First-line Medications for the Outpatient Treatment of Alcohol Use Disorder: A Systematic Review of Perceived Barriers
Bibliographic record
Abstract
OBJECTIVES: Alcohol use disorder (AUD) is a common illness with significant health and economic consequences. Although three pharmacotherapeutic agents have been shown to decrease heavy drinking days among individuals with AUD, they are vastly underutilized in clinical practice. The objective of this review was to elucidate barriers that may prevent patients from obtaining medication for addiction treatment (MAT) for AUD in an outpatient or residential setting. METHODS: Electronic searches of Medline and EMBASE were conducted, and reference lists were hand-searched. All study designs which discussed the use of MAT for AUD in an outpatient or residential setting were eligible for inclusion. Two reviewers independently screened the search output to identify potentially eligible articles, the full texts of which were retrieved and assessed for inclusion. RESULTS: After eliminating duplicate citations and articles that did not meet eligibility criteria, 23 articles were included in the review. Perceived barriers to obtaining pharmacotherapy for the treatment of AUD in an outpatient or residential setting were grouped into 3 themes: lack of knowledge and concerns about efficacy and complexity of prescribing; treatment philosophy and stigma; medication accessibility including formulary restrictions, geographical and socioeconomic barriers. CONCLUSIONS: Although evidence-based pharmacotherapeutics have been approved for the treatment of AUD, our findings suggest patients continue to experience barriers to the use of these medications. Efforts should be made to increase rates of prescribing by providers and the use of medications by patients. More research is needed to further elucidate perceived barriers to MAT use, along with strategies to overcome them.
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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 | 0.010 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".