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Record W2124389011 · doi:10.1186/s12909-015-0350-1

A scoping review of medical education research in family medicine

2015· review· en· W2124389011 on OpenAlexaff
Fiona Webster, Paul Krueger, H. Robson MacDonald, Douglas Archibald, Deanna Telner, Jessica Bytautas, Cynthia Whitehead

Bibliographic record

VenueBMC Medical Education · 2015
Typereview
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsBruyèreUniversity of OttawaCarleton UniversityUniversity of Toronto
Fundersnot available
KeywordsMedical educationCurriculumMEDLINEMedicinePsychologyPedagogyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Little is known about the state of education research within family medicine. As family medicine education models develop, it is important to develop an understanding of the current state of this research and develop ways to advance the field. METHODS: We conducted a scoping review of family medicine education research to describe 1) research topic areas and 2) the methodologies and methods used to study these topics. MEDLINE, Social Sciences Abstracts and ERIC electronic databases were searched. 817 full text articles from 2002 to 2012 were screened; 624 articles were included in the review. RESULTS: The following research topic areas were identified: continuing education, curriculum development, undergraduate education, teaching methods, assessment techniques, selection of entrants, non-clinical skills, professional and faculty development, clinical decision-making and resident well-being. Quantitative studies comprised the large majority of research approaches; overall minimal methodological details were provided. CONCLUSIONS: Our review highlights an overall need for increased sophisticated in methodological approaches to education research in family medicine, a problem that could be ameliorated by multiple strategies including better engagement of methodologists throughout the research process. The results provide guidance for future family medicine education research programs.

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)0.040
metaresearch head score (Gemma)0.062
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.607
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0400.062
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.610
GPT teacher head0.724
Teacher spread0.114 · 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; both teacher heads agree on what is shown here.

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

Citations47
Published2015
Admission routes1
Has abstractyes

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