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Simulation Testing for Selection of Critical Care Medicine Trainees. A Pilot Feasibility Study

2016· article· en· W2294322526 on OpenAlexaboutno aff
Adriano G. Cocciante, Martin N. Nguyen, Candida F. Marane, Anita Panayiotou, Amalia Karahalios, Janet A. Beer, Navroop Johal, John Morris, Stacy Turner, Elizabeth Hessian

Bibliographic record

VenueAnnals of the American Thoracic Society · 2016
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsDebriefingMedicineConcordancePersonalityInter-rater reliabilityRanking (information retrieval)Big Five personality traitsTest (biology)Medical educationClinical psychologyFamily medicinePsychologyRating scaleSocial psychology

Abstract

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RATIONALE: Selection of physicians into anesthesiology, intensive care, and emergency medicine training has traditionally relied on evaluation of curriculum vitae, letters of recommendation, and interviews, despite these methods being poor predictors of subsequent workplace performance. OBJECTIVES: In this study, we evaluated the feasibility and face validity of incorporating assessment of nontechnical skills in simulation and personality traits into an existing junior doctor selection framework. METHODS: Candidates short-listed for a critical care residency position were invited to participate in the study. On the interview day, consenting candidates participated in a simulation scenario and debriefing and completed a personality test (16 Personality Factor Questionnaire) and a survey. Timing of participants' progression through the stations and faculty staff numbers were evaluated. Nontechnical skills were evaluated and candidates ranked using the Ottawa Crisis Resource Management Global Rating Scale (Ottawa GRS). Nontechnical skills ranking and traditional selection method ranking were compared using the concordance correlation coefficient. Interrater reliability was assessed using the concordance correlation coefficient. MEASUREMENTS AND MAIN RESULTS: Thirteen of 20 eligible participants consented to study inclusion. All participants completed the necessary stations without significant time delays. Eighteen staff members were required to conduct interviews, simulation, debriefing, and personality testing. Participants rated the simulation station to be acceptable, fair, and relevant and as providing an opportunity to demonstrate abilities. Personality testing was rated less fair, less relevant, and less acceptable, and as giving less opportunity to demonstrate abilities. Participants reported that simulation was equally as stressful as the interview, whereas personality testing was rated less stressful. Assessors rated both personality testing and simulation as acceptable and able to provide additional information about candidates. The Ottawa GRS showed moderate interrater concordance. There was moderate concordance between rankings based on traditional selection methods and Ottawa GRS rankings (ρ = 0.52; 95% confidence interval, -0.02 to 0.82; P = 0.06). CONCLUSIONS: A multistation selection process involving interviews, simulation, and personality testing is feasible and has face validity. A potential barrier to adoption is the high number of faculty required to conduct the process.

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)0.006
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 score0.023
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
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 science0.0000.000
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 head0.380
GPT teacher head0.553
Teacher spread0.174 · 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

Citations17
Published2016
Admission routes1
Has abstractyes

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