Background. Yin deficiency (YD) is a pathological condition characterized by emaciation, afternoon fever, dry mouth, and night sweats. The incidence of YD is 23.3%. A 27-item Yin Deficiency Scale (YDS) was developed to estimate the clinical severity of YD. This study aimed to develop three short-form YDS versions to reduce the burden of response time, using three item-reduction approaches: Rasch, equidiscriminatory item-total correlation (EITC), and factor-based analyses. Methods. Two datasets were analyzed from previous studies (169 outpatients from May to June 2009 and 237 healthy college students from January to April 2016). The optimal response category was examined using Rasch analysis. Items with higher item-total correlations were determined using the EITC. Using a factor-based approach, the items were reduced, while maintaining the original YDS construct. Reliability was estimated using the person separation index (PSI) and Cronbach’s α values. The predictive accuracy was examined using the area under the curve (AUC). Finally, the relationship between YD and dysfunctional breathing (DB) was examined using factor scores from the YDS and the Korean version of the Nijmegen Questionnaire (KNQ). Results. We developed two 14-item YDS versions using the Rasch and EITC approaches, and a 16-item YDS version using a factor-based approach. Rasch analysis suggested an optimal response category of five points. The PSI of Rasch and Cronbach’s α of the EITC and factor-based versions were 2.19, 0.855, and 0.827. The AUCs of the three short-form YDS were 0.812, 0.811, and 0.818. The sensitivity of the EITC-YDS was 0.632, which was lower than its specificity of 0.875. The fatigue-related scores of the factor-based YDS were fairly correlated with the factor scores of the KNQ estimating the DB (r = 0.349–0.499). Conclusion. The 14-item Rasch- and 16-item factor-based YDS may replace the original YDS during YD’s primary screening, epidemiological surveys, and health checkups.

中文翻译：

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使用三项减少方法制定简式阴虚量表

背景。阴虚（YD）是一种以消瘦、午后发热、口干、盗汗为特征的病理状态。YD的发生率为23.3%。阴虚量表 (YDS) 包含 27 个项目，旨在评估 YD 的临床严重程度。本研究旨在开发三种简短的 YDS 版本，以减少响应时间的负担，使用三种项目减少方法：Rasch、等歧视项目总相关性 (EITC) 和基于因素的分析。方法。分析了之前研究的两个数据集（2009 年 5 月至 6 月的 169 名门诊患者和 2016 年 1 月至 4 月的 237 名健康大学生）。使用 Rasch 分析检查最佳响应类别。使用 EITC 确定项目与总相关性较高的项目。使用基于因素的方法，减少了项目，同时保持了原始的 YDS 构造。使用人员分离指数 (PSI) 和 Cronbach α值来估计可靠性。使用曲线下面积 (AUC) 检查预测准确性。最后，使用 YDS 和韩国版奈梅亨问卷 (KNQ) 的因子评分检查了 YD 和呼吸功能障碍 (DB) 之间的关系。结果。我们使用 Rasch 和 EITC 方法开发了两个 14 项 YDS 版本，以及使用基于因子的方法开发了一个 16 项 YDS 版本。拉希分析建议最佳响应类别为五个点。EITC 和基于因子版本的 Rasch 和 Cronbach α的 PSI分别为 2.19、0.855 和 0.827。三个简短形式 YDS 的 AUC 分别为 0.812、0.811 和 0.818。EITC-YDS 的敏感性为 0.632，低于其特异性 0.875。基于因子的 YDS 的疲劳相关得分与估计 DB 的 KNQ 的因子得分相当相关（r  = 0.349–0.499）。结论。在 YD 的初筛、流行病学调查和健康检查过程中，基于 14 项 Rasch 和 16 项因子的 YDS 可能会取代原来的 YDS。