Suppr超能文献

耳鸣障碍量表韩文版的拉施分析

Rasch Analysis of the Korean Version of the Tinnitus Handicap Inventory.

作者信息

Kim Ga-Young, Cho Young Sang, An Ji Hyun, Kim Jung-Wan, Moon Il Joon

机构信息

Hearing Research Laboratory, Samsung Medical Center, Seoul 06351, Republic of Korea.

Medical Research Institute, Sungkyunkwan University School of Medicine, Suwon 16419, Republic of Korea.

出版信息

J Clin Med. 2023 Sep 5;12(18):5785. doi: 10.3390/jcm12185785.

Abstract

Tinnitus is the perception of abnormal sounds in the ears or head without external auditory stimulation. While classical test theory is often used in tinnitus questionnaire development, it has limitations in assessing item characteristics. Item response theory (IRT) offers more precise individual ability estimations and identifies key and less important items, making it superior for reliable measurement tools. This study investigated the suitability of the Korean version of the Tinnitus Handicap Inventory (K-THI) as a patient-reported outcome measure (PROM) for clinical trials. Using Rasch analysis based on IRT, we evaluated K-THI's measurement of tinnitus-related disability in 545 patients (40.4% men, 59.6% women). Five items (2, 7, 8, 19, and 24) did not fit the Rasch model, yet a unidimensional scale and good fit for person and item data emerged (person: 0.89; item: 0.98). The three-point rating scale in K-THI proved suitable. IRT allowed precise evaluation of K-THI's properties, vital for reliable PROMs in patient-centered care. Our findings highlight IRT's role in questionnaire development, contributing to the advancement of PROMs.

摘要

耳鸣是指在没有外部听觉刺激的情况下,耳朵或头部感觉到异常声音。虽然经典测试理论常用于耳鸣问卷的开发,但在评估项目特征方面存在局限性。项目反应理论(IRT)能提供更精确的个体能力估计,并识别关键项目和不太重要的项目,使其在开发可靠的测量工具方面更具优势。本研究调查了韩国版耳鸣障碍量表(K-THI)作为临床试验中患者报告结局指标(PROM)的适用性。基于IRT使用拉施分析,我们评估了K-THI对545例患者(男性占40.4%,女性占59.6%)耳鸣相关残疾的测量情况。有5个项目(第2、7、8、19和24项)不符合拉施模型,但仍呈现出一个单维量表,且人与项目数据拟合良好(人:0.89;项目:0.98)。K-THI中的三点量表被证明是合适的。IRT能够精确评估K-THI的属性,这对于以患者为中心的护理中可靠的PROM至关重要。我们的研究结果突出了IRT在问卷开发中的作用,有助于推动PROM的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a06/10531739/bde42dfad178/jcm-12-05785-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验