Canadian guideline for the clinical management of high-risk drinking and alcohol use disorder
Bibliographic record
Abstract
BACKGROUND: In Canada, low awareness of evidence-based interventions for the clinical management of alcohol use disorder exists among health care providers and people who could benefit from care. To address this gap, the Canadian Research Initiative in Substance Misuse convened a national committee to develop a guideline for the clinical management of high-risk drinking and alcohol use disorder. METHODS: Development of this guideline followed the ADAPTE process, building upon the 2019 British Columbia provincial guideline for alcohol use disorder. A national guideline committee (consisting of 36 members with diverse expertise, including academics, clinicians, people with lived and living experiences of alcohol use, and people who self-identified as Indigenous or Métis) selected priority topics, reviewed evidence and reached consensus on the recommendations. We used the Appraisal of Guidelines for Research and Evaluation Instrument (AGREE II) and the Guidelines International Network's Principles for Disclosure of Interests and Management of Conflicts to ensure the guideline met international standards for transparency, high quality and methodological rigour. We rated the final recommendations using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) tool; the recommendations underwent external review by 13 national and international experts and stakeholders. RECOMMENDATIONS: The guideline includes 15 recommendations that cover screening, diagnosis, withdrawal management and ongoing treatment, including psychosocial treatment interventions, pharmacotherapies and community-based programs. The guideline committee identified a need to emphasize both underused interventions that may be beneficial and common prescribing and other practice patterns that are not evidence based and that may potentially worsen alcohol use outcomes. INTERPRETATION: The guideline is intended to be a resource for physicians, policymakers and other clinical and nonclinical personnel, as well as individuals, families and communities affected by alcohol use. The recommendations seek to provide a framework for addressing a large burden of unmet treatment and care needs for alcohol use disorder within Canada in an evidence-based manner.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".