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The validation of a computer-adaptive test (CAT) for assessing health-related quality of life in children and adolescents in a clinical sample: study design, methods and first results of the Kids-CAT study

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Abstract

Purpose

Recently, we developed a computer-adaptive test (CAT) for assessing health-related quality of life (HRQoL) in children and adolescents: the Kids-CAT. It measures five generic HRQoL dimensions. The aims of this article were (1) to present the study design and (2) to investigate its psychometric properties in a clinical setting.

Methods

The Kids-CAT study is a longitudinal prospective study with eight measurements over one year at two University Medical Centers in Germany. For validating the Kids-CAT, 270 consecutive 7- to 17-year-old patients with asthma (n = 52), diabetes (n = 182) or juvenile arthritis (n = 36) answered well-established HRQoL instruments (Pediatric Quality of Life Inventory™ (PedsQL), KIDSCREEN-27) and scales measuring related constructs (e.g., social support, self-efficacy). Measurement precision, test–retest reliability, convergent and discriminant validity were investigated.

Results

The mean standard error of measurement ranged between .38 and .49 for the five dimensions, which equals a reliability between .86 and .76, respectively. The Kids-CAT measured most reliably in the lower HRQoL range. Convergent validity was supported by moderate to high correlations of the Kids-CAT dimensions with corresponding PedsQL dimensions ranging between .52 and .72. A lower correlation was found between the social dimensions of both instruments. Discriminant validity was confirmed by lower correlations with non-corresponding subscales of the PedsQL.

Conclusions

The Kids-CAT measures pediatric HRQoL reliably, particularly in lower areas of HRQoL. Its test–retest reliability should be re-investigated in future studies. The validity of the instrument was demonstrated. Overall, results suggest that the Kids-CAT is a promising candidate for detecting psychosocial needs in chronically ill children.

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Notes

  1. The mean completion time refers to the time needed for the five generic core dimensions of the Kids-CAT and the additional chronic–generic dimension.

References

  1. Greenhalgh, J. (2009). The applications of PROs in clinical practice: What are they, do they work, and why? Quality of Life Research, 18(1), 115–123.

    Article  PubMed  Google Scholar 

  2. Valderas, J., Kotzeva, A., Espallargues, M., Guyatt, G., Ferrans, C., Halyard, M. Y., et al. (2008). The impact of measuring patient-reported outcomes in clinical practice: A systematic review of the literature. Quality of Life Research, 17(2), 179–193.

    Article  CAS  PubMed  Google Scholar 

  3. 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(1), 1.

    Article  Google Scholar 

  4. Nelson, E. C., Eftimovska, E., Lind, C., Hager, A., Wasson, J. H., & Lindblad, S. (2015). Patient reported outcome measures in practice. BMJ, 350, g7818.

    Article  PubMed  Google Scholar 

  5. Dawson, J., Doll, H., Fitzpatrick, R., Jenkinson, C., & Carr, A. J. (2010). The routine use of patient reported outcome measures in healthcare settings. BMJ, 340, c186.

    Article  PubMed  Google Scholar 

  6. 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(1), 66.

    Article  PubMed  PubMed Central  Google Scholar 

  7. 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(4), 742–764.

    Article  PubMed  Google Scholar 

  8. Kroenke, K., Monahan, P. O., & Kean, J. (2015). Pragmatic characteristics of patient-reported outcome measures are important for use in clinical practice. Journal of Clinical Epidemiology, 68(9), 1085–1092.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Higginson, I. J., & Carr, A. J. (2001). Using quality of life measures in the clinical setting. BMJ, 322(7297), 1297–1300.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Google Scholar 

  11. 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(5 Suppl 1), S3.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Devine, J., Otto, C., Rose, M., Barthel, D., Fischer, F., Mülhan, H., et al. (2015). A new computerized adaptive test advancing the measurement of health-related quality of life (HRQoL) in children: the Kids-CAT. Quality of Life Research, 24(4), 871–884.

    Article  CAS  PubMed  Google Scholar 

  13. Ravens-Sieberer, U., Herdman, M., Devine, J., Otto, C., Bullinger, M., Rose, M., et al. (2014). 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(3), 791–803.

    Article  PubMed  Google Scholar 

  14. Ravens-Sieberer, U., & The European KIDSCREEN Group. (2006). The KIDSCREEN questionnaires—quality of life questionnaires for children and adolescents—handbook. Lengerich: Pabst Science Publ.

    Google Scholar 

  15. Starfield, B., Riley, A., Forrest, C., Green, B., Robertson, J., & Rajmil, L. (2007). Child health and illness profile (CHIP). A comprehensive assessment of health and functioning of children and adolescents. Baltimore: Johns Hopkins Bloomberg School of Public Health.

    Google Scholar 

  16. Topolski, T., Edwards, T., & Patrick, D. (2002). User’s manual and interpretation guide for the youth quality of life (YQOL) instruments. Seattle: University of Washington.

    Google Scholar 

  17. Devine, J., Otto, C., Rose, M., Barthel, D., Fischer, F., Mühlan, H., et al. (2015). Erratum to: A new computerized adaptive test advancing the measurement of health-related quality of life (HRQoL) in children: the Kids-CAT. Quality of Life Research, 24(9), 2303.

    Article  CAS  PubMed  Google Scholar 

  18. Muehlan, H., Schmidt, S., Devine, J., Walter, O., Fischer, F., Nolte, S., et al. (2014). Assessing disease-related quality of life in children and adolescents with chronic conditions: development and application of a chronic-generic CAT derived from the DISABKIDS framework. Quality of Life Research, 23, 4.

    Google Scholar 

  19. Barthel, D., Fischer, K., Nolte, S., Otto, C., Meyrose, A.-K., Reisinger, S., et al. (2016). Implementation of the Kids-CAT in clinical settings: a newly developed computer-adaptive test to facilitate the assessment of patient-reported outcomes of children and adolescents in clinical practice in Germany. Quality of Life Research, 25, 585–594.

    Article  CAS  PubMed  Google Scholar 

  20. Bock, R. D., & Mislevy, R. J. (1982). Adaptive EAP estimation of ability in a microcomputer environment. Applied Psychological Measurement, 6(4), 431–444.

    Article  Google Scholar 

  21. Varni, J. W., Seid, M., & Kurtin, P. S. (2001). 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(8), 800–812.

    Article  CAS  PubMed  Google Scholar 

  22. Felder-Puig, R., Frey, E., Proksch, K., Varni, J., Gadner, H., & Topf, R. (2004). Validation of the German version of the Pediatric Quality of Life InventoryTM (PedsQLTM) in childhood cancer patients off treatment and children with epilepsy. Quality of Life Research, 13(1), 223–234.

    Article  CAS  PubMed  Google Scholar 

  23. Wille, N., Badia, X., Bonsel, G., Burström, K., Cavrini, G., Devlin, N., et al. (2010). Development of the EQ-5D-Y: A child-friendly version of the EQ-5D. Quality of Life Research, 19(6), 875–886.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Ravens-Sieberer, U., Wille, N., Badia, X., Bonsel, G., Burström, K., Cavrini, G., et al. (2010). Feasibility, reliability, and validity of the EQ-5D-Y: Results from a multinational study. Quality of Life Research, 19(6), 887–897.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Hays, R. D., Bjorner, J. B., Revicki, D. A., Spritzer, K. L., & Cella, D. (2009). Development of physical and mental health summary scores from the patient-reported outcomes measurement information system (PROMIS) global items. Quality of Life Research, 18(7), 873–880.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Bullinger, M. (1995). German translation and psychometric testing of the SF-36 health survey: preliminary results from the IQOLA project. Social Science and Medicine, 41(10), 1359–1366.

    Article  CAS  PubMed  Google Scholar 

  27. Schwarzer, R., & Jerusalem, M. (1995). Generalized Self-Efficacy scale. In J. Weinman, S. Wright & M. Johnston (Ed.), Measures in health psychology: A user’s portfolio. Causal and control beliefs (pp. 35–37). Windsor: NFER-NELSON.

  28. Schwarzer, R., & Jerusalem, M. (1999). Skalen zur erfassung von Lehrer-und Schülermerkmalen. Dokumentation der psychometrischen Verfahren im Rahmen der Wissenschaftlichen Begleitung des Modellversuchs Selbstwirksame schulen. Berlin: Freie Universität Berlin.

    Google Scholar 

  29. Schwarzer, R., Mueller, J., & Greenglass, E. (1999). Assessment of perceived general self-efficacy on the Internet: Data collection in cyberspace. Anxiety Stress and Coping, 12(2), 145–161.

    Article  Google Scholar 

  30. Huebner, E. S. (1991). Initial development of the student’s life satisfaction scale. School Psychology International, 12(3), 231–240.

    Article  Google Scholar 

  31. Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale. Journal of Personality Assessment, 49(1), 71–75.

    Article  CAS  PubMed  Google Scholar 

  32. Huebner, E. S., & Alderman, G. L. (1993). Convergent and discriminant validation of a children’s life satisfaction scale: Its relationship to self-and teacher-reported psychological problems and school functioning. Social Indicators Research, 30(1), 71–82.

    Article  Google Scholar 

  33. Epstein, N. B., Baldwin, L. M., & Bishop, D. S. (1983). The McMaster family assessment device. Journal of Marital and Family Therapy, 9(2), 171–180.

    Article  Google Scholar 

  34. Byles, J., Byrne, C., Boyle, M. H., & Offord, D. R. (1988). Ontario child health study: Reliability and validity of the general functioning subscale of the McMaster Family Assessment Device. Family Process, 27(1), 97–104.

    Article  CAS  PubMed  Google Scholar 

  35. Miller, I. W., Epstein, N. B., Bishop, D. S., & Keitner, G. I. (1985). The McMaster family assessment device: Reliability and validity. Journal of Marital and Family Therapy, 11(4), 345–356.

    Article  Google Scholar 

  36. Donald, C. A., & Ware, J. E. (1984). The measurement of social support. Research in Community and Mental Health, 4, 325–370.

    Google Scholar 

  37. Lampert, T., Kroll, L. E., & Stolzenberg, H. (2013). Messung des sozioökonomischen status in der studie „Gesundheit in Deutschland aktuell“(GEDA). Bundesgesundheitsblatt-Gesundheitsforschung-Gesundheitsschutz, 56(1), 131–143.

    Article  CAS  PubMed  Google Scholar 

  38. Lampert, P. D. T., Müters, S., Stolzenberg, H., Kroll, L. E., & Group, K. S. (2014). Messung des sozioökonomischen status in der KiGGS-studie. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz, 57(7), 762–770.

    Article  PubMed  Google Scholar 

  39. Winkler, J., & Stolzenberg, H. (1999). Der Sozialschichtindex im Bundes-Gesundheitssurvey. Gesundheitswesen, 61(2), S178–S183.

    PubMed  Google Scholar 

  40. Brauns, H., Scherer, S., & Steinmann, S. (2003). The CASMIN educational classification in international comparative research. In Hoffmeyer-Zlotnik J.H.P., & Wolf, C. (Eds.) Advances in cross-national comparison (pp. 221–244). New York: Springer.

  41. Ganzeboom, H. B., De Graaf, P. M., & Treiman, D. J. (1992). A standard international socio-economic index of occupational status. Social Science Research, 21(1), 1–56.

    Article  Google Scholar 

  42. Schenk, L., Bau, A.-M., Borde, T., Butler, J., Lampert, T., Neuhauser, H., et al. (2006). Mindestindikatorensatz zur erfassung des migrationsstatus. Bundesgesundheitsblatt-Gesundheitsforschung-Gesundheitsschutz, 49(9), 853–860.

    Article  CAS  PubMed  Google Scholar 

  43. Shrout, P. E., & Fleiss, J. L. (1979). Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin, 86(2), 420.

    Article  CAS  PubMed  Google Scholar 

  44. Cicchetti, D. V. (1994). Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychological Assessment, 6(4), 284.

    Article  Google Scholar 

  45. Fayers, P., & Machin, D. (2013). Quality of life: the assessment, analysis and interpretation of patient-reported outcomes. Chichester: Wiley.

    Google Scholar 

  46. Nunnally, J. C., & Bernstein, I. (1994). The assessment of reliability. Psychometric Theory, 3(1), 248–292.

    Google Scholar 

  47. Hinkle, D. E., Wiersma, W., & Jurs, S. G. (2003). Applied statistics for the behavioral sciences. Belmont: Wadsworth Publishing.

    Google Scholar 

  48. Maier, A., Holm, T., Wicks, P., Steinfurth, L., Linke, P., Münch, C., et al. (2012). Online assessment of ALS functional rating scale compares well to in-clinic evaluation: A prospective trial. Amyotrophic Lateral Sclerosis, 13(2), 210–216.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank all children, adolescents and their parents, who participated in the Kids-CAT study. We are grateful to the highly motivated study nurses Anja Bünte and Andrea Knaak and all pediatricians who contributed to the Kids-CAT project. We thank all student assistants and interns for their contributions to data entry and management. We thank the Federal Ministry of Education and Research for funding this research project. The Kids-CAT Study Group comprises: A. Bünte (Department of Pediatrics, University Medical Center Schleswig-Holstein, Campus Kiel, Arnold-Heller-Straße 3, House 9, 24105 Kiel, Germany), K. Gulau (Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, Research Unit Child Public Health, Center for Psychosocial Medicine, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany), A. Knaak (Hospital for Pediatrics and Adolescent Medicine, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany), H. Muehlan (Department Health & Prevention, Ernst-Moritz-Arndt University; Robert-Blum-Straße 13, 17487 Greifswald, Germany), S. Schmidt (Department Health & Prevention, Ernst-Moritz-Arndt University; Robert-Blum-Straße 13, 17487 Greifswald, Germany) and S. v. Sengbusch (Hospital for Pediatrics and Adolescent Medicine, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany).

Funding

This study was funded by the German Federal Ministry of Education and Research (grant number 0010-01GY1111).

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Correspondence to U. Ravens-Sieberer.

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Conflict of interest

D. Barthel, C. Otto, S. Nolte, A.-K. Meyrose, F. Fischer J. Devine, O. Walter, A. Mierke, K. I. Fischer, U. Thyen, M. Klein, T. Ankermann, M. Rose, U. Ravens-Sieberer, A. Bünte, K. Gulau, A. Knaak, H. Muehlan, S. Schmidt and S. v. Sengbusch declare that they have no conflict of interest.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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Barthel, D., Otto, C., Nolte, S. et al. The validation of a computer-adaptive test (CAT) for assessing health-related quality of life in children and adolescents in a clinical sample: study design, methods and first results of the Kids-CAT study. Qual Life Res 26, 1105–1117 (2017). https://doi.org/10.1007/s11136-016-1437-9

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