Psychometric properties of the Alcohol Use Disorders Identification Test (AUDIT) across cross-cultural subgroups, genders, and sexual orientations: Findings from the International Sex Survey (ISS)

© 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).INTRODUCTION: Despite being a widely used screening questionnaire, there is no consensus on the most appropriate measurement model for the Alcohol Use Disorders Identification Test (AUDIT). Furthermore, there have been limited studies on its measurement invariance across cross-cultural subgroups, genders, and sexual orientations. AIMS: The present study aimed to examine the fit of different measurement models for the AUDIT and its measurement invariance across a wide range of subgroups by country, language, gender, and sexual orientation. METHODS: Responses concerning past-year alcohol use from the participants of the cross-sectional International Sex Survey were considered (N = 62,943; M age: 32.73; SD = 12.59). Confirmatory factor analysis, as well as measurement invariance tests were performed for 21 countries, 14 languages, three genders, and four sexual-orientation subgroups that met the minimum sample size requirement for inclusion in these analyses. RESULTS: A two-factor model with factors describing 'alcohol use' (items 1-3) and 'alcohol problems' (items 4-10) showed the best model fit across countries, languages, genders, and sexual orientations. For the former two, scalar and latent mean levels of invariance were reached considering different criteria. For gender and sexual orientation, a latent mean level of invariance was reached. CONCLUSIONS: In line with the two-factor model, the calculation of separate alcohol-use and alcohol-problem scores is recommended when using the AUDIT. The high levels of measurement invariance achieved for the AUDIT support its use in cross-cultural research, capable also of meaningful comparisons among genders and sexual orientations.Peer reviewe

The eleven-item Alcohol, Smoking and Substance Involvement Screening Test (ASSIST-11): Cross-cultural psychometric evaluation across 42 countries

The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) is an instrument to screen substance-use-related health risks. However, little is known whether the ASSIST could be further shortened while remaining psychometrically sound across different countries, languages, gender identities, and sexual-orientation-based groups. The study aimed to validate a shortened 11-item ASSIST (ASSIST-11). Using the International Sex Survey data, 82,243 participants (M age = 32.39 years) across 42 countries and 26 languages completed questions from the ASSIST-11 regarding gender identity, sexual orientation, and other information. Confirmatory factor analysis (CFA) and multigroup CFA (MGCFA) evaluated the ASSIST-11's structure and tested measurement invariance across groups. Cronbach's α and McDonald's ω were used to examine the internal consistency. Cohen's d and independent t-tests were used to examine known-group validity. The ASSIST-11 was unidimensional across countries, languages, age groups, gender identities (i.e., men, women, and gender-diverse individuals), and sexual orientations (i.e., heterosexual and sexual minority individuals). Cronbach's α was 0.63 and McDonald's ω was 0.68 for the ASSIST-11. Known-group validity was supported by Cohen's d (range between 0.23 and 0.40) with significant differences (p-values<0.001). The ASSIST-11 is a modified instrument with a unidimensional factor structure across different languages, age groups, countries, gender identities, and sexual orientations. The low internal consistency of the ASSIST-11 might be acceptable as it assesses a broad concept (i.e., use of several different substances). Healthcare providers and researchers may use the ASSIST-11 to quickly assess substance-use information from general populations and evaluate the need to follow up with more detailed questions about substance use