ArticleBMC public health2016
A rank based social norms model of how people judge their levels of drunkenness whilst intoxicated.
Article in BMC public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 17 citations in OpenAlex.
- [Analysis of potential association of alcohol exposure with femoral head osteonecrosis and construction of a diagnostic model using machine learning].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026Article
- Taking pleasure seriously: Should alcohol research say more about fun?Addiction (Abingdon, England) · 2025Article
- Are you feeling what I'm feeling? Momentary interactions between personal and perceived peer subjective response predict craving and continued drinking in young adults.Drug and alcohol dependence · 2025Article
- Combining refutations and social norms increases belief change.Quarterly journal of experimental psychology (2006) · 2023Article
- An Exploration of the Multiplicative Effect of "Other People" and Other Environmental Effects on Violence in the Night-Time Environment.International journal of environmental research and public health · 2022Review
- Breath Alcohol Concentration and Perception of Drunkenness: A Comparison between Adolescents and Young Adults Drinking Alcohol in Public Settings.International journal of environmental research and public health · 2020Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundA rank based social norms model predicts that drinkers' judgements about their drinking will be based on the rank of their breath alcohol level amongst that of others in the immediate environment, rather than their actual breath alcohol level, with lower relative rank associated with greater feelings of safety. This study tested this hypothesis and examined how people judge their levels of drunkenness and the health consequences of their drinking whilst they are intoxicated in social drinking environments.
methodsBreath alcohol testing of 1,862 people (mean age = 26.96 years; 61.86 % male) in drinking environments. A subset (N = 400) also answered four questions asking about their perceptions of their drunkenness and the health consequences of their drinking (plus background measures).
resultsPerceptions of drunkenness and the health consequences of drinking were regressed on: (a) breath alcohol level, (b) the rank of the breath alcohol level amongst that of others in the same environment, and (c) covariates. Only rank of breath alcohol level predicted perceptions: How drunk they felt (b 3.78, 95 % CI 1.69 5.87), how extreme they regarded their drinking that night (b 3.7, 95 % CI 1.3 6.20), how at risk their long-term health was due to their current level of drinking (b 4.1, 95 % CI 0.2 8.0) and how likely they felt they would experience liver cirrhosis (b 4.8. 95 % CI 0.7 8.8). People were more influenced by more sober others than by more drunk others.
conclusionWhilst intoxicated and in drinking environments, people base judgements regarding their drinking on how their level of intoxication ranks relative to that of others of the same gender around them, not on their actual levels of intoxication. Thus, when in the company of others who are intoxicated, drinkers were found to be more likely to underestimate their own level of drinking, drunkenness and associated risks. The implications of these results, for example that increasing the numbers of sober people in night time environments could improve subjective assessments of drunkenness, are discussed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.