Measuring State and Trait Anxiety: An Application of Multidimensional Item Response Theory.
anxiety
assessment
bifactor
cognitive
psychometrics
somatic
Journal
Behavioral sciences (Basel, Switzerland)
ISSN: 2076-328X
Titre abrégé: Behav Sci (Basel)
Pays: Switzerland
ID NLM: 101576826
Informations de publication
Date de publication:
28 Jul 2023
28 Jul 2023
Historique:
received:
20
03
2023
revised:
21
07
2023
accepted:
25
07
2023
medline:
25
8
2023
pubmed:
25
8
2023
entrez:
25
8
2023
Statut:
epublish
Résumé
The State-Trait Inventory for Cognitive and Somatic Anxiety (STICSA) is a widely used measure of state and trait anxiety. Within the Classical Testing Theory model, consistent findings provide support for its multidimensional factor structure, discriminant, convergent, and nomological validity, as well as age and gender invariance, across healthy and clinical samples. Nevertheless, some issues regarding STICSA dimensionality and item-scale composition remain unresolved (e.g., both bifactor and two-factor models were found to fit data equally well). The goal of this study was to investigate the STICSA's dimensionality within the Item Response Theory, and to assess the tenability of the bifactor model as a plausible model over the multidimensional model. The sample consisted of 3338 Italian participants (58.21% females; 41.79% males) with an average age of 35.65 years (range: 18-99; SD = 20.25). Both bifactor and two-correlated dimensions of the STICSA scales were confirmed to fit data by applying the multidimensional Item Response Theory (mIRT). While the bifactor model showed better fit indices, the multidimensional model was more accurate and precise (0.86-0.88) in estimating state and trait latent anxiety. A further comparison between multidimensional item parameters revealed that the multidimensional and bifactor models were equivalent. Findings showed that the STICSA is an accurate and precise instrument for measuring somatic and cognitive symptomatology dimensions within state and trait anxiety. The use of the state/trait total score requires special attention from the clinicians and researchers to avoid bias in the psychodiagnostic assessment.
Identifiants
pubmed: 37622768
pii: bs13080628
doi: 10.3390/bs13080628
pmc: PMC10451624
pii:
doi:
Types de publication
Journal Article
Langues
eng
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