Measuring health-related quality of life among school adolescents across Chinese Human Geography Regions: psychometric validation and norm development of the Mandarin Chinese self-reported KID-SCREEN-10 index.

PURPOSE

The self-reported KIDSCREEN-10 index (KS-10) is widely used to assess health-related quality of life (HRQoL) in children and adolescents, but psychometric evidence for its Mandarin Chinese version remains limited. This study evaluates its psychometric properties, develops a population-based norm, and establishes a norm-referenced scoring algorithm.

METHODS

Data were collected from a two-wave cross-sectional survey across the Chinese Human Geography Regions (June 20-July 11, 2022). The sample included 3290 adolescents (ages 10-18; 51.5% female; 75.8% Han ethnic group) in their junior secondary education stage, obtained through convenience sampling (first wave) and multistage, stratified, cluster sampling (second wave). Psychometric properties were evaluated using the Rasch measurement method, and both a population-based norm and a norm-referenced scoring algorithm were developed and established.

RESULTS

Confirmatory factor analysis confirmed unidimensionality after two modifications. Rasch analysis demonstrated satisfactory psychometric performance, including an appropriate 5-category rating scale and strong goodness-of-fit. Minor local dependence was observed in a few item pairs, indicating slight unidimensionality violations. Both Rasch-generated reliability measures performed well. The person-item map showed acceptable matches and provided insights for further improvements. No substantial uniform differential item functioning was detected across 14 groups.

CONCLUSION

The Mandarin Chinese self-reported KS-10 demonstrates satisfactory psychometric properties and provides a concise measure of adolescent HRQoL. It is a user-friendly instrument suitable for routine school monitoring, large-scale population surveys, and clinical applications. The population-based norm and norm-referenced scoring algorithm support its broader application and promotion, and offer new insights for interpreting HRQoL sum scores.