Quality of Life Research

, Volume 19, Issue 4, pp 595–607 | Cite as

An item response analysis of the pediatric PROMIS anxiety and depressive symptoms scales

  • Debra E. IrwinEmail author
  • Brian Stucky
  • Michelle M. Langer
  • David Thissen
  • Esi Morgan DeWitt
  • Jin-Shei Lai
  • James W. Varni
  • Karin Yeatts
  • Darren A. DeWalt



The Patient-Reported Outcomes Measurement Information System (PROMIS) aims to develop self-reported item banks for clinical research. The PROMIS pediatrics (aged 8–17) project focuses on the development of item banks across several health domains (physical function, pain, fatigue, emotional distress, social role relationships, and asthma symptoms). The psychometric properties of the anxiety and depressive symptom item banks are described.


Participants (n = 1,529) were recruited in public school settings, hospital-based outpatient and subspecialty pediatrics clinics. The anxiety (k = 18) and depressive symptoms (k = 21) items were split between two test administration forms. Hierarchical confirmatory factor-analytic models (CFA) were conducted to evaluate scale dimensionality and local dependence. IRT analyses were then used to finalize item banks and short forms.


CFA results confirmed that anxiety and depressive symptoms are separate constructs and indicative of negative affect. Items with local dependence and DIF were removed resulting in 15 anxiety and 14 depressive symptoms items. The psychometric differences between short forms and simulated computer adaptive tests are presented.


PROMIS pediatric item banks were developed to provide efficient assessment of health-related quality of life domains. This sample provides initial calibrations of anxiety and depressive symptoms item banks and creates PROMIS pediatric instruments, version 1.0.


PROMIS Anxiety Depressive symptoms HRQOL PRO Scale development Surveys Pediatrics 



Patient-reported outcomes measurement information system


Pediatric quality of life inventory™


Health-related quality of life


Patient-reported outcomes


Confirmatory factor analysis


Item response theory


Local dependence


Differential item function


  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.
    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.CrossRefPubMedGoogle Scholar
  3. 3.
  4. 4.
    DeWalt, D., Rothrock, N., Yount, S., & Stone, A. A. (2007). PROMIS cooperative group: Evaluation of item candidates: The PROMIS qualitative item review. Medical Care, 45(Suppl 1), S12–S21.CrossRefPubMedGoogle Scholar
  5. 5.
    Walsh, T. R., Irwin, D. E., Meier, A., Varni, J. W., & DeWalt, D. (2008). The use of focus groups in the development of the PROMIS pediatric item bank. Quality of Life Research, 17, 725–735.CrossRefPubMedGoogle Scholar
  6. 6.
    Irwin, D. E., Varni, J. W., Yeatts, K., & DeWalt, D. (2009). Cognitive interviewing methodology in the development of a pediatric item bank: A patient reported outcomes measurement information system (PROMIS) study. Health and Quality of Life Outcomes, 7(3), 1–10.Google Scholar
  7. 7.
    Matza, L. S., Swensen, A. R., Flood, E. M., Secnik, K., & Leidy, N. K. (2004). Assessment of health-related quality of life in children: A review of conceptual, methodological, and regulatory issues. Value in Health, 7, 79–92.CrossRefPubMedGoogle Scholar
  8. 8.
    Ravens-Sieberer, U., Erhart, M., Wille, N., Wetzel, R., Nickel, J., & Bullinger, M. (2006). Generic health-related quality-of-life assessment in children and adolescents: Methodological considerations. Pharmacoeconomics, 24(12), 1199–1220.CrossRefPubMedGoogle Scholar
  9. 9.
    Irwin, D. E., Stucky, B. D., Thissen, D., Morgan DeWitt, E., Lai, J. S., Yeatts, K., Varni, J. W., & DeWalt, D. A. (2010). Sampling plan and patient characteristics of the PROMIS pediatrics large scale survey. Quality of Life Research manuscript under review.Google Scholar
  10. 10.
    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 items banks: Plans for the patient-reported outcome measurement information system (PROMIS). Medical Care, 45, S22–S31.CrossRefPubMedGoogle Scholar
  11. 11.
    Muthén, B., du Toit, S. H. C., & Spisic, D. (1997). Robust inference using weighted least squared and quadratic estimating equations in latent variable modeling with categorical and continuous outcomes. Los Angeles, CA: Muthén & Muthén, Unpublished technical report.Google Scholar
  12. 12.
    Muthen, L. K., & Muthen, B. O. (2004). Mplus user’s guide (2nd ed.). Los Angeles, CA: Muthen & Muthen (Ed.).Google Scholar
  13. 13.
    Hill, C. D., Edwards, M. C., Thissen, D., Langer, M. M., Wirth, R. J., Burwinkle, T. M., et al. (2007). Practical issues in the application of item response theory: A demonstration using items from the pediatric quality of life inventory™ (PedsQL™) 4.0 generic core scales. Medical Care, 45, S39–S47.CrossRefPubMedGoogle Scholar
  14. 14.
    Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores, Psychometrika Monograph. No. 17.Google Scholar
  15. 15.
    Samejima, F. (1997). Graded response model. In W. J. van der Linden & R. K. Hambleton (Eds.), Handbook of modern item response theory (pp. 85–100). New York: Springer.Google Scholar
  16. 16.
    du Toit, M. (Ed.). (2003). IRT from SSI. Lincolnwood, IL: Scientific Software International.Google Scholar
  17. 17.
    Orlando, M., & Thissen, D. (2000). Likelihood-based item-fit indices for dichotomous item response theory models. Applied Psychological Measurement, 24, 50–64.CrossRefGoogle Scholar
  18. 18.
    Orlando, M., & Thissen, D. (2003). Further examination of the performance of S-X2, an item fit index for dichotomous item response theory models. Applied Psychological Measurement, 27, 289–298.CrossRefGoogle Scholar
  19. 19.
    Bjorner, J. B., Smith, K. J., Edelen, M. O., Stone, C., Thissen, D., & Sun, X. (2007). IRTFIT: A macro for item fit and local dependence tests under IRT models. Lincoln, RI: QualityMetric Incorporated.Google Scholar
  20. 20.
    Thissen, D., Steinberg, L., & Wainer, H. (1993). Detection of differential item functioning using the parameters of item response models. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 67–113). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  21. 21.
    Thissen, D. (2001). IRTLRDIF: Software for the computation of the statistics involved in item response theory likelihood-ratio tests for differential item functioning. Chapel Hill, NC: L. L. Thurstone Psychometric Laboratory, The University of North Carolina at Chapel Hill.Google Scholar
  22. 22.
    Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society B, 57, 289–300.Google Scholar
  23. 23.
    Williams, V. S. L., Jones, L. V., & Tukey, J. W. (1999). Controlling error in multiple comparisons, with examples from state-to-state differences in educational achievement. Journal of Educational and Behavioral Statistics, 24, 42–69.Google Scholar
  24. 24.
    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.CrossRefPubMedGoogle Scholar
  25. 25.
    Kolen, M. J., & Brennan, R. L. (2004). Test equating, scaling, and linking (2nd ed.). New York, NY: Springer.Google Scholar
  26. 26.
    Dorans, N. J. (2007). Linking scores from multiple health outcome instruments. Quality of Life Research, 16(s1), 85–94.CrossRefPubMedGoogle Scholar
  27. 27.
    Joreskog, K. G., & Sorbom, D. (2003). LISREL 8.5. Lincolwood, IL: Scientific Software International, Inc.Google Scholar
  28. 28.
    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
  29. 29.
    Thissen, D., Reeve, B. B., Bjorner, J. B., & Chang, C.-H. (2007). Methodological issues for building item banks and computerized adaptive scales. Quality of Life Research, 16, 109–116.CrossRefPubMedGoogle Scholar
  30. 30.
    Varni, J. W., Seid, M., & Kurtin, P. S. (2001). The PedsQL™ 4.0: Reliability and validity of the pediatric quality of life inventory™ version 4.0 generic core scales in healthy and patient populations. Medical Care, 39, 800–812.CrossRefPubMedGoogle Scholar
  31. 31.
    Chen, W. H., & Thissen, D. (1997). Local dependence indices for item pairs using item response theory. Journal of Educational and Behavioral Statistics, 22, 265–289.Google Scholar
  32. 32.
    Reeve, B. B. (2000). Item- and scale-level analysis of clinical and non-clinical sample responses to the MMPI-2 depression scales employing item response theory. Unpublished doctoral dissertation, University of North Carolina at Chapel Hill.Google Scholar
  33. 33.
    Santor, D. A., Ramsay, J. O., & Zuroff, D. C. (1994). Nonparametric item analyses of the beck depression inventory: Evaluating gender item bias and response option weights. Psychological Assessment, 6, 255–270.CrossRefGoogle Scholar
  34. 34.
    Schaeffer, N. C. (1998). An application of item response theory to the measurement of depression. In C. C. Clogg (Ed.), Sociological methodology (Vol. 18, pp. 271–307). Washington, DC: American Sociological Association.Google Scholar
  35. 35.
    Varni, J. W., Seid, M., & Rode, C. A. (1999). The PedsQLTM: Measurement model for the pediatric quality of life inventoryTM. Medical Care, 37, 126–139.CrossRefPubMedGoogle Scholar
  36. 36.
    Ravens-Sieberer, U., Gosch, A., Rajmil, L., Erhart, M., Bruil, J., Duer, W., et al. (2005). KIDSCREEN-52 quality of life measure for children and adolescents. Expert Review of Pharmacoeconomics and Outcomes Research, 5, 353–364.CrossRefPubMedGoogle Scholar
  37. 37.
    Gibbons, R. D., Weiss, D. J., Kupfer, D. J., Frank, E., Fagiolini, A., Grochocinski, V. J., et al. (2008). Using computerized adaptive testing to reduce the burden of mental health assessment. Psychiatric Services, 59, 361–368.CrossRefPubMedGoogle Scholar
  38. 38.
    Bjorner, J. B., Chang, C. H., Thissen, D., & Reeve, B. B. (2007). Developing tailored instruments: item banking and computerized adaptive assessment. Quality of Life Research, 16, 95–108.CrossRefPubMedGoogle Scholar
  39. 39.
    Shafer, A. B. (2006). Meta-analysis of the factor structures of four depression questionnaires: Beck, CES-D, Hamilton, and Zung. Journal of Clinical Psychology, 62, 123–146.CrossRefPubMedGoogle Scholar
  40. 40.
    Watson, D., Clark, L. A., Weber, K., Assenheimer, J. A., Strauss, M. E., & McCormick, R. A. (1995). Testing a tripartite model: I. Evaluating the convergent and discriminant validity of anxiety and depression symptoms. Journal of Abnormal Psychology, 104, 3–14.CrossRefPubMedGoogle Scholar
  41. 41.
    Watson, D., Clark, L. A., Weber, K., Assenheimer, J. S., Strauss, M. E., & McCormick, R. A. (1995). Testing a tripartite model: II. Exploring the symptom structure of anxiety and depression in student, adult, and patient samples. Journal of Abnormal Psychology, 104, 15–25.CrossRefPubMedGoogle Scholar
  42. 42.
    Clark, L. A., & Watson, D. (1991). Tripartite model of anxiety and depression: Psychometric evidence and taxonomic implications. Journal of Abnormal Psychology, 100, 316–336.CrossRefPubMedGoogle Scholar
  43. 43.
    Chorpita, B. F., Albano, A. M., & Barlow, D. H. (1998). The structure of negative emotions in a clinical sample of children and adolescents. Journal of Abnormal Psychology, 107, 74–85.CrossRefPubMedGoogle Scholar
  44. 44.
    Brown, T. A., Chorpita, B. F., & Barlow, D. H. (1998). Structural relationships among dimensions of the DSM-IV anxiety and mood disorders and dimensions of negative affect, positive affect, and autonomic arousal. Journal of Abnormal Psychology, 107, 179–192.CrossRefPubMedGoogle Scholar
  45. 45.
    Pilkonis, P. A., Reise, S. P., Stover, A. M., Riley, W. T., Cella, D. (in press). Items banks for measuring emotional distress from the patient-reported outcomes measurement information system (PROMIS): Depression, anxiety, and anger. Manuscript in press.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Debra E. Irwin
    • 1
    Email author
  • Brian Stucky
    • 2
  • Michelle M. Langer
    • 3
  • David Thissen
    • 2
  • Esi Morgan DeWitt
    • 4
  • Jin-Shei Lai
    • 5
  • James W. Varni
    • 6
  • Karin Yeatts
    • 1
  • Darren A. DeWalt
    • 7
  1. 1.Department of EpidemiologyUniversity of North Carolina at Chapel HillChapel HillUSA
  2. 2.Department of PsychologyUniversity of North Carolina at Chapel HillChapel HillUSA
  3. 3.National Board of Medical ExaminersPhiladelphiaUSA
  4. 4.Department of PediatricsDuke University Medical CenterDurhamUSA
  5. 5.Department of Medical Social SciencesNorthwestern University Feinberg School of MedicineChicagoUSA
  6. 6.Department of Pediatrics, College of Medicine, Department of Landscape Architecture and Urban Planning, College of ArchitectureTexas A&M UniversityCollege StationUSA
  7. 7.Division of General Medicine and Clinical Epidemiology, Cecil G. Sheps Center for Health Services ResearchUniversity of North Carolina at Chapel HillChapel HillUSA

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