University of Houston, Department of Psychology, Houston, TX, USA.
University of North Texas Health Science Center, Graduate School of Biomedical Sciences, Fort Worth, TX, USA.
J Affect Disord. 2021 Oct 1;293:36-42. doi: 10.1016/j.jad.2021.06.005. Epub 2021 Jun 12.
Evaluating measurement bias is vital to ensure equivalent assessment across diverse groups. One approach for evaluating test bias, differential item functioning (DIF), assesses item-level bias across specified groups by comparing item-level responses between groups that have the same overall score. Previous DIF studies of the Beck Anxiety Inventory (BAI) have only assessed bias across age, sex, and disease duration in monolingual samples. We expand this literature through DIF analysis of the BAI across age, sex, education, ethnicity, cognitive status, and test language.
BAI data from a sample (n = 527, mean age=61.4 ± 12.7, mean education=10.9 ± 4.3, 69.3% female, 41.9% Hispanic/Latin American) from rural communities in West Texas, USA were analyzed. Item response theory (IRT) / logistic ordinal regression DIF was conducted across dichotomized demographic grouping factors. The Mann-Whitney U test and Hedge's g standardized mean differences were calculated before and after adjusting for the impact of DIF.
Significant DIF was demonstrated in 10/21 items. An adverse impact of DIF was not identified when demographics were assessed individually. Adverse DIF was identified for only one participant (1/527, 0.2%) when all demographics were aggregated.
These results might not be generalizable to a sample with broader racial representation, more severe cognitive impairment, and higher levels of anxiety.
Minimal item-level bias was identified across demographic factors considered. These results support prior evidence that the BAI is valid for assessing anxiety across age and sex while contributing new evidence of its clinical relevance across education, ethnicity, cognitive status, and English/Spanish test language.
评估测量偏差对于确保不同群体之间的评估等效至关重要。一种评估测试偏差的方法是差异项目功能(DIF),通过比较具有相同总分的组之间的项目水平反应来评估指定组的项目水平偏差。以前对贝克焦虑量表(BAI)的 DIF 研究仅在单语样本中评估了年龄、性别和疾病持续时间的偏差。我们通过对 BAI 进行年龄、性别、教育、种族、认知状态和测试语言的 DIF 分析来扩展这一文献。
对来自美国德克萨斯州西部农村社区的样本(n=527,平均年龄=61.4±12.7,平均教育程度=10.9±4.3,69.3%为女性,41.9%为西班牙裔/拉丁裔)的 BAI 数据进行了分析。在二分法人口统计学分组因素上进行了项目反应理论(IRT)/逻辑有序回归 DIF。在调整了 DIF 的影响后,计算了 Mann-Whitney U 检验和 Hedge's g 标准化平均差异。
在 21 个项目中的 10 个项目中显示出了显著的 DIF。当单独评估人口统计学数据时,没有发现 DIF 的不利影响。当汇总所有人口统计学数据时,只有一个参与者(1/527,0.2%)出现了不利的 DIF。
这些结果可能不适用于具有更广泛种族代表性、更严重认知障碍和更高焦虑水平的样本。
在考虑的人口统计学因素中,仅发现了最小的项目水平偏差。这些结果支持了先前的证据,即 BAI 可用于评估年龄和性别范围内的焦虑,同时为其在教育、种族、认知状态和英语/西班牙语测试语言方面的临床相关性提供了新的证据。