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Record W3199287667 · doi:10.1097/adm.0000000000000918

First-line Medications for the Outpatient Treatment of Alcohol Use Disorder: A Systematic Review of Perceived Barriers

2021· review· en· W3199287667 on OpenAlexaff
Caroline Gregory, Yelena Chorny, Shelley McLeod, Rohit Mohindra

Bibliographic record

VenueJournal of Addiction Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsSchwartz/Reisman Emergency Medicine Institute
Fundersnot available
KeywordsMedicineAlcohol use disorderAlcoholPsychiatryFamily medicine

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.214
Threshold uncertainty score0.775

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.080
GPT teacher head0.375
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations28
Published2021
Admission routes1
Has abstractyes

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