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Item bias detection in the Hospital Anxiety and Depression Scale using structural equation modeling: comparison with other item bias detection methods

机译：使用结构方程模型在医院焦虑症和抑郁量表中进行项目偏差检测：与其他项目偏差检测方法的比较

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Purpose Comparison of patient-reported outcomes may be invalidated by the occurrence of item bias, also known as differential item functioning. We show two ways of using structural equation modeling (SEM) to detect item bias: (1) multigroup SEM, which enables the detection of both uniform and nonuniform bias, and (2) multidimensional SEM, which enables the investigation of item bias with respect to several variables simultaneously. Method Gender- and age-related bias in the items of the Hospital Anxiety and Depression Scale (HADS; Zigmond and Snaith in Acta Psychiatr Scand 67:361–370, 1983) from a sample of 1068 patients was investigated using the multigroup SEM approach and the multidimensional SEM approach. Results were compared to the results of the ordinal logistic regression, item response theory, and contingency tables methods reported by Cameron et al. (Qual Life Res 23:2883–2888, 2014). Results Both SEM approaches identified two items with gender-related bias and two items with age-related bias in the Anxiety subscale, and four items with age-related bias in the Depression subscale. Results from the SEM approaches generally agreed with the results of Cameron et al., although the SEM approaches identified more items as biased. Conclusion SEM provides a flexible tool for the investigation of item bias in health-related questionnaires. Multidimensional SEM has practical and statistical advantages over multigroup SEM, and over other item bias detection methods, as it enables item bias detection with respect to multiple variables, of various measurement levels, and with more statistical power, ultimately providing more valid comparisons of patients’ well-being in both research and clinical practice.
机译：目的通过项偏倚（也称为差异项功能）的发生，可能会使患者报告的结局比较无效。我们展示了两种使用结构方程模型（SEM）来检测项目偏差的方法：（1）多组SEM，它可以检测均匀偏差和非均匀偏差，以及（2）多维SEM，它可以研究相对于项目偏差的情况同时添加几个变量方法采用多组SEM方法，从1068名患者的样本中调查了医院焦虑症和抑郁量表（HADS； Zigmond and Snaith in Acta Psychiatr Scand 67：361-370，1983）中与性别和年龄相关的偏见。多维SEM方法。将结果与Cameron等人报道的序数逻辑回归，项目响应理论和列联表方法的结果进行比较。 （Qual Life Res 23：2883–2888，2014）。结果两种SEM方法都在焦虑子量表中确定了两个与性别相关的偏倚项和两个与年龄相关的偏见，而在抑郁子量表中识别了四个与年龄相关的偏倚项。 SEM方法得出的结果通常与Cameron等人的结果一致，尽管SEM方法发现有更多项目存在偏差。结论SEM为调查健康相关问卷中的项目偏倚提供了灵活的工具。多维SEM相对于多组SEM和其他项目偏差检测方法具有实用和统计优势，因为它可以针对多个变量，各种测量水平和更大的统计能力进行项目偏差检测，最终提供了对患者病情的更有效比较研究和临床实践中的幸福感。

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