Alcohol dependence and treatment utilization in Europe – a representative cross-sectional study in primary care
Bibliographic record
Abstract
BACKGROUND: Alcohol dependence (AD) in Europe is prevalent and causes considerable health burden. Recognition by general practitioners (GPs) and provision of or referral to treatment may contribute to reduce this burden. This paper studied AD prevalence in varying European primary care settings and examined who received treatment. METHODS: In a cross-sectional multi-centre study in six European countries, 358 general practitioners assessed 13,003 primary care patients between January 2013 and January 2014, of which 8,476 patients were interviewed, collecting information on socio-demographics, physical and mental problems, and on alcohol use, problems and treatment. AD diagnoses were determined by GPs' clinical judgement and a standardized interview. A wide definition for AD treatment included individual and group interventions provided by different health professionals. Descriptive as well as inferential statistics were employed. RESULTS: AD was prevalent among patients in European primary health care settings (8.7 %, 95 % confidence interval (CI): 8.1-9.3 %). Treatment rates were low (22.3 % of all AD cases, 95 % CI: 19.4-25.2 %). For both prevalence and treatment utilization, considerable country variations were observed. AD was associated with a number of socio-economic disadvantages (e.g. higher unemployment rate) and higher physical (e.g., liver disease, hypertension) and mental comorbidities (e.g., depression, anxiety). Liver problems, mental distress and daily amount of alcohol used were higher among treated versus untreated male patients with AD. CONCLUSION: A minority of people identified as having AD received treatment, showing heavier drinking patterns and a higher level of co-morbidity. Different types of treatment, depending on severity of AD, should be considered.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".