Literature DB >> 34166907

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

Joshua M Garcia1, Matthew W Gallagher1, Sid E O'Bryant2, Luis D Medina3.   

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.
Copyright © 2021. Published by Elsevier B.V.

Entities:  

Keywords:  Anxiety disorders; Bias; Ethnic groups; Measurement; Psychometrics; Rural population

Mesh:

Year:  2021        PMID: 34166907      PMCID: PMC8349838          DOI: 10.1016/j.jad.2021.06.005

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   6.533


  33 in total

1.  Item response theory and health outcomes measurement in the 21st century.

Authors:  R D Hays; L S Morales; S P Reise
Journal:  Med Care       Date:  2000-09       Impact factor: 2.983

2.  Differential item functioning and health assessment.

Authors:  Jeanne A Teresi; John A Fleishman
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Review 3.  Late-life anxiety and cognitive impairment: a review.

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4.  Scoring and modeling psychological measures in the presence of multidimensionality.

Authors:  Steven P Reise; Wes E Bonifay; Mark G Haviland
Journal:  J Pers Assess       Date:  2012-10-02

5.  Demographic characteristics do not decrease the utility of depressive symptoms assessments: examining the practical impact of item bias in four heterogeneous samples of older adults.

Authors:  Natalia O Dmitrieva; Denise Fyffe; Shubhabrata Mukherjee; Robert Fieo; Laura B Zahodne; Jamie Hamilton; Guy G Potter; Jennifer J Manly; Heather R Romero; Dan Mungas; Laura E Gibbons
Journal:  Int J Geriatr Psychiatry       Date:  2014-04-15       Impact factor: 3.485

6.  An inventory for measuring clinical anxiety: psychometric properties.

Authors:  A T Beck; N Epstein; G Brown; R A Steer
Journal:  J Consult Clin Psychol       Date:  1988-12

Review 7.  Anxiety disorders in older adults: a comprehensive review.

Authors:  Kate B Wolitzky-Taylor; Natalie Castriotta; Eric J Lenze; Melinda A Stanley; Michelle G Craske
Journal:  Depress Anxiety       Date:  2010-02       Impact factor: 6.505

8.  Symptoms of Generalized Anxiety Disorder Among Adults: United States, 2019.

Authors:  Emily P Terlizzi; Maria A Villarroel
Journal:  NCHS Data Brief       Date:  2020-09

9.  Japanese-English language equivalence of the Cognitive Abilities Screening Instrument among Japanese-Americans.

Authors:  Laura E Gibbons; Susan McCurry; Kristoffer Rhoads; Kamal Masaki; Lon White; Amy R Borenstein; Eric B Larson; Paul K Crane
Journal:  Int Psychogeriatr       Date:  2008-10-24       Impact factor: 3.878

10.  A regularization approach for the detection of differential item functioning in generalized partial credit models.

Authors:  Gunther Schauberger; Patrick Mair
Journal:  Behav Res Methods       Date:  2020-02
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