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Record W3123772788 · doi:10.1097/acm.0000000000003841

A Communication-Based Assessment Station as an Alternative to the OSCE

2021· article· en· W3123772788 on OpenAlexaff
Vijay K. Sandhu, Carla Garcia, Raed Hawa, Andrea Waddell

Bibliographic record

VenueAcademic Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsCentre for Addiction and Mental HealthUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsObjective structured clinical examinationCronbach's alphaPsychologyMedical educationTest (biology)Educational measurementMedicineFamily medicineClinical psychologyPsychometricsCurriculum

Abstract

fetched live from OpenAlex

To the Editor: The objective structured clinical examination (OSCE) is the gold standard in clinical performance examination, but its administration is expensive, requiring training of standardized patients and evaluators. 1 With recent centralization of clinical performance assessment at our institution into a high-stakes “integrated OSCE,” the Department of Psychiatry modified its psychiatry-specific examination by replacing two OSCE stations with a communicator skills assessment (ComSA) station. In ComSA stations, the examiner role-plays scenarios such as answering a family member’s questions or consulting an allied health professional. The ComSA station appears to be a favorable option, given its lower cost and logistical simplicity. Yet, literature on examiner roleplay in performance-based assessments is limited. 2 In 2014, we sought evidence for our department’s use of a ComSA station in place of an OSCE station. Using 3 random iterations of our revised psychiatry clerkship examination, we examined 126 examinees’ scores on four examination components: process scores (communication skills), content scores (station-specific knowledge), post-encounter probe (PEP) for OSCE stations, and the psychiatry written examination. We conducted a paired-samples test of equivalence to assess whether performance on ComSA stations was equivalent to that on OSCE stations. Our findings demonstrate that the performances on the knowledge domains (content scores, PEPs, and the written exam) are equivalent. The process domains on the ComSA and OSCE are also equivalent; however, the ComSA process score and the written examination score are not equivalent measurements. Using Cronbach’s alpha omitted-variable analysis, we determined the impact of the replacement on overall examination performance. 3 The internal consistency of two OSCE stations and one ComSA station was similar to and often higher than that of three OSCE stations. This finding strongly suggests that a ComSA station can replace an OSCE station without adversely impacting the exam’s internal reliability. Overall, our results demonstrate that our ComSA station and OSCE stations assessed learner performance similarly and that the former can be integrated into an exam without decreasing the exam’s validity. Study limitations include possible curricular variations between iterations. Furthermore, the equivalence of the ComSA station to OSCE stations and the former’s acceptability in other specialities, such as surgery, should be examined. The realities of medical education require that we consider not only a method’s rigor but also its feasibility and sustainability. Our findings are promising, as they suggest that lower-cost alternatives can be validated and easily implemented into existing assessment frameworks without reducing assessment quality. Acknowledgments: The authors would like to thank Tammy Mok for her assistance in data extraction.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.101
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.101
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0100.002

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 head0.060
GPT teacher head0.462
Teacher spread0.402 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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