Skip to main content

Advertisement

Log in

A new computerized adaptive test advancing the measurement of health-related quality of life (HRQoL) in children: the Kids-CAT

  • Published:
Quality of Life Research Aims and scope Submit manuscript

An Erratum to this article was published on 19 March 2015

Abstract

Purpose

Assessing health-related quality of life (HRQoL) via Computerized Adaptive Tests (CAT) provides greater measurement precision coupled with a lower test burden compared to conventional tests. Currently, there are no European pediatric HRQoL CATs available. This manuscript aims at describing the development of a HRQoL CAT for children and adolescents: the Kids-CAT, which was developed based on the established KIDSCREEN-27 HRQoL domain structure.

Methods

The Kids-CAT was developed combining classical test theory and item response theory methods and using large archival data of European KIDSCREEN norm studies (n = 10,577–19,580). Methods were applied in line with the US PROMIS project. Item bank development included the investigation of unidimensionality, local independence, exploration of Differential Item Functioning (DIF), evaluation of Item Response Curves (IRCs), estimation and norming of item parameters as well as first CAT simulations.

Results

The Kids-CAT was successfully built covering five item banks (with 26–46 items each) to measure physical well-being, psychological well-being, parent relations, social support and peers, and school well-being. The Kids-CAT item banks proved excellent psychometric properties: high content validity, unidimensionality, local independence, low DIF, and model conform IRCs. In CAT simulations, seven items were needed to achieve a measurement precision between .8 and .9 (reliability). It has a child-friendly design, is easy accessible online and gives immediate feedback reports of scores.

Conclusions

The Kids-CAT has the potential to advance pediatric HRQoL measurement by making it less burdensome and enhancing the patient–doctor communication.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Clarke, S. A., & Eiser, C. (2004). The measurement of health-related quality of life (QOL) in paediatric clinical trials: A systematic review. Health and Quality of Life Outcomes, 2, 66.

    Article  PubMed Central  PubMed  Google Scholar 

  2. Solans, M., Pane, S., Estrada, M. D., Serra-Sutton, V., Berra, S., Herdman, M., et al. (2008). Health-related quality of life measurement in children and adolescents: A systematic review of generic and disease-specific instruments. Value in Health, 11, 742–764.

    Article  PubMed  Google Scholar 

  3. Detmar, S. B., Muller, M. J., Schornagel, J. H., Wever, L. D., & Aaronson, N. K. (2002). Health-related quality-of-life assessments and patient-physician communication: A randomized controlled trial. JAMA, 288, 3027–3034.

    Article  PubMed  Google Scholar 

  4. Engelen, V., Detmar, S., Koopman, H., Maurice-Stam, H., Caron, H., Hoogerbrugge, P., et al. (2012). Reporting health-related quality of life scores to physicians during routine follow-up visits of pediatric oncology patients: Is it effective? Pediatr. Blood Cancer, 58, 766–774.

    Article  Google Scholar 

  5. Gutteling, J. J., Darlington, A. S., Janssen, H. L., Duivenvoorden, H. J., Busschbach, J. J., & de Man, R. A. (2008). Effectiveness of health-related quality-of-life measurement in clinical practice: A prospective, randomized controlled trial in patients with chronic liver disease and their physicians. Quality of Life Research, 17, 195–205.

    Article  PubMed Central  PubMed  Google Scholar 

  6. de la Osa, N., Ezpeleta, L., Granero, R., & Domenech, J. M. (2009). Brief mental health screening questionnaire for children and adolescents in primary care settings. International Journal of Adolescent Medicine and Health, 21, 91–100.

    PubMed  Google Scholar 

  7. Becker, J., Fliege, H., Kocalevent, R. D., Bjorner, J. B., Rose, M., Walter, O. B., et al. (2008). Functioning and validity of a computerized adaptive test to measure anxiety (A-CAT). Depression and Anxiety, 25, E182–E194.

    Article  PubMed  Google Scholar 

  8. Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S., 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.

    Article  PubMed Central  PubMed  Google Scholar 

  9. Fliege, H., Becker, J., Walter, O. B., Bjorner, J. B., Klapp, B. F., & Rose, M. (2005). Development of a computer-adaptive test for depression (D-CAT). Quality of Life Research, 14, 2277–2291.

    Article  PubMed  Google Scholar 

  10. Gibbons, R. D., Weiss, D. J., Pilkonis, P. A., Frank, E., Moore, T., Kim, J. B., et al. (2012). Development of a computerized adaptive test for depression. Archives of General Psychiatry, 69, 1104–1112.

    Article  PubMed Central  PubMed  Google Scholar 

  11. Rose, M., Bjorner, J. B., Fischer, F., Anatchkova, M., Gandek, B., Klapp, B. F., et al. (2012). Computerized adaptive testing–ready for ambulatory monitoring? Psychosomatic Medicine, 74, 338–348.

    Article  PubMed  Google Scholar 

  12. Turner-Bowker, D. M., Saris-Baglama, R. N., Smith, K. J., DeRosa, M. A., Paulsen, C. A., & Hogue, S. J. (2011). Heuristic evaluation and usability testing of a computerized patient-reported outcomes survey for headache sufferers. Telemedicine Journal and E-Health, 17, 40–45.

    Article  PubMed Central  PubMed  Google Scholar 

  13. Coster, W. J., Haley, S. M., Ni, P., Dumas, H. M., & Fragala-Pinkham, M. A. (2008). Assessing self-care and social function using a computer adaptive testing version of the pediatric evaluation of disability inventory. Archives of Physical Medicine and Rehabilitation, 89, 622–629.

    Article  PubMed Central  PubMed  Google Scholar 

  14. Dumas, H. M., Fragala-Pinkham, M. A., Haley, S. M., Ni, P., Coster, W., Kramer, J. M., et al. (2012). Computer adaptive test performance in children with and without disabilities: Prospective field study of the PEDI-CAT. Disability and Rehabilitation, 34, 393–401.

    Article  PubMed Central  PubMed  Google Scholar 

  15. Dumas, H. M., & Fragala-Pinkham, M. A. (2012). Concurrent validity and reliability of the pediatric evaluation of disability inventory-computer adaptive test mobility domain. Pediatric Physical Therapy, 24, 171–176.

    Article  PubMed  Google Scholar 

  16. Haley, S. M., Raczek, A. E., Coster, W. J., Dumas, H. M., & Fragala-Pinkham, M. A. (2005). Assessing mobility in children using a computer adaptive testing version of the pediatric evaluation of disability inventory. Archives of Physical Medicine and Rehabilitation, 86, 932–939.

    Article  PubMed  Google Scholar 

  17. Haley, S. M., Chafetz, R. S., Tian, F., Montpetit, K., Watson, K., Gorton, G., et al. (2010). Validity and reliability of physical functioning computer-adaptive tests for children with cerebral palsy. Journal of Pediatric Orthopedics, 30, 71–75.

    Article  PubMed  Google Scholar 

  18. Forrest, C. B., Bevans, K. B., Tucker, C., et al. (2012). The patient reported outcome measurement information system (PROMIS®) for children and youth: Application to pediatric psychology. Journal of Pediatric Psychology, 37, 614–621.

    Article  PubMed Central  PubMed  Google Scholar 

  19. Haley, S. M., Ni, P., Ludlow, L. H., & Fragala-Pinkham, M. A. (2006). Measurement precision and efficiency of multidimensional computer adaptive testing of physical functioning using the pediatric evaluation of disability inventory. Archives of Physical Medicine and Rehabilitation, 87, 1223–1229.

    Article  PubMed  Google Scholar 

  20. Haley, S. M., Coster, W. J., Dumas, H. M., Fragala-Pinkham, M. A., Kramer, J., Ni, P., et al. (2011). Accuracy and precision of the pediatric evaluation of disability inventory computer-adaptive tests (PEDI-CAT). Developmental Medicine and Child Neurology, 53, 1100–1106.

    Article  PubMed Central  PubMed  Google Scholar 

  21. 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, S3–S11.

    Article  PubMed Central  PubMed  Google Scholar 

  22. Dumas, H., Fragala-Pinkham, M., Haley, S., Coster, W., Kramer, J., Kao, Y. C., et al. (2010). Item bank development for a revised pediatric evaluation of disability inventory (PEDI). Physical & Occupational Therapy in Pediatrics, 30, 168–184.

    Article  Google Scholar 

  23. Dumas, H. M., Fragala-Pinkham, M. A., & Haley, S. M. (2010). Development of a postacute hospital item bank for the new pediatric evaluation of disability inventory-computer adaptive test. International Journal of Rehabilitation Research, 33, 332–338.

    Article  PubMed  Google Scholar 

  24. Dumas, H. M., Rosen, E. L., Haley, S. M., Fragala-Pinkham, M. A., Ni, P., & O’Brien, J. E. (2010). Measuring physical function in children with airway support: A pilot study using computer adaptive testing. Developmental Neurorehabilitation, 13, 95–102.

    Article  PubMed  Google Scholar 

  25. Haley, S. M., Ni, P., Fragala-Pinkham, M. A., Skrinar, A. M., & Corzo, D. (2005). A computer adaptive testing approach for assessing physical functioning in children and adolescents. Developmental Medicine and Child Neurology, 47, 113–120.

    Article  PubMed  Google Scholar 

  26. Haley, S. M., Fragala-Pinkham, M., & Ni, P. (2006). Sensitivity of a computer adaptive assessment for measuring functional mobility changes in children enrolled in a community fitness programme. Clinical Rehabilitation, 20, 616–622.

    Article  PubMed  Google Scholar 

  27. Haley, S. M., Fragala-Pinkham, M. A., Dumas, H. M., Ni, P., Gorton, G. E., Watson, K., et al. (2009). Evaluation of an item bank for a computerized adaptive test of activity in children with cerebral palsy. Physical Therapy, 89, 589–600.

    Article  PubMed Central  PubMed  Google Scholar 

  28. Haley, S. M., Ni, P., Dumas, H. M., Fragala-Pinkham, M. A., Hambleton, R. K., Montpetit, K., et al. (2009). Measuring global physical health in children with cerebral palsy: Illustration of a multidimensional bi-factor model and computerized adaptive testing. Quality of Life Research, 18, 359–370.

    Article  PubMed Central  PubMed  Google Scholar 

  29. Tucker, C. A., Haley, S. M., Dumas, H. M., Fragala-Pinkham, M. A., Watson, K., Gorton, G. E., et al. (2008). Physical function for children and youth with cerebral palsy: Item bank development for computer adaptive testing. Journal of Pediatric Rehabilitation Medicine, 1, 245–253.

    PubMed  Google Scholar 

  30. Tucker, C. A., Gorton, G. E., Watson, K., Fragala-Pinkham, M. A., Dumas, H. M., Montpetit, K., et al. (2009). Development of a parent-report computer-adaptive test to assess physical functioning in children with cerebral palsy I: Lower-extremity and mobility skills. Developmental Medicine and Child Neurology, 51, 717–724.

    Article  PubMed  Google Scholar 

  31. Tucker, C. A., Montpetit, K., Bilodeau, N., Dumas, H. M., Fragala-Pinkham, M. A., Watson, K., et al. (2009). Development of a parent-report computer-adaptive test to assess physical functioning in children with cerebral palsy II: Upper-extremity skills. Developmental Medicine and Child Neurology, 51, 725–731.

    Article  PubMed  Google Scholar 

  32. Bevans, K. B., Riley, A. W., & Forrest, C. B. (2010). Development of the healthy pathways child-report scales. Quality of Life Research, 19, 1195–1214.

    Article  PubMed Central  PubMed  Google Scholar 

  33. DeWalt, D. A., Thissen, D., Stucky, B. D., Langer, M. M., Morgan, D. E., Irwin, D. E., et al. (2013). PROMIS pediatric peer relationships scale: Development of a peer relationships item bank as part of social health measurement. Health Psychology, 32, 1093–1103.

    Article  PubMed  Google Scholar 

  34. Irwin, D. E., Gross, H. E., Stucky, B. D., Thissen, D., Dewitt, E. M., Lai, J. S., et al. (2012). Development of six PROMIS pediatrics proxy-report item banks. Health and Quality of Life Outcomes, 10, 22.

    Article  PubMed Central  PubMed  Google Scholar 

  35. Kerfeld, C. I., Dudgeon, B. J., Engel, J. M., & Kartin, D. (2013). Development of items that assess physical function in children who use wheelchairs. Pediatric Physical Therapy, 25, 158–166.

    Article  PubMed Central  PubMed  Google Scholar 

  36. Lai, J. S., Stucky, B. D., Thissen, D., Varni, J. W., Dewitt, E. M., Irwin, D. E., et al. (2013). Development and psychometric properties of the PROMIS (R) pediatric fatigue item banks. Quality of Life Research, 22, 2417–2427.

    Article  PubMed  Google Scholar 

  37. Yeatts, K. B., Stucky, B., Thissen, D., Irwin, D., 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.

    Article  PubMed Central  PubMed  Google Scholar 

  38. Ravens-Sieberer, U., Schmidt, S., Gosch, A., Erhart, M., Petersen, C., & Bullinger, M. (2007). Measuring subjective health in children and adolescents: Results of the European KIDSCREEN/DISABKIDS Project. Psychosoc. Med., 4, Doc08.

  39. Ravens-Sieberer, U., Auquier, P., Erhart, M., Gosch, A., Rajmil, L., Bruil, J., et al. (2007). The KIDSCREEN-27 quality of life measure for children and adolescents: Psychometric results from a cross-cultural survey in 13 European countries. Quality of Life Research, 16, 1347–1356.

    Article  PubMed  Google Scholar 

  40. Ravens-Sieberer, U., Erhart, M., Gosch, A., & Wille, N. (2008). Mental health of children and adolescents in 12 European countries-results from the European KIDSCREEN study. Clinical Psychology and Psychotherapy, 15, 154–163.

    Article  PubMed  Google Scholar 

  41. Ravens-Sieberer, U., Herdman, M., Devine, J., Otto, C., Bullinger, M., Rose, M., et al. (2013). The European KIDSCREEN approach to measure quality of life and well-being in children: Development, current application, and future advances. Quality of Life Research, 23, 791–803.

    Article  PubMed Central  PubMed  Google Scholar 

  42. Schmidt, S., Debensason, D., Muhlan, H., Petersen, C., Power, M., Simeoni, M. C., et al. (2006). The DISABKIDS generic quality of life instrument showed cross-cultural validity. Journal of Clinical Epidemiology, 59, 587–598.

    Article  PubMed  Google Scholar 

  43. Schmidt, S., Thyen, U., Chaplin, J., Mueller-Godeffroy, E., & Bullinger, M. (2008). Healthcare needs and healthcare satisfaction from the perspective of parents of children with chronic conditions: The DISABKIDS approach towards instrument development. Child Care, Health and Development, 34, 355–366.

    Article  CAS  PubMed  Google Scholar 

  44. 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 & Outcomes Research, 5, 353–364.

    Article  Google Scholar 

  45. Ware, J. E., Jr., Bjorner, J. B., & Kosinski, M. (1999). Dynamic health assessment: The search for more practical and more precise outcome measures. Quality of Life Newsletter, 11–13.

  46. Ware, J. E., Jr., Bjorner, J. B., & Kosinski, M. (2000). Practical implications of item response theory and computerized adaptive testing: A brief summary of ongoing studies of widely used headache impact scales. Medical Care, 38, II73–II82.

  47. Bjorner, J. B., Kosinski, M., & Ware, J. E, Jr. (2003). Using item response theory to calibrate the Headache Impact Test (HIT™) to the metric of traditional headache scales. Quality of Life Research, 12, 981–1002.

    Article  PubMed  Google Scholar 

  48. Fliege, H., Becker, J., Walter, O. B., Rose, M., Bjorner, J. B., & Klapp, B. F. (2009). Evaluation of a computer-adaptive test for the assessment of depression (D-CAT) in clinical application. International Journal of Methods in Psychiatric Research, 18, 23–36.

    Article  PubMed  Google Scholar 

  49. Kocalevent, R. D., Rose, M., Becker, J., Walter, O. B., Fliege, H., Bjorner, J. B., et al. (2009). An evaluation of patient-reported outcomes found computerized adaptive testing was efficient in assessing stress perception. Journal of Clinical Epidemiology, 62(278–87), 287.

    Google Scholar 

  50. Walter, O. B., Becker, J., Fliege, H., Bjorner, J., Kosinski, M., Walter, M., et al. (2005). Entwicklungsschritte fuer einen computeradaptiven Test zur Erfassug von Angst (A-CAT). [Developmental steps for a computer-adapted test for anxiety]. Diagnostica, 51, 88–100.

    Article  Google Scholar 

  51. Walter, O. B., Becker, J., Bjorner, J. B., Fliege, H., Klapp, B. F., & Rose, M. (2007). Development and evaluation of a computer adaptive test for ‘Anxiety’ (Anxiety-CAT). Quality of Life Research, 16(Suppl 1), 143–155.

    Article  PubMed  Google Scholar 

  52. Forrest, C. B. (2013). Advancing pediatric patient-reported outcome assessment. Value Health, 16, 907–908.

    Article  PubMed  Google Scholar 

  53. Fries, J. F., Bruce, B., & Cella, D. (2005). The promise of PROMIS: Using item response theory to improve assessment of patient-reported outcomes. Clinical and Experimental Rheumatology, 23, S53–S57.

    CAS  PubMed  Google Scholar 

  54. Kurth, B. M., Kamtsiuris, P., Holling, H., Schlaud, M., Dolle, R., Ellert, U., et al. (2008). The challenge of comprehensively mapping children’s health in a nation-wide health survey: Design of the German KiGGS-study. BMC Public Health, 8, 196.

    Article  PubMed Central  PubMed  Google Scholar 

  55. Ravens-Sieberer, U., Erhart, M., Wille, N., & Bullinger, M. (2008). Health-related quality of life in children and adolescents in Germany: Results of the BELLA study. European Child and Adolescent Psychiatry, 17(Suppl 1), 148–156.

    Article  PubMed  Google Scholar 

  56. Currie, C., Nic, G. S., & Godeau, E. (2009). The Health Behaviour in School-aged Children: WHO Collaborative Cross-National (HBSC) study: Origins, concept, history and development 1982–2008. International Journal of Public Health, 54(Suppl 2), 131–139.

    Article  PubMed  Google Scholar 

  57. Ottova, V., Hillebrandt, D., & Ravens-Sieberer, U. (2012). Trends in subjective health and well-being of children and adolescents in Germany: Results of the Health Behaviour in School-aged Children (HBSC) Study 2002 to 2010. Gesundheitswesen, 74(Suppl), S15–S24.

    PubMed  Google Scholar 

  58. Ravens-Sieberer, U. (2009). The contribution of HBSC to international child health research: A milestone in child public health. International Journal of Public Health, 54(Suppl 2), 121–122.

    Article  PubMed  Google Scholar 

  59. Baars, R. M., Atherton, C. I., Koopman, H. M., Bullinger, M., & Power, M. (2005). The European DISABKIDS project: Development of seven condition-specific modules to measure health related quality of life in children and adolescents. Health and Quality of Life Outcomes, 3, 70.

    Article  PubMed Central  PubMed  Google Scholar 

  60. The KIDSCREEN GROUP EUROPE. (2006). The KIDSCREEN questionnaires - Quality of life questionnaires for children and adolescents. Lengerich: Pabst.

    Google Scholar 

  61. Ravens-Sieberer, U., & Bullinger, M. (1998). Assessing health-related quality of life in chronically ill children with the German KINDL: First psychometric and content analytical results. Quality of Life Research, 7, 399–407.

    Article  CAS  PubMed  Google Scholar 

  62. Starfield, B., Riley, A. W., Forrest, C. B., Green, B. F., Robertson, J. A., & Rajmil, L. (2007). Child Health and Illness Profile (CHIP). A comprehensive assessment of health and functioning of children and adolescents. Johns Hopkins Bloomberg School of Public Health.

  63. Grob, A., Lüthi, R., Kaiser, F. G., Flammer, A., Mackinnon, A., & Wearing, A. J. (1991). Berner Fragebogen zum Wohlbefinden Jugendlicher (BFW) (Bernese questionnaire of subjective well-being). Diagnostica, 37, 66–75.

    Google Scholar 

  64. The Child Health Questionnaire (CHQ). (2000). Scoring and Interpretation Manual. Boston: HealthActCHQ Inc.

    Google Scholar 

  65. Topolski, T. D., Edwards, T. C., & Patrick, D. L. (2002). User’s manual and interpretation guide for the youth quality of life (YQOL) instruments. University of Washington, Department of Health Services, Seattle, WA.

  66. Kurt, B. M. (2005). KIGGS. The German health survey for children and adolescents. Robert Koch Institute, Head Department of Epidemiology and Health Reporting.

  67. Stiensmeier-Pelster, J., Schürmann, M., & Duda, K. (1989). Depressions-Inventar für Kinder und Jugendliche (DIKJ). Göttingen: Hogrefe.

    Google Scholar 

  68. Faulstich, M. E., Carey, M. P., Ruggiero, L., Enyart, P., & Gresham, F. (1986). Assessment of depression in childhood and adolescence: An evaluation of the Center for Epidemiological Studies Depression Scale for Children (CES-DC). American Journal of Psychiatry, 143, 1024–1027.

    Article  CAS  PubMed  Google Scholar 

  69. Birmaher, B., Brent, D. A., Chiappetta, L., Bridge, J., Monga, S., & Baugher, M. (1999). Psychometric properties of the screen for childhood anxiety related emotional disorders (SCARED): A replication study. Journal of the American Academy of Child and Adolescent Psychiatry, 38(10), 1230–1236.

    Article  CAS  PubMed  Google Scholar 

  70. Conners, C. K. (2008). Conners scale (3rd ed.). North Tonawanda, NY: Multi-Health Systems Inc.

    Google Scholar 

  71. Achenbach, T. M., & Rescorla, L. (2001). ASEBA school-age forms and profiles. Burlington: Aseba.

    Google Scholar 

  72. Margalit, M. (1995). CSOC: Children sense of coherence manual. Tel Aviv: Tel Aviv University Press.

    Google Scholar 

  73. Jerusalem, M., & Schwarzer, R. (1999). Allgemeine Selbstwirksamkeit. In R. Schwarzer & M. Jerusalem (Eds.), Skalen zur Erfassung von Lehrer-und Schülermerkmalen. Dokumentation der psychometrischen Verfahren im Rahmen der Wissenschaftlichen Begleitung des Modellversuchs Selbstwirksame Schulen. Berlin: Free University of Berlin.

    Google Scholar 

  74. Jerusalem, M. & Mittag, W. (1999). Problemorientiertes, aktives Coping (ACOPE). In R. Schwarzer & M. Jerusalem (Eds.), Skalen zur Erfassung von Lehrer-und Schülermerkmalen. Dokumentation der psychometrischen Verfahren im Rahmen der Wissenschaftlichen Begleitung des Modellversuchs Selbstwirksame Schulen. Berlin: Free University of Berlin.

  75. Bäßler, J., & Schwarzer, R. (1999). Emotionsorientiertes, vermeidendes Coping (ECOPE). In R. Schwarzer & M. Jerusalem (Eds.), Skalen zur Erfassung von Lehrer-und Schülermerkmalen. Dokumentation der psychometrischen Verfahren im Rahmen der Wissenschaftlichen Begleitung des Modellversuchs Selbstwirksame Schulen. Berlin: Free University of Berlin.

  76. Parker, G., Tupling, H., & Brown, L. B. (1979). Parental bonding instrument (PBI). British Journal of Medical Psychology, 52, 1–10.

    Article  Google Scholar 

  77. Schneewind, K. A. (2014). Die Familienklimaskalen (FKS). In M. Cierpa (Ed.), Familiendiagnostik (pp. 232–255). Berlin: Springer.

    Google Scholar 

  78. Meltzer, H. (2003). Development of a common instrument for mental health. In A. Nosikov & C. Gudex (Eds.), EUROHIS: Developing common instruments for health surveys. Amsterdam: IOS Press.

    Google Scholar 

  79. Sherbourne, C. D., & Steward, A. L. (1991). The MOS social support survey. Social Science and Medicine, 32, 705–714.

    Article  CAS  PubMed  Google Scholar 

  80. R Development Core Team. (2008). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.

  81. Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48, 1–36.

    Google Scholar 

  82. Nunnally, J. (1978). Psychometric Theory (2nd ed.). New York: MacGraw-Hill.

    Google Scholar 

  83. Cook, K. F., Kallen, M. A., & Amtmann, D. (2009). Having a fit: Impact of number of items and distribution of data on traditional criteria for assessing IRT’s unidimensionality assumption. Quality of Life Research, 18, 447–460.

    Article  PubMed Central  PubMed  Google Scholar 

  84. 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, S22–S31.

    Article  PubMed  Google Scholar 

  85. Embretson, S. E., & Reise, S. P. (2000). Item response theory for psychologists. London: Lawrence Erlbaum Associates.

    Google Scholar 

  86. Swaminathan, H., & Rogers, J. J. (1990). Detecting differential item functioning using logistic regression procedures. Journal of Educational Measurement, 27, 361–370.

    Article  Google Scholar 

  87. Bjorner, J. B., Kreiner, S., Ware, J. E., Damsgaard, M. T., & Bech, P. (1998). Differential item functioning in the Danish translation of the SF-36. Journal of Clinical Epidemiology, 51, 1189–1202.

    Article  CAS  PubMed  Google Scholar 

  88. Nagelkerke, N. J. D. (1991). Miscellanea. A note on a general definition of the coefficient of determination. Biometrika, 78, 691–692.

    Article  Google Scholar 

  89. Mazza, A., Punzo, A., & McGuire, B. (2012). KernSmoothIRT: AN R package for kernel smoothing in item response theory. Cornell University Library. Ref Type: Electronic Citation.

  90. Muraki, E. (1997). A generalized partial credit model. In W. J. Linden & R. K. Hambleton (Eds.), Handbook of modern item response theory (pp. 153–164). Berlin: Springer.

    Chapter  Google Scholar 

  91. Muraki, E., & Bock, R. D. (1999). PARSCALE: IRT based test scoring and item analysis for graded open-ended exercises and performance tasks. Chicago: Scientific Software Int.

    Google Scholar 

  92. Wainer, H., Dorans, N. J., Flaugher, R., Green, B. F., Mislevy, R. J., Steinberg, L., et al. (2000). Computerized adaptive testing: A primer (2nd ed.). Hillsdale: Lawrence Erlbaum Associates.

    Google Scholar 

  93. Irwin, D. E., Stucky, B., 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.

    Article  PubMed Central  PubMed  Google Scholar 

  94. Irwin, D. E., Stucky, B. D., Langer, M. M., Thissen, D., Dewitt, E. M., Lai, J. S., et al. (2011). PROMIS® pediatric anger scale: An item response theory analysis. Quality of Life Research, 21(4), 697–706.

    Article  PubMed Central  PubMed  Google Scholar 

  95. Bevans, K. B., Gardner, W., Pajer, K., Riley, A. W., & Forrest, C. B. (2013). Qualitative development of the PROMIS(R) pediatric stress response item banks. Journal of Pediatric Psychology, 38, 173–191.

    Article  PubMed Central  PubMed  Google Scholar 

  96. Irwin, D. E., Varni, J. W., Yeatts, K., & DeWalt, D. A. (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.

    Article  PubMed Central  PubMed  Google Scholar 

  97. 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.

    Article  PubMed Central  PubMed  Google Scholar 

  98. Ravens-Sieberer, U., Devine, J., Bevans, K., Riley, A. W., Moon, J., Salsman, J. M., et al. (2014). Subjective well-being measures for children were developed within the PROMIS project: Presentation of first results. Journal of Clinical Epidemiology, 67, 207–218.

    Article  PubMed Central  PubMed  Google Scholar 

  99. DeWitt, E. M., Stucky, B. D., Thissen, D., Irwin, D. E., Langer, M., Varni, J. W., ... & 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.

  100. Kratz, A. L., Slavin, M. D., Mulcahey, M. J., Jette, A. M., Tulsky, D. S., & Haley, S. M. (2013). An examination of the PROMIS® pediatric instruments to assess mobility in children with cerebral palsy. Quality of Life Research, 22(10), 2865–2876.

Download references

Acknowledgments

This work was funded by the German Federal Ministry of Education and Research (BMBF, Grant 0010-01GY1111, PI: Prof. Dr. Ulrike Ravens-Sieberer, MPH, University Medical Center Hamburg-Eppendorf). We would like to thank our advisory board members (Prof. Dr. Christopher Forrest, Prof. Dr. Lena Lämmle, Prof. Dr. Markus Wirtz, and Prof. Dr. Monika Bullinger) for the helpful advice and support. We also thank all children and parents, who participated in the archived studies, which were used for building the Kids-CAT.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to J. Devine.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material (DOC 34 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Devine, J., Otto, C., Rose, M. et al. A new computerized adaptive test advancing the measurement of health-related quality of life (HRQoL) in children: the Kids-CAT. Qual Life Res 24, 871–884 (2015). https://doi.org/10.1007/s11136-014-0812-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-014-0812-7

Keywords

Navigation