale-level analyses? Implications for translating language tests. Language Testing, 20(2), 136–147.CrossRefGoogle Scholar
  23. 23.
    Salzberger, T., Sinkovics, R. R., & Schlegelmilch, B. B. (1999). Data equivalence in cross-cultural research: A comparison of classical test theory and latent trait theory based approaches. Australasian Marketing Journal, 7(2), 23–38.CrossRefGoogle Scholar
  24. 24.
    Butow, P. N., Bell, M., Aldridge, L. J., Sze, M., Eisenbruch, M., et al. (2013). Unmet needs in immigrant cancer survivors: A cross-sectional population based study. Supportive Care in Cancer, 21, 2509–2520.PubMedCrossRefGoogle Scholar
  25. 25.
    Bell, M. L., Butow, P. N., and Goldstein, D. (2013). Informatively missing quality of life and unmet needs sex data for immigrant and Anglo-Australian cancer patients and survivors. Quality of Life Research, 22(10), 1–4.Google Scholar
  26. 26.
    Schuman, H. (1966). The random probe: A technique for evaluating the validity of closed questions. American Sociological Review, 31(2), 218–222.Google Scholar
  27. 27.
    Andrich, D., Sheridan, B., & Luo, G. (2010). Rasch models for measurement: RUMM2030. Perth, Western Australia: RUMM Laboratory.Google Scholar
  28. 28.
    Chen, W.-H., Lenderking, W., Jin, Y., Wyrwich, K., Gelhorn, H., et al. (2014). Is Rasch model analysis applicable in small sample size pilot studies for assessing item characteristics? An example using PROMIS pain behavior item bank data. Quality of Life Research, 23(2), 485–493.PubMedCrossRefGoogle Scholar
  29. 29.
    Linacre, M. (1994). Sample size and item calibration stability. Rasch Measurement Transactions, 7, 328.Google Scholar
  30. 30.
    Marais, I., & Andrich, D. (2008). Effects of varying magnitude and patterns of response dependence in the unidimensional Rasch model. Journal of Applied Measurement, 9(2), 105–124.PubMedGoogle Scholar
  31. 31.
    Andrich, D., & Hagquist, C. (2012). Real and artificial differential item functioning. Journal of Educational and Behavioral Statistics, 37(3), 387–416.CrossRefGoogle Scholar
  32. 32.
    Marais, I., & Andrich, D. (2008). Formalising dimension and response violations of local independence in the unidimensional Rasch model. Journal of Applied Measurement, 9(3), 200–215.PubMedGoogle Scholar
  33. 33.
    Scott, N. W., Fayers, P. M., Aaronson, N. K., Bottomley, A., Graeff, A., et al. (2007). The use of differential item functioning analyses to identify cultural differences in responses to the EORTC QLQ-C30. Quality of Life Research, 16(1), 115–129.PubMedCrossRefGoogle Scholar
  34. 34.
    Andrich, D. (2005). The Rasch model explained. In S. Alagumalai, D. Durtis, & N. Hungi (Eds.), Applied Rasch measurement: A book of exemplars (pp. 308–328). Dordrecht, Netherlands: Springer.Google Scholar
  35. 35.
    McKenna, S. P., Wilburn, J., Thorsen, H., & Brodersen, J. (2012). Adapting patient-reported outcome measures for use in new languages and cultures. In K. B. Christensen, S. Kreiner, & M. Mesbah (Eds.), Rasch models in health (pp. 303–315). London, UK: Wiley.Google Scholar
  36. 36.
    Petersen, M. A., Groenvold, M., Bjorner, J. B., Aaronson, N., Conroy, T., et al. (2003). Use of differential item functioning analysis to assess the equivalence of translations of a questionnaire. Quality of Life Research, 12(4), 373–385.PubMedCrossRefGoogle Scholar
  37. 37.
    Gershon, R., Cella, D., Dineen, K., Rosenbloom, S., Peterman, A., et al. (2003). Item response theory and health-related quality of life in cancer. Expert Review of Pharmacoeconomics and Outcomes Research, 3(6), 783–791.PubMedCrossRefGoogle Scholar
  38. 38.
    ABS, Australian Social Trends (4102.0). A.B.o. Statistics, Editor 2010, AGPS: Canberra.Google Scholar
  39. 39.
    Hobart, J. C. (2003). Rating scales for neurologists. Journal of Neurology, Neurosurgery and Psychiatry, 74, 22–26.CrossRefGoogle Scholar
  40. 40.
    Flynn, K. E., Jeffery, D. D., Keefe, F. J., Porter, L. S., Shelby, R. A., et al. (2011). Sexual functioning along the cancer continuum: Focus group results from the patient-reported outcomes measurement information system (PROMIS®). Psycho-Oncology, 20(4), 378–386.PubMedCentralPubMedCrossRefGoogle Scholar
  41. 41.
    Borsboom, D. (2006). When does measurement invariance matter? Commentary. Medical Care, 44(11), S176–S181.PubMedCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • J. A. McGrane
    • 1
  • P. N. Butow
    • 2
  • M. Sze
    • 2
  • M. Eisenbruch
    • 3
  • D. Goldstein
    • 4
  • M. T. King
    • 2
  1. 1.Pearson Psychometric Laboratory, Faculty of EducationUniversity of Western AustraliaCrawley, PerthAustralia
  2. 2.Psycho-Oncology Co-operative Research Group (PoCoG)University of SydneySydneyAustralia
  3. 3.School of Psychology and PsychiatryMonash UniversityMelbourneAustralia
  4. 4.Faculty of Medicine, Prince of Wales Clinical SchoolUniversity of New South WalesSydneyAustralia

Personalised recommendations