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Record W4322504465 · doi:10.3390/pharmacy11020045

Pharmacist Administration of Long-Acting Injectable Antipsychotics to Community-Dwelling Patients: A Scoping Review

2023· review· en· W4322504465 on OpenAlexaff
Andrea Murphy, Sowon Suh, Louise Gillis, Jason Morrison, David M. Gardner

Bibliographic record

VenuePharmacy · 2023
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsKellogg's (Canada)Dalhousie University
Fundersnot available
KeywordsPsycINFOMEDLINEMedicineScopusPharmacistPharmacyMedical prescriptionFamily medicineNursingPolitical science

Abstract

fetched live from OpenAlex

Long-acting injectable antipsychotics (LAIAs) have demonstrated positive outcomes for people with serious mental illnesses. They are underused, and access to LAIAs can be challenging. Pharmacies could serve as suitable environments for LAIA injection by pharmacists. To map and characterize the literature regarding the administration of LAIAs by pharmacists, a scoping review was conducted. Electronic-database searches (e.g., PsycINFO, Ovid Medline, Scopus, and Embase) and others including ProQuest Dissertations & Theses Global and Google, were conducted. Citation lists and cited-reference searches were completed. Zotero was used as the reference-management database. Covidence was used for overall review management. Two authors independently screened articles and performed full-text abstractions. From all sources, 292 studies were imported, and 124 duplicates were removed. After screening, 13 studies were included for abstraction. Most articles were published in the US since 2010. Seven studies used database and survey methods, with adherence and patient satisfaction as the main patient-outcomes assessed. Reporting of pharmacists' and patients' perspectives surrounding LAIA administration was minimal and largely anecdotal. Financial analyses for services were also limited. The published literature surrounding pharmacist administration of LAIAs is limited, providing little-to-no guidance for the development and implementation of this service by others.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.609
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.332
GPT teacher head0.533
Teacher spread0.201 · 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.

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

Citations5
Published2023
Admission routes1
Has abstractyes

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