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A screening focusing on aftereffects of alcohol consumption in a student population. A National cross-sectional survey

dc.rights.licenseopenen_US
dc.contributor.authorHAZART, J.
dc.contributor.authorBLANQUET, M.
dc.contributor.authorDEBOST-LEGRAND, A.
dc.contributor.authorPERREVE, A.
dc.contributor.authorLEGER, S.
dc.contributor.authorMARTOIA, V.
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorMAURICE, Sylvie
dc.contributor.authorBROUSSE, G.
dc.contributor.authorGERBAUD, L.
dc.date.accessioned2020-11-16T13:58:43Z
dc.date.available2020-11-16T13:58:43Z
dc.date.issued2018-03-30
dc.identifier.issn1121-2233 (Print) 1121-2233en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/14033
dc.description.abstractEnIntroduction: Students overestimate alcohol consumption of those around them and underestimate their own, so that quantitative approach may not be the most relevant to assess students' drinking. The main objective was to provide an appropriate tool for screening for students with potential drinking problems. Methods: A multicentre cross-sectional survey was conducted by internet between February and June, 2013 in France. Thirteen questions explored alcohol consumption, including 8 concerning after-effects of drinking episodes (4 items of the AUDIT) and alcohol behaviour (CAGE test). A multiple correspondence analysis (MCA) was conducted to identify profiles of student's alcohol consumption. Partitioning methods were used to group students by mode of alcohol use. The most relevant items included in the MCA were identified. Three questions were identified as most pertinent among the students with potential drinking problems and ranked by a decision tree with the Chi-square Automatic Interaction Detector method. Finally, we assessed the generalisation of the model. Results: A total of 36,427 students participated in the survey: 25,679 were women (70.5% of respondents), sex ratio 0.42 and mean aged 21.2 (sd 3.7 years). Among those who had experimented with alcohol (N = 33,113), three consumption profiles were identified: "simple/non-use" (66.9%), "intermediate consumption" (25.9%) and "problem drinking" (7.2%). For the latter group, the three most relevant items were (Q20) "not able to stop drinking after starting", (Q21) "failed to do what was normally expected", and (Q23) "unable to remember what happened the night before". Conclusions: These results provide healthcare professionals with a 3-item screening tool for students "problem drinking".
dc.language.isoENen_US
dc.subject.enISPED
dc.title.enA screening focusing on aftereffects of alcohol consumption in a student population. A National cross-sectional survey
dc.title.alternativeJ Prev Med Hygen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.15167/2421-4248/jpmh2018.59.1.780en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed29938239en_US
bordeaux.journalJournal of Preventive Medicine and Hygieneen_US
bordeaux.pageE48-e62en_US
bordeaux.volume59en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - U1219en_US
bordeaux.issue1en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.teamISPEDen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-03194153
hal.version1
hal.date.transferred2021-04-09T11:13:19Z
hal.exporttrue
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