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Record W4304811961 · doi:10.1186/s12909-022-03746-4

Impact of interactive multi-media learning for physicians in musculoskeletal education – a pilot study

2022· article· en· W4304811961 on OpenAlexafffundabout
Veronica Wadey, Tosan Okoro, Thrmiga Sathiyamoorthy, David A. Snowdon, Heather McDonald-Blumer, Alfred Cividino, Deborah Kopansky-Giles, David M. Levy, Risa Freeman, Jodi Herold, Douglas Archibald

Bibliographic record

VenueBMC Medical Education · 2022
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsUniversity of OttawaCanada Research ChairsCanadian Memorial Chiropractic CollegeMcMaster UniversityUniversity of Toronto
FundersUniversity of TorontoCanadian Rheumatology Association
KeywordsMedicineCurriculumRandomized controlled trialPhysical therapyRepeated measures designRandomizationMedical educationInternal medicinePsychology

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this educational study was to investigate the use of interactive case-based modules relating to the screening and identification of early-stage inflammatory arthritis in both online technology (OLT) and paper (PF) formats with identical content. METHODS: Forty learners from family medicine or rheumatology residency programs were recruited. Content pertaining to a "Sore Hands, Sore Feet" (SHSF) and Gait Arms Legs Spine (GALS) screening tool modules were selected, reviewed and developed based on a validated curriculum from the World Health Organization and Canadian Curriculum for MSK conditions. Both the SHSF module and GALS screening tool were assessed via a randomized control trial. Assessments were completed during an orientation with all learners; then prior to the intervention (T1); at the end of the module (T2) and 3 months following the modules (T3) to assess retention. Focus groups were conducted to determine learners' satisfaction with the different learning formats. Baseline data was collated, and analysis performed after randomization into the PF (control) and OLT (experimental) groups. Repeated measures ANOVA was used for statistical analyses. RESULTS: Forty participants were recruited and randomized into the PF or OLT group (n = 20 each). At 3 months, there were n = 31 participants for SHSF (PF n = 19, OLT n = 12) and n = 32 for GALS (PF n = 19, OLT n = 13). There was no significant difference between the OLT and PF groups in both analyses. A significant increase in scores from Pre- to Post-Module in SHSF (F (1, 18) = 24.62. p < .0001) and GALS (F (1, 30) = 40.08, p < .0001) were identified to suggest learning occurred with both formats. The repeated measures ANOVA to assess retention revealed a significant decrease in scores from Post-Module to Follow-up for both learning format groups for SHSF (F (1, 29) = 4.68. p = .039), and GALS (F (1, 30) = 18.27. p < .0001) suggesting 3 months may be too long to retain this educational information. CONCLUSIONS: Both formats led to residents' ability to screen, identify and initially manage inflammatory arthritis. The hypothesis is rejected because both OLT and PF groups demonstrated significant learning during the process regardless of format. It is important to emphasize that from T1 (pre-module) to T2 (post-module), the residents demonstrated learning regardless of group to which they were assigned. However, learning retention declined from T2 (post-module) to T3 (three-month follow-up). Regular review of knowledge may be required earlier than 3 months to retain information learned. This study may impact educational strategies in MSK health. TRIAL REGISTRATION: This study did not involve "patients" rather learners and as such it was not registered.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
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)0.0010.000

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 head0.022
GPT teacher head0.394
Teacher spread0.373 · 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 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

Citations2
Published2022
Admission routes3
Has abstractyes

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