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Record W7133101470

Use of a cannabis clinical guide by community pharmacists providing care for people using cannabis: an exploratory feasibility study

2024· dissertation· W7133101470 on OpenAlexafffund
Avery S. Loi

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Toronto
FundersCentre for Climate Change Economics and Policy, University of LeedsOntario College of PharmacistsNational Academies of Sciences, Engineering, and Medicine
KeywordsFocus groupExploratory researchCommunity pharmacyCannabisPharmacyPharmacy practiceCommunity practicePharmaceutical care
DOInot available

Abstract

fetched live from OpenAlex

Pharmacists are uniquely positioned to provide care to the 6.4 million Canadians using cannabis. Pharmacists’ reported lack of comfort with their cannabis-related knowledge is a barrier. To address this, we evaluated a cannabis clinical guide for pharmacists. We aimed to describe the use of this guide by community pharmacists to provide care for patient using cannabis, in order to inform feasibility. A secondary objective was to identify pharmacists’ perspectives on use of the guide in their practice. We recruited four community pharmacists for this exploratory feasibility study who used the guide in their practice for three months, and conducted a focus group to gather their perspectives. A global assessment of feasibility considered implementation determinants and outcomes, how the guide was used in practice, and participant feedback. It was determined that a future trial evaluating the impact and implementation of the cannabis clinical guide in community pharmacies would be feasible.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.031
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.217
GPT teacher head0.524
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2024
Admission routes2
Has abstractyes

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