MétaCan
Menu
Back to cohort
Record W4416221124 · doi:10.1302/1358-992x.2025.13.057

A RANDOMIZED CONTROLLED TRIAL TO EXAMINE THE EFFECTIVENESS OF 20 MUSCULOSKELETAL “SHORT” CASE SIMULATIONS ON FAMILY MEDICINE RESIDENTS’ DEVELOPMENT OF KNOWLEDGE AND SKILLS: A PILOT STUDY

2025· article· en· W4416221124 on OpenAlexaff
Veronica Wadey, Adalsteinn Brown, Stanley J. Hamstra, Anne Wideman, Navin Kaushal, Sam Keshen, Purti Papneja, Alex Kiss

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRandomized controlled trialSession (web analytics)FeelingProtocol (science)Intervention (counseling)DemographicsInformed consentClinical trialAlternative medicine

Abstract

fetched live from OpenAlex

Musculoskeletal (MSK) complaints comprise up to 30% of primary care visits and training is variable among institutions (1). The COVID pandemic contributed to learners feeling unprepared for practice due to the abrupt cessation of clinical exposure (2). Strategies to optimize learning of MSK conditions to prepare learners for real-world clinical encounters is important (3). A 20 module MSK case simulation educational tool was previously developed and tested to be useful in improving knowledge and skills. The purpose of this study was to determine if Family Medicine residents completing the 20 MSK Short Case Simulations delivered through on-line links would improve their knowledge, skills and satisfaction in learning about how to identify and initially manage patients with various MSK conditions when compared to learners not exposed to the same educational tool. Study Design: Randomized Control Trial. Fourteen post-graduate year one (PGY1) and 12 post-graduate year two (PGY2) family medicine residents were randomized to the CTL (N=13) or EXP (13) groups. Residents attended an orientation session outlining the study protocol and consents for participation were obtained. The CTL group completed an online questionnaire (T1) with the same MCQ questions that are contained within the 20 MSK Short Case Simulations. The CTL group had no exposure to the MSK modules. The EXP Group experienced the intervention of doing the 20 MSK Case Simulations which contained a demographics questionnaire, pre-MCQs (T1); the MSK case module (intervention); post-MCQs and a satisfaction questionnaire. One month after the EXP group completed their MSK modules, both the CTL and EXP group completed a T2 questionnaire with the same 100 MCQs reflecting the same questions in the 20 MSK case simulation modules. A quantitative analysis using paired t-tests comparing the two groups were computed. Satisfaction scores were assessed. Twenty-six residents consented and were randomized for the study (CTL=13; EXP=13). One resident in both the CTL and EXP group withdrew from the study. The EXP group (N=12) completed 218 modules. Additional data was lost due to 2 residents in each group not completing theT1 questionnaires. No significant differences (p=.73) were observed among the two groups thus indicating both CTL and EXP groups to be equal at the start of the study. The EXP group (N=12) completing MSK short case simulations had 2 residents complete some but not all 20 modules. The analysis demonstrated a significant difference in knowledge in the EXP group (p<.04) as demonstrated in the T2 questionnaire. One hundred percent of participants in the EXP group indicated they would recommend 11 of the 20 modules to a colleague for learning. Ninety percent of the participants indicated they would recommend the other 9 MSK modules to a colleague for learning. All EXP group participants were very satisfied with the modules and would do them again. Online interactive MSK case simulations were useful as a learning tool for family medicine residents. Current studies are ongoing to determine patient satisfaction and resident competency in MSK knowledge and skills based on patient experience and faculty observations respectively.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.870

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
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 head0.019
GPT teacher head0.335
Teacher spread0.317 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueOrthopaedic ProceedingsSame topicMusculoskeletal Disorders and RehabilitationFrench-language works237,207