OBJECTIVE: This study evaluates the State-Trait Anxiety Inventory (STAI) structure using a Rasch psychometric approach, and a refined and shorter STAI version is proposed. METHODS: A cross-sectional study was performed with 900 inpatients scheduled for elective surgery. Age varied from 18 to 60 years (American Society of Anesthesiologists physical status I-III). Demographic information was collected using a structured questionnaire. The measuring instrument (the STAI) was applied to all patients in the afternoon before the surgery and prior to the patients receiving preoperative sedatives. RESULTS: Rasch analysis of the state and trait anxiety scales was performed separately. This analysis demonstrated that the original format of state and trait scales fails to show invariance across the trait-state anxiety level, which results in the unstable performance of items. The refined scale was retested in two subsequent random samples of 300 subjects each, and the results were confirmed. The performance was adequate regardless of gender. In the analysis, some items of the state scale (items 3,4,9,10,12,15, and 20) were deleted due to poor fit statistics. The remaining 13 items showed unidimensionality, local independence, and adequate index of internal consistency. Also, the original trait scale displayed several weaknesses. First, the four-point Likert response scale proved to be inadequate, and threshold disorders were found in all 20 items. Also, the original trait scale showed insufficient item-trait interaction and several individual item misfits. Following the rescoring process, and retesting in a second random sample, items were excluded (namely Items 3, 4, 11, 13, 14, 15, 18, and 19). The refined version showed local independence, unidimensionality, and adequate fit statistics. DISCUSSION: The results indicate that the application of the Rasch model led to the refinement of the classic STAI state and trait scales. In addition, they suggest that these shorter versions have a more suitable psychometric performance and are free of threshold disorders and differential item functioning problems. Published by Elsevier Inc.
OBJECTIVE: This study evaluates the State-Trait Anxiety Inventory (STAI) structure using a Rasch psychometric approach, and a refined and shorter STAI version is proposed. METHODS: A cross-sectional study was performed with 900 inpatients scheduled for elective surgery. Age varied from 18 to 60 years (American Society of Anesthesiologists physical status I-III). Demographic information was collected using a structured questionnaire. The measuring instrument (the STAI) was applied to all patients in the afternoon before the surgery and prior to the patients receiving preoperative sedatives. RESULTS: Rasch analysis of the state and trait anxiety scales was performed separately. This analysis demonstrated that the original format of state and trait scales fails to show invariance across the trait-state anxiety level, which results in the unstable performance of items. The refined scale was retested in two subsequent random samples of 300 subjects each, and the results were confirmed. The performance was adequate regardless of gender. In the analysis, some items of the state scale (items 3,4,9,10,12,15, and 20) were deleted due to poor fit statistics. The remaining 13 items showed unidimensionality, local independence, and adequate index of internal consistency. Also, the original trait scale displayed several weaknesses. First, the four-point Likert response scale proved to be inadequate, and threshold disorders were found in all 20 items. Also, the original trait scale showed insufficient item-trait interaction and several individual item misfits. Following the rescoring process, and retesting in a second random sample, items were excluded (namely Items 3, 4, 11, 13, 14, 15, 18, and 19). The refined version showed local independence, unidimensionality, and adequate fit statistics. DISCUSSION: The results indicate that the application of the Rasch model led to the refinement of the classic STAI state and trait scales. In addition, they suggest that these shorter versions have a more suitable psychometric performance and are free of threshold disorders and differential item functioning problems. Published by Elsevier Inc.
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Authors: Aline P Brietzke; Joanna R Rozisky; Jairo A Dussan-Sarria; Alicia Deitos; Gabriela Laste; Priscila F T Hoppe; Suzana Muller; Iraci L S Torres; Mário R Alvares-da-Silva; Rivadavio F B de Amorim; Felipe Fregni; Wolnei Caumo Journal: Front Neurosci Date: 2016-01-11 Impact factor: 4.677
Authors: Leonardo M Botelho; Leon Morales-Quezada; Joanna R Rozisky; Aline P Brietzke; Iraci L S Torres; Alicia Deitos; Felipe Fregni; Wolnei Caumo Journal: Front Hum Neurosci Date: 2016-06-27 Impact factor: 3.169