Reliability and validity of Japanese versions of KIDSCREEN-27 and KIDSCREEN-10 questionnaires

Environmental Health and Preventive Medicine(2016)

引用 18|浏览11
暂无评分
摘要
Objective This study aimed to assess the reliability and validity of Japanese versions of the KIDSCREEN-27 (J-KIDSCREEN-27) and KIDSCREEN-10 (J-KIDSCREEN-10) questionnaires, which are shorter versions of the KIDSCREEN-52 (J-KIDSCREEN-52). Methods The present analyses are based on a pre-existing dataset of the J-KIDSCREEN-52 validation study, including 1564 children and adolescents aged 8–18 years and their 1326 parents. All were asked to complete the J-KIDSCREEN and Pediatric Quality of Life Inventory (PedsQL) questionnaires. Test–retest reliability was assessed with Intraclass Correlation Coefficients (ICCs) in a one-way random effects model, and internal consistency reliability was measured using Cronbach’s alpha coefficients. Agreement between child and parent scores was evaluated using ICCs in a two-way mixed effects model. To assess concurrent validity, a sub-sample of 535 parents evaluated their child’s mental health status using the Strengths and Difficulties Questionnaire (SDQ). Results For children, test–retest ICCs were ≥0.60 and Cronbach’s alpha ≥0.70 for every dimension of both instruments. Correlations of corresponding dimensions between the J-KIDSCREEN-27 or -10 and the PedsQL were acceptable. For parents, test–retest ICCs were ≥0.60, Cronbach’s alpha ≥0.70, and ICCs between child and parent scores ≥0.41 in every dimension of both instruments. In multivariate logistic regression models, after adjusting for confounders, lower health-related QOL in every dimension of both instruments, except Physical Well-being, was significantly associated with higher odds ratios for borderline and clinical ranges of the SDQ. Conclusion The child/adolescent and parent/proxy versions of the J-KIDSCREEN-27 and J-KIDSCREEN-10 demonstrated acceptable levels of reliability and validity.
更多
查看译文
关键词
Health-related quality of life, KIDSCREEN, Children, Validity, Mental health
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要