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Impact of feedback from pharmacists in reducing antipsychotic polypharmacy in schizophrenia

2011· article· en· W1560370757 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePsychiatry and Clinical Neurosciences · 2011
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersCanadian Psychiatric Research Foundation
KeywordsPolypharmacyAntipsychoticMedical prescriptionMedicineSchizophrenia (object-oriented programming)Psychological interventionPsychiatryPharmacology

Abstract

fetched live from OpenAlex

The objective was to examine effects of active interventions on physician's prescribing of antipsychotic polypharmacy. Prescriptions for patients with schizophrenia at the Centre for Addiction and Mental Health, Canada were collected in 2006 (n = 648) and 2008 (n = 778). During the intervening period, a pharmacist monitored prescriptions with antipsychotic polypharmacy and contacted corresponding prescribers to provide education on risks of polypharmacy. Moreover, educational sessions on polypharmacy were presented to inpatient and outpatient teams. A three-fold decrease in the prevalence of antipsychotic polypharmacy was observed between 2006 (18.3%) and 2008 (6.6%). Thus, active monitoring of prescriptions with educational interventions could reduce antipsychotic polypharmacy.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.093
GPT teacher head0.424
Teacher spread0.332 · 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