Alcohol Use Disorders in Primary Health Care: What Do We Know and Where Do We Go?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: To analyze the current paradigm and clinical practice for dealing with alcohol use disorders (AUD) in primary health care. METHODS: Analyses of guidelines and recommendations, reviews and meta-analyses. RESULTS: Many recommendations or guidelines for interventions for people with alcohol use problems in primary health care, from hazardous drinking to AUD, can be summarized in the SBIRT principle: screening for alcohol use and alcohol-related problems, brief interventions for hazardous and in some cases harmful drinking, referral to specialized treatment for people with AUD. However, while there is some evidence that these procedures are effective in reducing drinking levels, they are rarely applied in clinical practice in primary health care, and no interventions are initiated, even if the primary care physician had detected problems or AUD. Rather than asking primary health care physicians to conduct interventions which are not typical for medical doctors, we recommend treatment initiation for AUD at the primary health care level. AUD should be treated like hypertension, i.e. with regular checks for alcohol consumption, advice for behavioral interventions in case of consumption exceeding thresholds, and pharmaceutical assistance in case the behavioral interventions were not successful. Minimally, alcohol consumption should be screened for in all situations where there is a co-morbidity with alcohol being a potential cause (such as hypertension, insomnia, depression or anxiety disorders). CONCLUSIONS: A paradigm shift is proposed for dealing with problematic alcohol consumption in primary health care, where initiation for treatment for AUD is seen as the central element.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it