MétaCan
Menu
Back to cohort
Record W3083037575 · doi:10.15766/mep_2374-8265.10945

Deconstructing the Joint Examination: A Novel Approach to Teaching Introductory Musculoskeletal Physical Examination Skills for Medical Students

2020· article· en· W3083037575 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.

Bibliographic record

VenueMedEdPORTAL · 2020
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCurriculumCoachingConfidence intervalMedical educationObjective structured clinical examinationPsychologyMedicinePhysical educationPhysical therapyInternal medicinePedagogy

Abstract

fetched live from OpenAlex

Introduction: Musculoskeletal (MSK) disorders are very common, but suboptimal teaching of MSK medicine occurs and expert clinicians agree that MSK physical examination (PE) skills can be confusing and complicated for medical students. An innovative approach in introductory teaching of MSK PE skills was developed using constructivist theory for second-year medical students. Methods: -test comparisons of self-confidence scores and MSK-specific OSCE station scores between the historical and innovation groups. Results: < 0.001). OSCE scores significantly improved in MSK-specific stations, with medium to large effect size across the different stations. Discussion: We successfully used a framework of deconstruction, repetition, and spaced practice to develop fundamental MSK PE skills in preclerkship medical students. This curriculum structure provides an effective example for teaching introductory MSK PE skills to early medical learners.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.941
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.312
Teacher spread0.296 · 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