MétaCan
Menu
Back to cohort
Record W2005438636 · doi:10.1592/phco.21.7.731.34570

Practice‐Based Research: Lessons from Community Pharmacist Participants

2001· article· en· W2005438636 on OpenAlexaff
Scot H. Simpson, Jeffrey Johnson, Catherine M. Biggs, Rosemarie S. Biggs, Arlene Kuntz, William Semchuk, Jeff Taylor, Karen B. Farris, Ross T. Tsuyuki

Bibliographic record

VenuePharmacotherapy The Journal of Human Pharmacology and Drug Therapy · 2001
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsRegina Qu'Appelle Health RegionInstitute of Health EconomicsUniversity of SaskatchewanUniversity of Alberta
Fundersnot available
KeywordsCommunity pharmacistPharmacyPharmacistCommunity pharmacyPharmacy practiceCommunity practiceMedical educationMedicineNursingValue (mathematics)PsychologyFamily medicineComputer science

Abstract

fetched live from OpenAlex

We designed this project to determine community pharmacists' opinions regarding the challenges and motivations of their recent participation in a pharmacy practice-based research study At the conclusion of a randomized, multicenter study, 87 community pharmacist-investigators were sent a questionnaire that explored four areas: motivating factors to participate, barriers to participation, communication tools used by study coordinators, and design issues for future studies. Fifty-eight (67%) completed questionnaires were returned. Key factors motivating participation in the study were desire to improve the profession and opportunity to learn. Time was the greatest barrier to participation. Pharmacy practice-based research has two distinct advantages. First, it translates clinical knowledge into direct application in the community. Second, it provides needed data to demonstrate the value of enhanced pharmacy practice. Thorough understanding of pharmacists' opinions is necessary to optimize the design of future studies.

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)0.143
metaresearch head score (Gemma)0.141
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.756

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1430.141
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0100.008
Scholarly communication0.0080.008
Open science0.0070.011
Research integrity0.0090.008
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 head0.622
GPT teacher head0.589
Teacher spread0.033 · 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 designQualitative
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

Citations66
Published2001
Admission routes1
Has abstractyes

Explore more

Same venuePharmacotherapy The Journal of Human Pharmacology and Drug TherapySame topicPharmaceutical Practices and Patient OutcomesFrench-language works237,207