Quality of Life Research

, Volume 22, Issue 7, pp 1819–1830 | Cite as

Evaluation of the Patient-Reported Outcomes Information System (PROMIS®) Spanish-language physical functioning items

  • Sylvia H. Paz
  • Karen L. Spritzer
  • Leo S. Morales
  • Ron D. Hays
Article

Abstract

Purpose

To evaluate the equivalence of the PROMIS® physical functioning item bank by language of administration (English versus Spanish).

Methods

The PROMIS® wave 1 English-language physical functioning bank consists of 124 items, and 114 of these were translated into Spanish.

Analysis

Item frequencies, means and standard deviations, item-scale correlations, and internal consistency reliability were calculated. The IRT assumption of unidimensionality was evaluated by fitting a single-factor confirmatory factor analytic model. IRT threshold and discrimination parameters were estimated using Samejima’s Graded Response Model. DIF by language of administration was evaluated.

Results

Item means ranged from 2.53 (SD = 1.36) to 4.62 (SD = 0.82). Coefficient alpha was 0.99, and item-rest correlations ranged from 0.41 to 0.89. A one-factor model fits the data well (CFI = 0.971, TLI = 0.970, and RMSEA = 0.052). The slope parameters ranged from 0.45 (“Are you able to run 10 miles?”) to 4.50 (“Are you able to put on a shirt or blouse?”). The threshold parameters ranged from −1.92 (“How much do physical health problems now limit your usual physical activities (such as walking or climbing stairs)?”) to 6.06 (“Are you able to run 10 miles?”). Fifty of the 114 items were flagged for DIF based on an R2 of 0.02 or above criterion. The expected total score was higher for Spanish- than English-language respondents.

Conclusions

English- and Spanish-speaking subjects with the same level of underlying physical function responded differently to 50 of 114 items. This study has important implications in the study of physical functioning among diverse populations.

Keywords

PROMIS® item banks IRT Physical function Spanish items 

Supplementary material

11136_2012_292_MOESM1_ESM.doc (222 kb)
Supplementary material 1 (DOC 222 kb)
11136_2012_292_MOESM2_ESM.doc (204 kb)
Supplementary material 2 (DOC 204 kb)
11136_2012_292_MOESM3_ESM.doc (44 kb)
Supplementary material 3 (DOC 44 kb)
11136_2012_292_MOESM4_ESM.doc (173 kb)
Supplementary material 4 (DOC 173 kb)

References

  1. 1.
  2. 2.
    Shorris, E. (1992). Latinos: A biography of the people. New York: W.W. Norton & Co.Google Scholar
  3. 3.
    Morales, L., Kington, R., Valdez, R., et al. (2002). Socioeconomic, cultural, and behavioral factors affecting hispanic health outcomes. Journal of Health Care Poor Underserved, 13(4), 477–503.Google Scholar
  4. 4.
    California State Department of Finance. (2002). Current population survey report: March 2001 data. Sacramento, November 2002.Google Scholar
  5. 5.
    Los Angeles County Department of Health Services. (2000). Data collection and analysis division. Los Angeles: Vital Statistics of Los Angeles County.Google Scholar
  6. 6.
    U.S. Census Bureau: Census 2000 US Demographic profile and population center. Washington, DC 20033 (NP-T4-F) Projections of the total resident population by 5-year age groups, race, and Hispanic origin with special age categories.Google Scholar
  7. 7.
    U.S. Census Bureau: Current population reports (P25-1130) Population projections of the US by age, sex, race, and Hispanic origin.Google Scholar
  8. 8.
  9. 9.
  10. 10.
  11. 11.
  12. 12.
    Rose, M., Bjorner, J. B., Becker, J., et al. (2008). Evaluation of a preliminary physical function item bank supported the expected advantages of the Patient-Reported Outcomes Measurement Information System (PROMIS). Journal of Clinical Epidemiology, 61, 17–33.PubMedCrossRefGoogle Scholar
  13. 13.
    Bruce, B., Fries, J. F., Ambrosini, D., et al. (2009). Better assessment of physical function: Item improvement is neglected but essential. Arthritis Research & Therapy, 11, R191. doi:10.1186/ar2890.CrossRefGoogle Scholar
  14. 14.
    Cella, D., Riley, W., Stone, A., et al. (2010). The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. Journal of Clinical Epidemiology, 63, 1179–1194.PubMedCrossRefGoogle Scholar
  15. 15.
    Teresi, J. A., Ocepek-Welikson, K., Kleinman, M., et al. (2009). Analysis of differential item functioning in the depression item bank from the Patient Reported Outcome Measurement Information System (PROMIS): An item response theory approach. Psychology Science Quarterly, 51(2), 148–180.PubMedGoogle Scholar
  16. 16.
  17. 17.
    Rivers, D. (2006). Sample matching: representative sampling from Internet panels. Palo Alto, CA: Polimetrix, Inc.Google Scholar
  18. 18.
    Liu, H., Cella, D. F., Gershon, R., Shen, J., Morales, L. S., Riley, W., et al. (2010). Representativeness of the PROMIS internet panel. Journal of Clinical Epidemiology, 63(11), 1169–1178.PubMedCrossRefGoogle Scholar
  19. 19.
    Bonomi, A. E., Cella, D. F., Hahn, E. A., Bjordal, K., Sperner-Unterweger, B., Gangeri, L., et al. (1996). Multilingual translation of the Functional Assessment of Cancer Therapy (FACT) quality of life measurement system. Quality of Life Research, 5, 309–320.PubMedCrossRefGoogle Scholar
  20. 20.
    Cella, D., Hernandez, L., Bonomi, A. E., Corona, M., Vaquero, M., Shiomoto, G., et al. (1998). Spanish language translation and initial validation of the functional assessment of cancer therapy quality-of-life instrument. Medical Care, 36, 1407–1418.PubMedCrossRefGoogle Scholar
  21. 21.
    Lent, L., Hahn, E., Eremenco, S., Webster, K., & Cella, D. (1999). Using cross-cultural input to adapt the Functional Assessment of Chronic Illness Therapy (FACIT) scales. Acta Oncologica, 38, 695–702.PubMedCrossRefGoogle Scholar
  22. 22.
  23. 23.
  24. 24.
    MPlus: Muthen & Muthen. www.statmodel.com/.
  25. 25.
    Reeve, B. B., Hays, R. D., Bjorner, J. B., Cook, K. F., Crane, P. K., Teresi, J. A., 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 Suppl 1), 22–31.CrossRefGoogle Scholar
  26. 26.
    Morales, L. S., Flowers, C., Gutierrez, P., et al. (2006). Item and scale differential functioning of the mini-mental state exam assessed using the Differential Item and Test Functioning (DFIT) framework. Medical Care, 44, S143–S151.PubMedCrossRefGoogle Scholar
  27. 27.
    Du Toit, M. (2003). IRT from Scientific Software International. Chicago, IL: SSI, Inc.Google Scholar
  28. 28.
    Choi, S., Gibbons, L., & Crane, P. (2011). Lordif: An R package for detecting differential item functioning using iterative hybrid ordinal logistic regression/item response theory and Monte Carlo simulations. Journal of Statistical Software, 39(8).Google Scholar
  29. 29.
  30. 30.
    Choi, S. W. (2009). Firestar: Computerized adaptive testing simulation program for polytomous item response theory models. Applied Psychological Measurement, 33(8), 644–645.CrossRefGoogle Scholar
  31. 31.
    Eremenco, S., Cella, D., & Arnold, B. (2005). A comprehensive method for the translation and cross-cultural validation of health status questionnaires. Evaluation and the Health Professions, 28(2), 212–232.PubMedCrossRefGoogle Scholar
  32. 32.

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Sylvia H. Paz
    • 1
  • Karen L. Spritzer
    • 1
  • Leo S. Morales
    • 3
    • 4
  • Ron D. Hays
    • 1
    • 2
  1. 1.Division of General Internal Medicine and Health Services Research, Department of MedicineUCLA School of MedicineLos AngelesUSA
  2. 2.RANDSanta MonicaUSA
  3. 3.Group Health Research Institute, Group Health CooperativeSeattleUSA
  4. 4.Department of Health ServicesUniversity of WashingtonSeattleUSA

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