Subtopic Deep Dive
Alcohol Use Disorders Identification
Research Guide
What is Alcohol Use Disorders Identification?
Alcohol Use Disorders Identification develops and validates screening tools like AUDIT and AUDIT-C to detect harmful alcohol consumption in vulnerable populations including the homeless.
Researchers evaluate sensitivity and specificity of brief screening versions in high-risk groups. Prevalence studies show elevated AUD rates among homeless individuals (Lewer et al., 2019, 147 citations). Over 180-citation works estimate AUD prevalence across Europe (Rehm et al., 2014).
Why It Matters
Screening tools enable early interventions that reduce substance-related homelessness and chronic disease burden. Lewer et al. (2019) found homeless people in London had six times higher odds of chronic diseases linked to alcohol use than housed controls. Horyniak et al. (2016, 255 citations) highlight high substance use prevalence among forced migrants, a group overlapping with homelessness, informing targeted public health responses. Hawk and D’Onofrio (2018, 181 citations) demonstrate emergency department screenings improve substance use disorder outcomes in vulnerable patients.
Key Research Challenges
Low Sensitivity in Homeless
Screening tools like AUDIT show reduced sensitivity in homeless populations due to atypical consumption patterns. Lewer et al. (2019) report higher chronic disease prevalence but validation gaps persist. Brief versions like AUDIT-C require population-specific cutoffs.
Prevalence Estimation Variability
AUD prevalence varies widely across homeless subgroups, complicating tool standardization. Rehm et al. (2014) estimate 5-10% AD rates in Europe but lack homeless stratification. Horyniak et al. (2016) note limited data on disaster-displaced migrants with AUD.
Validation in Acute Settings
Emergency screenings face feasibility issues in chaotic homeless environments. Hawk and D’Onofrio (2018) validate interventions but report implementation barriers. Velez et al. (2016, 168 citations) identify hospitalized patients' reluctance affecting tool accuracy.
Essential Papers
The Cannabis Youth Treatment (CYT) Study: Main findings from two randomized trials
Michael L. Dennis, Susan H. Godley, Guy Diamond et al. · 2004 · Journal of Substance Abuse Treatment · 771 citations
Segregation and Mortality: The Deadly Effects of Racism?
Chiquita Collins, David R. Williams · 1999 · Sociological Forum · 324 citations
Epidemiology of Substance Use among Forced Migrants: A Global Systematic Review
Danielle Horyniak, Jason Melo, Risa M. Farrell et al. · 2016 · PLoS ONE · 255 citations
Our understanding of substance use among forced migrants remains limited, particularly regarding persons displaced due to disasters, development and deportation. Despite a growing body of work amon...
Emergency department screening and interventions for substance use disorders
Kathryn Hawk, Gail D’Onofrio · 2018 · Addiction Science & Clinical Practice · 181 citations
Prevalence of and Potential Influencing Factors for Alcohol Dependence in Europe
Jürgen Rehm, Peter Anderson, Joe Barry et al. · 2014 · European Addiction Research · 180 citations
Alcohol use disorders (AUDs), and alcohol dependence (AD) in particular, are prevalent and associated with a large burden of disability and mortality. The aim of this study was to estimate prevalen...
“It’s been an Experience, a Life Learning Experience”: A Qualitative Study of Hospitalized Patients with Substance Use Disorders
Christine M. Velez, Christina Nicolaidis, P. Todd Korthuis et al. · 2016 · Journal of General Internal Medicine · 168 citations
Benefit–Cost in the California Treatment Outcome Project: Does Substance Abuse Treatment “Pay for Itself”?
Susan L. Ettner, David Huang, Elizabeth Evans et al. · 2005 · Health Services Research · 162 citations
Objective. To examine costs and monetary benefits associated with substance abuse treatment. Data Sources. Primary and administrative data on client outcomes and agency costs from 43 substance abus...
Reading Guide
Foundational Papers
Start with Rehm et al. (2014, 180 citations) for AUD prevalence baselines, then Dennis et al. (2004, 771 citations) for treatment context, as they establish metrics referenced in homeless studies.
Recent Advances
Study Lewer et al. (2019, 147 citations) for homeless-specific chronic disease links and Hawk and D’Onofrio (2018, 181 citations) for screening interventions.
Core Methods
Core techniques: AUDIT/AUDIT-C psychometric testing, cross-sectional prevalence surveys (Rehm et al., 2014), emergency screening protocols (Hawk and D’Onofrio, 2018).
How PapersFlow Helps You Research Alcohol Use Disorders Identification
Discover & Search
Research Agent uses searchPapers('AUDIT homeless sensitivity') to find Lewer et al. (2019), then citationGraph reveals Rehm et al. (2014) as a key prevalence reference, and findSimilarPapers uncovers Horyniak et al. (2016) for migrant overlaps.
Analyze & Verify
Analysis Agent applies readPaperContent on Hawk and D’Onofrio (2018) to extract sensitivity metrics, verifyResponse with CoVe checks screening claims against Lewer et al. (2019), and runPythonAnalysis computes pooled specificity from reported homeless data using GRADE for evidence grading.
Synthesize & Write
Synthesis Agent detects gaps in homeless-specific AUDIT cutoffs via contradiction flagging between Rehm et al. (2014) and Lewer et al. (2019), while Writing Agent uses latexEditText for methods sections, latexSyncCitations for 10+ references, and latexCompile for publication-ready tables; exportMermaid visualizes screening workflow diagrams.
Use Cases
"Calculate pooled AUD prevalence in homeless from recent studies"
Research Agent → searchPapers('alcohol disorders homeless prevalence') → Analysis Agent → runPythonAnalysis(pandas meta-analysis on Lewer 2019 + Horyniak 2016 data) → researcher gets CSV with 95% CI estimates and forest plot.
"Draft review on AUDIT validation for homeless screening"
Synthesis Agent → gap detection on Hawk 2018 + Rehm 2014 → Writing Agent → latexEditText(structured abstract) → latexSyncCitations(15 refs) → latexCompile(PDF) → researcher gets camera-ready LaTeX manuscript.
"Find code for AUDIT scoring in vulnerable populations"
Research Agent → paperExtractUrls(Horyniak 2016) → paperFindGithubRepo → githubRepoInspect → researcher gets validated Python AUDIT-C calculator with homeless dataset benchmarks.
Automated Workflows
Deep Research workflow conducts systematic review of 50+ AUDIT papers, chaining searchPapers → citationGraph → GRADE grading for homeless sensitivity meta-analysis. DeepScan applies 7-step verification to Velez et al. (2016) qualitative data, checkpointing prevalence claims against Rehm et al. (2014). Theorizer generates hypotheses on brief screeners from Hawk and D’Onofrio (2018) intervention patterns.
Frequently Asked Questions
What defines Alcohol Use Disorders Identification?
It focuses on screening tools like AUDIT and AUDIT-C validated for harmful alcohol use detection in homeless and vulnerable groups, emphasizing sensitivity and specificity.
What are key methods used?
Methods include psychometric validation of AUDIT/AUDIT-C, prevalence surveys, and emergency department screenings (Hawk and D’Onofrio, 2018), with cross-sectional comparisons like Lewer et al. (2019).
What are major papers?
Foundational: Rehm et al. (2014, 180 citations) on European AD prevalence; recent: Lewer et al. (2019, 147 citations) comparing homeless vs. housed health.
What open problems remain?
Challenges include tool validation for diverse homeless subgroups and integration into acute care without reducing accuracy (Velez et al., 2016; Horyniak et al., 2016).
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Part of the Homelessness and Social Issues Research Guide