A new Computerized Adaptive Test advancing the measurement of Health-Related Quality of Life (HRQoL) in children: The Kids-CAT

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.

Publication
Quality of Life Research, (24), 4, pp. 871 - 884
Matthias Rose
Matthias Rose
Department Head
Felix Fischer
Felix Fischer
Group Leader Psychometrics and Health Outcomes

Psychologist with a weakness for quantitative data analysis

Sandra Nolte
Sandra Nolte
Psychometrics and Health Outcomes

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