Validity study of the Beck Anxiety Inventory (Portuguese version) by the Rasch Rating Scale model

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Abstract

Our objective was to conduct a validation study of the Portuguese version of the Beck Anxiety Inventory (BAI) by means of the Rasch Rating Scale Model, and then compare it with the most used scales of anxiety in Portugal. The sample consisted of 1,160 adults (427 men and 733 women), aged 18-82 years old (M=33.39; SD=11.85). Instruments were Beck Anxiety Inventory, State-Trait Anxiety Inventory and Zung Self-Rating Anxiety Scale. It was found that Beck Anxiety Inventory's system of four categories, the data-model fit, and people reliability were adequate. The measure can be considered as unidimensional. Gender and age-related differences were not a threat to the validity. BAI correlated significantly with other anxiety measures. In conclusion, BAI shows good psychometric quality.

Translated abstract

Foi objetivo a validação da versão portuguesa do Beck Anxiety Inventory (BAI) mediante o modelo Rasch Rating Scale e a sua comparação com as escalas mais usadas de ansiedade em Portugal. A amostra consistia de 1160 adultos (427 homens e 733 mulheres) com idades entre 18-82 anos (M = 33,39; DP = 11,85). Os instrumentos utilizados foram: BAI, State-Trait Anxiety Inventory e Zung Anxiety Scale. Verificou-se que o sistema de quatro categorias, o ajuste dos dados ao modelo e a fidelidade das pessoas eram adequados. A medida é unidimensional. O género e as diferenças relacionadas com a idade não se mostraram ameaças à validade. O BAI correlaciona-se significativamente com as restantes medidas de ansiedade. Conclui-se que o instrumento apresenta boa qualidade psicométrica.

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Manual da versão em português das Escalas Beck

J Cunha, JA CUNHA, J. CUNHA … (2001)

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Optimizing rating scale category effectiveness.

John M Linacre (2002)

Rating scales are employed as a means of extracting more information out of an item than would be obtained from a mere "yes/no", "right/wrong" or other dichotomy. But does this additional information increase measurement accuracy and precision? Eight guidelines are suggested to aid the analyst in optimizing the manner in which rating scales categories cooperate in order to improve the utility of the resultant measures. Though these guidelines are presented within the context of Rasch analysis, they reflect aspects of rating scale functioning which impact all methods of analysis. The guidelines feature rating-scale-based data such as category frequency, ordering, rating-to-measure inferential coherence, and the quality of the scale from measurement and statistical perspectives. The manner in which the guidelines prompt recategorization or reconceptualization of the rating scale is indicated. Utilization of the guidelines is illustrated through their application to two published data sets.