Quality of Life Research

, Volume 21, Issue 7, pp 1223–1240 | Cite as

PROMIS® Parent Proxy Report Scales: an item response theory analysis of the parent proxy report item banks

  • James W. VarniEmail author
  • David Thissen
  • Brian D. Stucky
  • Yang Liu
  • Hally Gorder
  • Debra E. Irwin
  • Esi Morgan DeWitt
  • Jin-Shei Lai
  • Dagmar Amtmann
  • Darren A. DeWalt



The objective of the present study is to describe the item response theory (IRT) analysis of the National Institutes of Health (NIH) Patient Reported Outcomes Measurement Information System (PROMIS®) pediatric parent proxy-report item banks and the measurement properties of the new PROMIS® Parent Proxy Report Scales for ages 8–17 years.


Parent proxy-report items were written to parallel the pediatric self-report items. Test forms containing the items were completed by 1,548 parent–child pairs. CCFA and IRT analyses of scale dimensionality and item local dependence, and IRT analyses of differential item functioning were conducted.


Parent proxy-report item banks were developed and IRT parameters are provided. The recommended unidimensional short forms for the PROMIS® Parent Proxy Report Scales are item sets that are subsets of the pediatric self-report short forms, setting aside items for which parent responses exhibit local dependence. Parent proxy-report demonstrated moderate to low agreement with pediatric self-report.


The study provides initial calibrations of the PROMIS® parent proxy-report item banks and the creation of the PROMIS® Parent Proxy-Report Scales. It is anticipated that these new scales will have application for pediatric populations in which pediatric self-report is not feasible.


PROMIS® Parent proxy report Item response theory 



Patient Reported Outcomes Measurement Information System


Food and drug administration


Health-related quality of life


National Institute of Health



This work was funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U01AR052181. Information on the Patient-Reported Outcomes Measurement Information System (PROMIS®) can be found at and


  1. 1.
    Ader, D. N. (2007). Developing the patient-reported outcomes measurement information system (PROMIS). Medical Care, 45(Suppl 1), S1–S2.CrossRefGoogle Scholar
  2. 2.
    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-report outcomes measurement information system (PROMIS). Medical Care, 45(Suppl 1), S22–S31.PubMedCrossRefGoogle Scholar
  3. 3.
    Cella, D., Yount, S., Rothrock, N., Gershon, R., Cook, K., Reeve, B., et al. (2007). The patient-reported outcomes measurement information system (PROMIS): Progress of an NIH roadmap cooperative group during its first two years. Medical Care, 45(Suppl 1), S3–S11.PubMedCrossRefGoogle Scholar
  4. 4.
    Irwin, D. E., Stucky, B. D., Thissen, D., DeWitt, E. M., Lai, J. S., Yeatts, K., et al. (2010). Sampling plan and patient characteristics of the PROMIS pediatrics large-scale survey. Quality of Life Research, 19, 585–594.PubMedCrossRefGoogle Scholar
  5. 5.
    Irwin, D. E., Stucky, B. D., Langer, M. M., Thissen, D., DeWitt, E. M., Lai, J. S., et al. (2010). An item response analysis of the pediatric PROMIS anxiety and depressive symptoms scales. Quality of Life Research, 19, 595–607.PubMedCrossRefGoogle Scholar
  6. 6.
    Varni, J. W., Stucky, B. D., Thissen, D., DeWitt, E. M., Irwin, D. E., Lai, J. S., et al. (2010). PROMIS pediatric pain interference scale: An item response theory analysis of the pediatric pain item bank. Journal of Pain, 11, 1109–1119.PubMedCrossRefGoogle Scholar
  7. 7.
    DeWitt, E. M., Stucky, B. D., Thissen, D., Irwin, D. E., Langer, M., Varni, J. W., Lai, J. S., Yeatts, K. B., & DeWalt, D. A. (2011). Construction of the eight-item patient-reported outcomes measurement information system pediatric physical function scales: built using item response theory. Journal of Clinical Epidemiology, 64(7), 794–804.Google Scholar
  8. 8.
    Yeatts, K., Stucky, B. D., Thissen, D., Irwin, D. E., Varni, J. W., DeWitt, E. M., et al. (2010). Construction of the pediatric asthma impact scale (PAIS) for the patient-reported outcomes measurement information system (PROMIS). Journal of Asthma, 47, 295–302.PubMedCrossRefGoogle Scholar
  9. 9.
    Sprangers, M. A. G., & Aaronson, N. K. (1992). The role of health care providers and significant others in evaluating the quality of life of patients with chronic disease: A review. Journal of Clinical Epidemiology, 45, 743–760.PubMedCrossRefGoogle Scholar
  10. 10.
    Achenbach, T. M., McConaughy, S. H., & Howell, C. T. (1987). Child/adolescent behavioral and emotional problems: Implications of cross-informant correlations for situational specificity. Psychological Bulletin, 101, 213–232.PubMedCrossRefGoogle Scholar
  11. 11.
    Varni, J. W., Katz, E. R., Seid, M., Quiggins, D. J. L., Friedman-Bender, A., & Castro, C. M. (1998). The pediatric cancer quality of life inventory (PCQL): I Instrument development, descriptive statistics, and cross-informant variance. Journal of Behavioral Medicine, 21, 179–204.PubMedCrossRefGoogle Scholar
  12. 12.
    Upton, P., Lawford, J., & Eiser, C. (2008). Parent-child agreement across child health-related quality of life instruments: A review of the literature. Quality of Life Research, 17, 895–913.PubMedCrossRefGoogle Scholar
  13. 13.
    Varni, J. W., Limbers, C. A., & Burwinkle, T. M. (2007). Parent proxy-report of their children’s health-related quality of life: An analysis of 13, 878 parents’ reliability and validity across age subgroups using the PedsQL 4.0 Generic Core Scales. Health and Quality of Life Outcomes, 5(2), 1–10.PubMedCrossRefGoogle Scholar
  14. 14.
    Campo, J. V., Comer, D. M., Jansen-McWilliams, L., Gardner, W., & Kelleher, K. J. (2002). Recurrent pain, emotional distress, and health service use in childhood. Journal of Pediatrics, 141, 76–83.PubMedCrossRefGoogle Scholar
  15. 15.
    Janicke, D. M., Finney, J. W., & Riley, A. W. (2001). Children’s health care use: A prospective investigation of factors related to care-seeking. Medical Care, 39, 990–1001.PubMedCrossRefGoogle Scholar
  16. 16.
    Varni, J. W., & Setoguchi, Y. (1992). Screening for behavioral and emotional problems in children and adolescents with congenital or acquired limb deficiencies. American Journal of Diseases of Children, 146, 103–107.PubMedGoogle Scholar
  17. 17.
    Varni, J. W., Burwinkle, T. M., & Lane, M. M. (2005). Health-related quality of life measurement in pediatric clinical practice: An appraisal and precept for future research and application. Health and Quality of Life Outcomes, 3(34), 1–9.Google Scholar
  18. 18.
    Reise, S. P., & Waller, N. G. (2009). Item response theory and clinical measurement. Annual Review of Clinical Psychology, 5, 27–48.PubMedCrossRefGoogle Scholar
  19. 19.
    Embretson, S. E., & Reise, S. P. (2000). Item response theory for psychologists. Mahwah, NJ: Erlbaum.Google Scholar
  20. 20.
    Irwin, D. E., Gross, H. E., Stucky, B. D., Thissen, D., DeWitt, E. M., Lai, J. S., Amtmann, D., Khastou, L., Varni, J. W., & DeWalt, D. A. (2011). Development of the PROMIS® pediatrics proxy-report item banks. Manuscript under review.Google Scholar
  21. 21.
    Muthén, L. K., & Muthén, B. O. (2007). Mplus user’s guide [Computer Software] (5th ed.). Los Angeles, CA: Muthén & Muthén.Google Scholar
  22. 22.
    Reise, S. P., Moore, T. M., & Haviland, M. G. (2010). Bifactor models and rotations: Exploring the extent to which multidimensional data yield univocal scale scores. Journal of Personality Assessment, 92, 544–559.PubMedCrossRefGoogle Scholar
  23. 23.
    Cai, L., du Toit, S. H. C., & Thissen, D. (in press). IRTPRO: Flexible, multidimensional, multiple categorical IRT modeling [Computer software]. Chicago, IL: Scientific Software International.Google Scholar
  24. 24.
    Chen, W. H., & Thissen, D. (1997). Local dependence indexes for item pairs using item response theory. Journal of Educational and Behavioral Statistics, 22, 265–289.Google Scholar
  25. 25.
    Lord, F. M. (1977). A study of item bias using item characteristic curve theory. In Y. H. Portinga (Ed.), Basic problems in cross-cultural psychology (pp. 19–29). Amsterdam: Swets and Zeitlinge.Google Scholar
  26. 26.
    Cai, L. (2008). SEM of another flavour: Two new applications of the supplemented EM algorithm. British Journal of Mathematical and Statistical Psychology, 61, 309–329.PubMedCrossRefGoogle Scholar
  27. 27.
    Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, 57, 289–300.Google Scholar
  28. 28.
    Steinberg, L., & Thissen, D. (2006). Using effect sizes for research reporting: Examples using item response theory to analyze differential item functioning. Psychological Methods, 11, 402–415.PubMedCrossRefGoogle Scholar
  29. 29.
    Orlando, M., & Thissen, D. (2003). Further investigation of the performance of S-X2: An item fit index for use with dichotomous item response theory models. Applied Psychological Measurement, 27, 289–298.CrossRefGoogle Scholar
  30. 30.
    Thissen, D., Nelson, L., Rosa, K., & McLeod, L. D. (2001). Item response theory for items scored in more than two categories. In D. Thissen & H. Wainer (Eds.), Test scoring (pp. 141–186). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  31. 31.
    Eiser, C., & Morse, R. (2001). Can parents rate their child’s health-related quality of life? Results from a systematic review. Quality of Life Research, 10, 347–357.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • James W. Varni
    • 1
    Email author
  • David Thissen
    • 2
  • Brian D. Stucky
    • 3
  • Yang Liu
    • 2
  • Hally Gorder
    • 2
  • Debra E. Irwin
    • 4
  • Esi Morgan DeWitt
    • 5
  • Jin-Shei Lai
    • 6
  • Dagmar Amtmann
    • 7
  • Darren A. DeWalt
    • 8
  1. 1.Department of Pediatrics, College of Medicine, Department of Landscape Architecture and Urban Planning, College of ArchitectureTexas A&M UniversityCollege StationUSA
  2. 2.Department of PsychologyUniversity of North Carolina at Chapel HillChapel HillUSA
  3. 3.RAND CorporationSanta MonicaUSA
  4. 4.Department of EpidemiologyUniversity of North Carolina at Chapel HillChapel HillUSA
  5. 5.Department of Pediatrics, Division of RheumatologyCincinnati Children’s Hospital Medical CenterCincinnatiUSA
  6. 6.Department of Medical Social SciencesNorthwestern University Feinberg School of MedicineChicagoUSA
  7. 7.Department of Rehabilitation MedicineUniversity of WashingtonSeattleUSA
  8. 8.Division of General Medicine and Clinical Epidemiology, Cecil G. Sheps Center for Health Services ResearchUniversity of North Carolina at Chapel HillChapel HillUSA

Personalised recommendations