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Record W2064187773 · doi:10.1207/s15328015tlm1602_10

Teaching the Musculoskeletal Examination: Are Patient Educators as Effective as Rheumatology Faculty?

2004· article· en· W2064187773 on OpenAlexaff
Susan Humphrey‐Murto, C. Douglas Smith, Claire Touchie, Timothy C. Wood

Bibliographic record

VenueTeaching and Learning in Medicine · 2004
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsLikert scaleMedicineMedical educationTUTORInternal medicineRheumatologyFaculty developmentPhysical therapyFamily medicinePsychologyProfessional developmentPedagogy

Abstract

fetched live from OpenAlex

BACKGROUND: Effective education of clinical skills is essential if doctors are to meet the needs of patients with rheumatic disease, but shrinking faculty numbers has made clinical teaching difficult. A solution to this problem is to utilize patient educators. PURPOSE: This study evaluates the teaching effectiveness of patient educators compared to rheumatology faculty using the musculoskeletal (MSK) examination. METHOD: Sixty-two 2nd-year medical students were randomized to receive instruction from patient educators or faculty. Tutorial groups received instructions during three, 3-hr sessions. Clinical skills were evaluated by a 9 station objective structured clinical examination. Students completed a tutor evaluation form to assess their level of satisfaction with the process. RESULTS: Faculty-taught students received a higher overall mark (66.5% vs. 62.1%,) and fewer failed than patient educator-taught students (5 vs. 0, p = 0.02). Students rated faculty educators higher than patient educators (4.13 vs. 3.58 on a 5-point Likert scale). CONCLUSION: Rheumatology faculty appear to be more effective teachers of the MSK physical exam than patient educators.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.007
GPT teacher head0.309
Teacher spread0.302 · 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 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

Citations25
Published2004
Admission routes1
Has abstractyes

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