AIMS: The study aimed to evaluate psychometrically a Danish translation of the Short Alcohol Withdrawal Scale (SAWS) in an outpatient setting in patients with Alcohol Dependence (AD) and Alcohol Withdrawal Symptoms/Syndrome (AWS). METHODS: One hundred and twenty-two patients with AD and AWS filled in a 10-item rating scale to describe their symptoms with four graduations on five physical and five psychological items. The question of dimensionality of the construct was addressed in three different ways. First, a scree plot was constructed based on the polychoric correlations between items. Second, promax factor loadings were calculated for a two-factor model. These two steps were based on exploratory factor analysis. Third, specific violations such as local dependence and differential item functioning were investigated under the one-factor model in a confirmatory factor analysis. RESULTS: The scree plot supported one or two dimensions while the promax rotations gave little support for a two-factor model. The confirmatory analysis also supported a one-factor model. CONCLUSION: The decomposition of the polychoric correlation matrix into eigenvalues and vectors suggested that there was most likely one factor underlying the 10 items in the SAWS. This was confirmed by a confirmative factor analysis with only one component when specific model violations such as local dependence and differential item findings were investigated. The SAWS is easy to use.
RCT Entities:
AIMS: The study aimed to evaluate psychometrically a Danish translation of the Short Alcohol Withdrawal Scale (SAWS) in an outpatient setting in patients with Alcohol Dependence (AD) and AlcoholWithdrawal Symptoms/Syndrome (AWS). METHODS: One hundred and twenty-two patients with AD and AWS filled in a 10-item rating scale to describe their symptoms with four graduations on five physical and five psychological items. The question of dimensionality of the construct was addressed in three different ways. First, a scree plot was constructed based on the polychoric correlations between items. Second, promax factor loadings were calculated for a two-factor model. These two steps were based on exploratory factor analysis. Third, specific violations such as local dependence and differential item functioning were investigated under the one-factor model in a confirmatory factor analysis. RESULTS: The scree plot supported one or two dimensions while the promax rotations gave little support for a two-factor model. The confirmatory analysis also supported a one-factor model. CONCLUSION: The decomposition of the polychoric correlation matrix into eigenvalues and vectors suggested that there was most likely one factor underlying the 10 items in the SAWS. This was confirmed by a confirmative factor analysis with only one component when specific model violations such as local dependence and differential item findings were investigated. The SAWS is easy to use.
Authors: Ashley A Knapp; Nicholas P Allan; Renee Cloutier; Heidemarie Blumenthal; Shahrzad Moradi; Alan J Budney; Sarah E Lord Journal: J Behav Med Date: 2020-09-27