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Record W2053518889 · doi:10.3109/0142159x.2014.970623

Continuing professional development in HIV chronic disease management for primary care providers

2014· article· en· W2053518889 on OpenAlexafffund
Helen H. Kang, Benita Yip, William Chau, Adriana Nóhpal De La Rosa, David S. Hall, Rolando Barrios, Julio Montaner, Silvia Guillemi

Bibliographic record

VenueMedical Teacher · 2014
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsVancouver Coastal HealthSt. Paul's HospitalHealth CanadaAIDS Vancouver
FundersMinistry of Health, British Columbia
KeywordsMedicinePrimary careProfessional developmentContinuing educationHuman immunodeficiency virus (HIV)NursingChronic diseaseFamily medicineContinuing professional developmentContinuing medical educationDisease managementMEDLINENurse practitionersDiseaseMedical educationHealth careInternal medicine

Abstract

fetched live from OpenAlex

Primary care providers need continuing professional development (CPD) in order to improve their knowledge and confidence in the care of patients with chronic conditions. We developed an intensive modular CPD program in the chronic disease management of HIV for primary care providers. The program combines self-directed learning, interactive tutorials with experts, small group discussions, case studies, clinical training, one-on-one mentoring and individualized learning objectives. We trained 27 family physicians and 7 nurse practitioners between 2011 and 2013. The trainees reported high levels of satisfaction with the program. There was a 136.76% increase in the number of distinct HIV-positive patients receiving HIV-related medication refills that were prescribed by the trainees.

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)0.003
metaresearch head score (Gemma)0.010
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 score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.390
Teacher spread0.373 · 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

Citations3
Published2014
Admission routes2
Has abstractyes

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