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Enregistrement W3209142821 · doi:10.1097/acm.0000000000004280

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

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

Notice bibliographique

RevueAcademic Medicine · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueInnovations in Medical Education
Établissements canadiensMcMaster UniversityUniversity of Saskatchewan
Organismes subventionnairesnon disponible
Mots-clésPsychological interventionCohortDocumentationSituational ethicsSpecialtyDescriptive statisticsPsychologyMedical educationFamily medicineTest (biology)MedicineNursingComputer scienceSocial psychology

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,025
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,007
Score d'incertitude au seuil0,027

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,025
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,002
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,037
Tête enseignante GPT0,384
Écart entre enseignants0,347 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations6
Publié2021
Routes d'admission1
Résumé présentoui

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