The Psychometric Properties of a Shortened Dutch Version of the Consequences Scale Used in the Core Alcohol and Drug Survey
Principal Investigator(s): View help for Principal Investigator(s) Sara De Bruyn
Version: View help for Version V1
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Project Citation:
De Bruyn, Sara. The Psychometric Properties of a Shortened Dutch Version of the Consequences Scale Used in the Core Alcohol and Drug Survey. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2017-11-02. https://doi.org/10.3886/E100248V1
Project Description
Summary:
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Background: Alcohol and drug misuse among
college students has been studied extensively and has been clearly identified as
a public health problem. Within more general populations alcohol misuse remains
one of the leading causes of disease, disability and death worldwide. Conducting
research on alcohol misuse requires valid and reliable instruments to measure its
consequences. One scale that is often used is the consequences scale in the Core
Alcohol and Drug Survey (CADS). However, psychometric studies on the CADS are
rare and the ones that do exist report varying results. This article aims to
address this imbalance by examining the psychometric properties of a Dutch
version of the CADS in a large sample of Flemish university and college
students.
Methods: The analyses are based on data collected by the inter-university project ‘Head in the clouds’, measuring alcohol use among students. In total, 19,253 students participated (22.1% response rate). The CADS scale was measured using 19 consequences, and participants were asked how often they had experienced these on a 6-point scale. Firstly, the factor structure of the CADS was examined. Two models from literature were compared by performing confirmatory factor analyses (CFA) and were adapted if necessary. Secondly, we assessed the composite reliability as well as the convergent, discriminant and concurrent validity.
Results: The two-factor model, identifying personal consequences (had a hangover; got nauseated or vomited; missed a class) and social consequences (got into an argument or fight; been criticized by someone I know; done something I later regretted; been hurt or injured) was indicated to be the best model, having both a good model fit and an acceptable composite reliability. In addition, construct validity was evaluated to be acceptable, with good discriminant validity, although the convergent validity of the factor measuring ‘social consequences’ could be improved. Concurrent validity was evaluated as good.
Conclusions: In deciding which model best represents the data, it is crucial that not only the model fit is evaluated, but the importance of factor reliability and validity issues is also taken into account. The two-factor model, identifying personal consequences and social consequences, was concluded to be the best model. This shortened Dutch version of the CADS (CADS_D) is a useful tool to screen alcohol-related consequences among college students.
Methods: The analyses are based on data collected by the inter-university project ‘Head in the clouds’, measuring alcohol use among students. In total, 19,253 students participated (22.1% response rate). The CADS scale was measured using 19 consequences, and participants were asked how often they had experienced these on a 6-point scale. Firstly, the factor structure of the CADS was examined. Two models from literature were compared by performing confirmatory factor analyses (CFA) and were adapted if necessary. Secondly, we assessed the composite reliability as well as the convergent, discriminant and concurrent validity.
Results: The two-factor model, identifying personal consequences (had a hangover; got nauseated or vomited; missed a class) and social consequences (got into an argument or fight; been criticized by someone I know; done something I later regretted; been hurt or injured) was indicated to be the best model, having both a good model fit and an acceptable composite reliability. In addition, construct validity was evaluated to be acceptable, with good discriminant validity, although the convergent validity of the factor measuring ‘social consequences’ could be improved. Concurrent validity was evaluated as good.
Conclusions: In deciding which model best represents the data, it is crucial that not only the model fit is evaluated, but the importance of factor reliability and validity issues is also taken into account. The two-factor model, identifying personal consequences and social consequences, was concluded to be the best model. This shortened Dutch version of the CADS (CADS_D) is a useful tool to screen alcohol-related consequences among college students.
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