Differential item functioning of the Beck Anxiety Inventory in a rural, multi-ethnic cohort

Joshua M. Garcia, Matthew W. Gallagher, Sid E. O'Bryant, Luis D. Medina

Research output: Contribution to journalArticlepeer-review

Abstract

Background: 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. Methods: 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. Results: 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. Limitations: These results might not be generalizable to a sample with broader racial representation, more severe cognitive impairment, and higher levels of anxiety. Conclusions: 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.

Original languageEnglish
Pages (from-to)36-42
Number of pages7
JournalJournal of Affective Disorders
Volume293
DOIs
StatePublished - 1 Oct 2021

Keywords

  • Anxiety disorders
  • Bias
  • Ethnic groups
  • Measurement
  • Psychometrics
  • Rural population

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