Generalizability theory distinguishes between state and trait anxiety.

Abstract

Accurate distinction between state and trait anxiety is necessary for assessment and monitoring of individual anxiety levels over time and developing effective interventions to reduce anxiety. Generalizability theory (G-theory) is a suitable method to distinguish between state and trait and to evaluate reliability of test scores and sources of measurement error in the assessment of affective conditions. We applied G-theory to the widely used 40-item State and Trait Anxiety Inventory (STAI) completed by 139 participants on three occasions separated by 2-week intervals. The results show that both subscales of the STAI demonstrated excellent reliability for test scores in measuring trait anxiety with high generalizability of scores across occasions and persons (G = 0.84-0.92). The most dynamic aspects of state anxiety were identified in both subscales including satisfaction, nervousness, feelings of pleasure, perceived failure, calmness, feeling inadequate, and sensitivity to disappointments and this informed the development of a more sensitive state anxiety scale presented here. The STAI trait subscale and the proposed sensitive state subscale can be used to more accurately distinguish between state and trait anxiety. The most dynamic aspects of anxiety identified using G-theory are more amenable and need to be considered as the primary target of interventions aiming at reducing anxiety. More comprehensive assessment of state anxiety may benefit from the development of a longer scale informed by G-theory. (PsycInfo Database Record (c) 2021 APA, all rights reserved).