Cross-cultural application of the Korean version of the EORTC QLQ-ELD14 questionnaire for elderly patients with cancer

Ae Jin Goo, Dong Wook Shin,Hyung Kook Yang, Jong-Hyock Park,So-Young Kim, Joo Yeon Shin,Young Ae Kim, Changhoon Kim,Nam-Soo Hong, Young Joo Min,Keeho Park

Journal of Geriatric Oncology(2017)

引用 11|浏览42
暂无评分
摘要
OBJECTIVES:The European Organization for Research and Treatment of Cancer (EORTC) QLQ-ELD14 is a validated tool that measures Health-related Quality-of-life (HRQOL) for elderly patients with cancer. This study was conducted to evaluate the psychometric properties of the Korean version of the EORTC QLQ-ELD14 to determine if this tool can be used to evaluate HRQOL for older Korean patients with cancer. MATERIALS AND METHODS:We recruited 439 elderly patients with cancer aged ≥60years from 11 cancer centers and completed the EORTC QLQ-ELD14 questionnaires. The reliability and validity of the EORTC QLQ-ELD14 questionnaire were assessed via Cronbach alpha, multitrait scaling analyses, correlation analyses with the EORTC QLQ-C30, and known-group comparisons. Known-group comparisons were conducted by dividing the patients into groups based on the cancer stage, depression level, and loss of mobility. RESULTS:The scale structure of the Korean version of the EORTC QLQ-ELD14 was consistent with the originally hypothesized scale structure. Cronbach alpha coefficients ranged 0.65-0.88. Multitrait scaling analysis showed good item convergent and discriminant validity. Low scaling errors (3.1%) were observed. Divergent validity was demonstrated by no strong correlation with the EORTC QLQ C30. The clinical validity of the Korean version of the EORTC QLQ-ELD14 was demonstrated by its ability to discriminate among patient subgroups categorized by AJCC stage, depression level, and loss of mobility. CONCLUSION:Our findings indicate that the Korean version of the EORTC QLQ-ELD14 questionnaire is reliable and valid for measuring QOL of older Korean patients with cancer.
更多
查看译文
关键词
Validation,Korean,Elderly,Cancer,Oncology,EORTC-QLQ-ELD14
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