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Record W2224777402 · doi:10.1186/s12909-015-0506-z

How to set the bar in competency-based medical education: standard setting after an Objective Structured Clinical Examination (OSCE)

2016· article· en· W2224777402 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMC Medical Education · 2016
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsSunnybrook Health Science CentreHealth Sciences CentreMount Sinai HospitalThe Wilson CentreToronto East General HospitalWomen's College Hospital
Fundersnot available
KeywordsObjective structured clinical examinationMedical educationEducational measurementSet (abstract data type)MedicinePsychologyMEDLINECurriculumComputer sciencePedagogy

Abstract

fetched live from OpenAlex

BACKGROUND: The goal of the Objective Structured Clinical Examination (OSCE) in Competency-based Medical Education (CBME) is to establish a minimal level of competence. The purpose of this study was to 1) to determine the credibility and acceptability of the modified Angoff method of standard setting in the setting of CBME, using the Borderline Group (BG) method and the Borderline Regression (BLR) method as a reference standard; 2) to determine if it is feasible to set different standards for junior and senior residents, and 3) to determine the desired characteristics of the judges applying the modified Angoff method. METHODS: The results of a previous OSCE study (21 junior residents, 18 senior residents, and six fellows) were used. Three groups of judges performed the modified Angoff method for both junior and senior residents: 1) sports medicine surgeons, 2) non-sports medicine orthopedic surgeons, and 3) sports fellows. Judges defined a borderline resident as a resident performing at a level between competent and a novice at each station. For each checklist item, the judges answered yes or no for "will the borderline/advanced beginner examinee respond correctly to this item?" The pass mark was calculated by averaging the scores. This pass mark was compared to that created using both the BG and the BLR methods. RESULTS: A paired t-test showed that all examiner groups expected senior residents to get significantly higher percentage of checklist items correct compared to junior residents (all stations p < 0.001). There were no significant differences due to judge type. For senior residents, there were no significant differences between the cut scores determined by the modified Angoff method and the BG/BLR method. For junior residents, the cut scores determined by the modified Angoff method were lower than the cut scores determined by the BG/BLR Method (all p < 0.01). CONCLUSION: The results of this study show that the modified Angoff method is an acceptable method of setting different pass marks for senior and junior residents. The use of this method enables both senior and junior residents to sit the same OSCE, preferable in the regular assessment environment of CBME.

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.

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)0.006
metaresearch head score (Gemma)0.067
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.067
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.018
GPT teacher head0.384
Teacher spread0.366 · 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