MétaCan
Menu
Back to cohort
Record W4411286870 · doi:10.2337/db25-565-p

565-P: From Knowledge to Practice—Evaluating Diabetes Training for U.S. Physical Therapy Residents

2025· article· en· W4411286870 on OpenAlexaboutno aff
Kathleen Cummer, Mary K. Hastings

Bibliographic record

VenueDiabetes · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiabetes mellitusTraining (meteorology)Physical therapyEndocrinologyGeography

Abstract

fetched live from OpenAlex

Introduction and Objective: Exercise is key in diabetes management, yet patients’ knowledge and absence of exercise specialists may be limiting factors. Physical therapists (PTs), as exercise specialists, should be part of diabetes care. Yet PTs knowledge of diabetes in the US and abroad is limited. The aim of this study was to 1) compare baseline knowledge of US PTs in a residency program to PTs in Canada (CA) and Saudi Arabia (SA), and 2) assess the effect of an education module for US PTs. Methods: Eight participants enrolled in PT residency programs, at two universities, completed pre- and post-training surveys. The surveys have been used to describe PTs knowledge of diabetes in CA and SA. The module was a 2-hour lecture about foundational diabetes and pathophysiology knowledge, the role of PTs, and clinical decision making. Correct responses to knowledge questions were compared across studies, and over time for US PTs. Results: US trained PTs baseline diabetes knowledge varied but was comparable to CA and SA. (Table) Current clinical practice standards were poorer for US PTs compared to CA and SA. (Table) However, after the module, all US diabetes scores improved and were higher than CA and SA scores Conclusion: US PTs diabetes knowledge is comparable to those in CA and SA. However, PTs current clinical practice approach was worse. US PTs knowledge improved after an education module about diabetes. Follow-up is needed to determine if the education module impacted clinical practice. Disclosure K. Cummer: None. M.D. Ferguson: None. D. Quach: None. M. Hastings: None.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.820
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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 head0.037
GPT teacher head0.398
Teacher spread0.360 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueDiabetesSame topicMusculoskeletal Disorders and RehabilitationFrench-language works237,207