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Record W2112407584

Practice-based small group learning programs: systematic review.

2012· review· en· W2112407584 on OpenAlexaff
Eman Zaher, Savithiri Ratnapalan

Bibliographic record

VenuePubMed · 2012
Typereview
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceMedical educationMEDLINEFocus groupProfessional developmentSmall group learningClinical PracticeMedicineNursing
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify the format, content, and effects of practice-based small group learning (PBSGL) programs involving FPs. DATA SOURCES: The Ovid MEDLINE, EMBASE, and ERIC databases were searched from inception to the second week of November 2011, yielding 99 articles. STUDY SELECTION: Articles were included in the analysis if they described the format or content of or evaluated PBSGL programs among FPs. Thirteen articles were included in the analysis. SYNTHESIS: Two main PBSGL formats exist. The first is self-directed learning, which includes review and discussion of troubling or challenging patient cases. The contents of such programs vary with different teaching styles. The second format targets specific problems from practice to improve certain knowledge or skills or implement new guidelines by using patient cases to stimulate discussion of the selected topic. Both formats are similar in their ultimate goal, equally important, and well accepted by learners and facilitators. Evaluations of learners' perceptions and learning outcomes indicate that PBSGL constitutes a feasible and effective method of professional development. CONCLUSION: Current evidence suggests that PBSGL is a promising method of continuing professional development for FPs. Such programs can be adapted according to learning needs. Future studies that focus on the changes in practice effected by PBSGL will strengthen the evidence for this form of learning and motivate physicians and institutions to adopt it.

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)0.006
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.602
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.002

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 head0.174
GPT teacher head0.471
Teacher spread0.297 · 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

Citations45
Published2012
Admission routes1
Has abstractyes

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