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Record W2105301230 · doi:10.1136/vr.102633

Standardised clients as assessors in a veterinary communication OSCE: a reliability and validity study

2014· article· en· W2105301230 on OpenAlexaffabout
Elpida Artemiou, Cindy L. Adams, Kent G. Hecker, Andrea Vallevand, Claudio Violato, Jason B. Coe

Bibliographic record

VenueVeterinary Record · 2014
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of GuelphUniversity of Calgary
FundersZoetis
KeywordsCertificationChecklistObjective structured clinical examinationReliability (semiconductor)Scale (ratio)Rating scaleConstruct validityMedical educationCommunication skillsValidityMedicinePsychologyVeterinary medicinePsychometricsStatisticsMathematicsClinical psychologyGeographyCartography

Abstract

fetched live from OpenAlex

In human medicine, standardised patients (SP) have been shown to reliably and accurately assess learners' communication performance in high-stakes certification Objective Structured Clinical Examinations (OSCE), offering a feasible way to reduce the need for recruitment, time commitment and coordination of faculty assessors. In this study, we evaluated the use of standardised clients (SC) as a viable option for assessing veterinary students' communication performance. We designed a four-station, two-track communication skills OSCE. SC assessors used an adapted nine-item Liverpool Undergraduate Communication Assessment Scale (LUCAS). Faculty used a 21-item checklist derived from the Calgary-Cambridge Guide (CCG) and a five-point global rating scale. Participants were second year veterinary students (n=96). For the four stations, intrastation reliability (α) ranged from 0.63 to 0.82 for the LUCAS, and 0.73 to 0.87 for the CCG. The interstation reliability coefficients were 0.85 for the LUCAS and 0.89 for the CGG. The calculated Generalisability (G) coefficients were 0.62 for the LUCAS and 0.60 for the CGG. Supporting construct validity, SC and faculty assessors showed a significant correlation between the LUCAS and CCG total percent scores (r=0.45, P<0.001), and likewise between the LUCAS and global rating scores (r=0.49, P<0.001).Study results support that SC assessors offer a reliable and valid approach for assessing veterinary communication OSCE.

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)0.002
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 score0.304
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.063
GPT teacher head0.397
Teacher spread0.334 · 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

Citations26
Published2014
Admission routes2
Has abstractyes

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