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Record W3209142821 · doi:10.1097/acm.0000000000004280

Incorporating Situational Judgment Tests Into Postgraduate Medical Education Admissions: Examining Educational and Organizational Outcomes

2021· article· en· W3209142821 on OpenAlexaff
Anurag Saxena, Loni Desanghere, Kelly Dore, Harold Reiter

Bibliographic record

VenueAcademic Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMcMaster UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsPsychological interventionCohortDocumentationSituational ethicsSpecialtyDescriptive statisticsPsychologyMedical educationFamily medicineTest (biology)MedicineNursingComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

Purpose: CASPer is an online situational judgment test (SJT) that has been developed for use in medical school admissions, with a separate version developed for admission into specialty training. CASPer was developed to be a broad measure of personal and professional qualities for the entire applicant pool at the time of screening to help bring better quality applicants to interview. The purpose of this project was to examine if using CASPer in the residency selection process impacted the prevalence and type of professionalism issues, formal remediation incidents, and associated cost savings within the college. Methods: Resident in difficulty documentation (type of intervention, CanMEDs areas of difficulty, professionalism issues, and costs) across 4 years before the implementation of CASPer (pre-CASPer cohort) and 4 years post-CASPer implementation (post-CASPer cohort) were reviewed. Descriptive statistics and between-group comparisons were used to explore type of interventions and associated problems. Professionalism issues, as documented in resident files, were categorized into different types of unprofessional behavior based on frameworks proposed by Mak-van der Vossen et al 1 and Hilton and Stolnick. 2 Results: The number of residents identified to be in difficulty during the pre- and post-CASPer time frames were similar (16 and 15 residents, respectively). Likewise, the number of interventions within each cohort were comparable, with 18 interventions documented in the pre-CASPer cohort and 16 interventions documented in the post-CASPer cohort. Despite these similarities, the number of residents requiring formal learning interventions (i.e., remediation or probation) in the pre-CASPer group were significantly higher (P < .05) when compared with the post-CASPer cohort (15 vs 5 respectively). The number of residents requiring informal learning interventions (i.e., enhanced learning plans) that allow the residents to continue the program with additional focused effort in areas that need to be addressed increased from 3 (pre-CASPer cohort) to 11 (post-CASPer cohort). The reduction in formal learning interventions from the pre- to post-CASPer group was associated with a 96% reduction in costs (e.g., salary for additional training, preceptor remunerations, additional assessments to tailor interventions, logistics [vacations, leaves, travel], resident resource office support), from hundreds of thousands to tens of thousands of dollars spent in resources. Within these formal and informal interventions, the medical expert domain was found to be the most frequent role requiring attention in both the pre- (16/16,100%) and post-CASPer cohorts (12/15, 80%). Professionalism issues were identified in 75% of pre-CASPer cases but were found in reduced frequency in the post-CASPer group (40%). Categorization of the professionalism issues showed an overall reduction in professionalism concerns, from pre- to post-CASPer cohorts, across all domains (e.g., involvement, integrity, interaction, introspection, ethical practice, reflection/self-awareness, responsibility/accountability, respect for patients, social responsibility) except teamwork. Discussion: The results of this study suggest that the inclusion of the SJT CASPer in the screening of applicants to postgraduate medical training provides important information that can result in a reduction in the number of formal interventions and number of professionalism concerns among selected residents, subsequently reducing associated costs as well as faculty and staff time. Significance: In addition to the immediate benefits of integrating SJTs in the applicant selection process, the cost savings associated with reduced formal interventions can be redirected to enhancing institutional endeavors (e.g., Competence by Design launch) and improving programs (e.g., additional funding for courses and well-being work). Acknowledgments: The National Board of Medical Examiners Stemmler Fund for their original support of CASPer creation.

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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)0.005
metaresearch head score (Gemma)0.025
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.384
Teacher spread0.347 · 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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Citations6
Published2021
Admission routes1
Has abstractyes

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