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Record W2891744337 · doi:10.1186/s12909-018-1326-8

Point of care ultrasound training for internal medicine: a Canadian multi-centre learner needs assessment study

2018· article· en· W2891744337 on OpenAlexafffundabout
Kathryn Watson, Ada Lam, Shane Arishenkoff, Samantha Halman, Neil E. Gibson, Jeffrey Yu, Kathryn Myers, Marcy Mintz, Irene Ma

Bibliographic record

VenueBMC Medical Education · 2018
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsWestern UniversityUniversity of OttawaUniversity of British ColumbiaUniversity of AlbertaUniversity of Calgary
FundersUniversity of Ottawa
KeywordsMedicinePoint of care ultrasoundCurriculumLikert scaleInternal medicineMedical educationScale (ratio)Family medicineRadiologyUltrasoundPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Significant gaps currently exist in the Canadian internal medicine point-of-care ultrasound (POCUS) curriculum. From a learner's perspective, it remains unknown what key POCUS skills should be prioritized. This needs assessment study seeks to establish educational priorities for POCUS for internal medicine residents at five Canadian residency training programs. METHODS: All internal medicine trainees [postgraduate year (PGY) 1-5] from five internal medicine residency training programs in Canada (n = 598) were invited to complete an online survey on 15 diagnostic POCUS applications, 9 bedside procedures, and 18 POCUS knowledge items. For POCUS applications and procedures, participants were asked how applicable they are to patient care in internal medicine and the participants' reported skills in those domains. Self-reported knowledge and skills were rated on a 5-point Likert scale, where 1 = very poor and 5 = very good. Applicability was rated, where 1 = not at all applicable and 5 = very applicable. RESULTS: A total of 253 of 598 residents (42%) participated in our study. Data from one centre (n = 15) was removed because of low response rate (15%) and significant baseline differences between those trainees and the remaining participants. Of the remaining analyzable data from four training programs (n = 238), participants reported highest applicability to internal medicine for the following applications and procedures: identifying ascites/free fluid [mean applicability score of 4.9 ± standard deviation (SD) 0.4]; gross left ventricular function (mean 4.8 ± SD 0.5) and pericardial effusion (mean 4.7 ± SD 0.5); thoracentesis (mean score 4.9 ± SD 0.3), central line insertion (mean 4.9 ± SD 0.3), and paracentesis (mean 4.9 ± SD 0.3), respectively. Overall reported knowledge/skills was low, with skill gaps being the highest for identifying deep vein thrombosis (mean gap 2.7 ± SD 1.1), right ventricular strain (mean 2.7 ± SD 1.1), and gross left ventricular function (mean 2.7 ± SD 1.0). CONCLUSIONS: Many POCUS applications and procedures were felt to be applicable to the practice of internal medicine. Significant skill gaps exist in the four Canadian training programs included in the study. POCUS curriculum development efforts should target training based on these perceived skill gaps.

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)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.012
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)0.0030.000

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 head0.073
GPT teacher head0.441
Teacher spread0.368 · 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

Citations50
Published2018
Admission routes3
Has abstractyes

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