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Publisher: Wiley
Languages: English
Types: Article
Subjects:
Background: There is inadequate recognition of alcohol misuse as a public health issue in India. Information on screening measures is critical for prevention and early intervention efforts. This study critically evaluated the full and shorter versions of the AUDIT and RAPS4-QF as screening measures for alcohol use disorders (AUDs) in a community sample of male drinkers in Goa, India. Methods: Data from male drinking respondents in a population study on alcohol use patterns and sexual risk behaviors in randomly selected rural and urban areas of North Goa are reported. Overall, 39% (n = 743) of the 1899 screened men, age 18 to 49, reported consuming alcohol in the last 12 months. These current drinkers were administered the screening measures as part of detailed interviews on drinking patterns and AUD symptoms. Receiver Operating Characteristic (ROC) analysis was conducted for each combination of screening measure and criterion (alcohol dependence or any AUD). Reliability and correlations among the 4 measures were also examined. Results: All 4 measures performed well with area under the curves of at least 0.79. The full screeners that included both drinking patterns and problem items (the AUDIT and the RAP4-QF) performed better than their shorter versions (the AUDIT-C and the RAPS4) in detecting AUDs. Performance of the AUDIT and RAPS4-QF improved with lowered and raised thresholds, respectively, and alternate cut-off scores are suggested. Scores on the full measures were significantly correlated (0.80). Reliability estimates for the AUDIT measures were higher than those for the RAPS4 measures. Conclusions: All measures were efficient at detecting AUDs. When screening for alcohol-related problems among males in the general population in India, cut-off scores for screeners may need to be adjusted. Selecting an appropriate screening measure and cut-off score necessitates careful consideration of the screening context and resources available to confirm alcohol-related diagnoses.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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