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Enregistrement W1965625798 · doi:10.1111/j.1365-2923.2008.03220.x

Team OSCEs: evaluation methodology or educational encounter?

2008· article· en· W1965625798 sur OpenAlexaff
Pippa Hall, Alan Taniguchi

Notice bibliographique

RevueMedical Education · 2008
Typearticle
Langueen
DomaineHealth Professions
ThématiqueInterprofessional Education and Collaboration
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésFormative assessmentCurriculumMedical educationTeamworkContext (archaeology)Health careInterprofessional educationObjective structured clinical examinationMedicinePsychologyProblem-based learningNursingPedagogy

Résumé

récupéré en direct d'OpenAlex

Context and setting Two university faculties of health sciences piloted the team objective structured clinical examination (TOSCE) format in 2006 to interprofessional undergraduate health sciences students. Most of these students were medical students, but the sample included students drawn from social work, chaplaincy, nursing and occupational therapy (OT) curricula. Subsequently, three TOSCE stations have been delivered over a half-day, conducted every 6 weeks, to medical students at one university since January 2007 as part of the mandatory clerkship curriculum. Other health care students participate as an elective. Both interprofessional groups (medical and nursing students, or social work, OT and chaplaincy students) and uniprofessional groups (medical students, who role-play the roles of other team members) have thus participated in the TOSCE experience at this university for over 16 months. Why the idea was necessary Current interest in interprofessional education for collaborative patient-centred practice (IECPCP) raises challenges of defining the competencies necessary for teamwork and how to teach and then evaluate them. There is little medical education literature that directs curriculum designers to evaluation methods or formative educational assessment tools for IECPCP. What was done Stations for the OSCE were created based on clinical scenarios that require a team approach to care (hence ‘team OSCEs’ [TOSCEs]). Stations are 30 minutes in length and teams of five or six students work through scenarios, depicted by a standardised patient (SP) or a video clip, to determine an interprofessional care plan for the patient involved. Students are evaluated on a set of clinical competencies in an area of focus which varies from station to station (e.g. palliative care), and a set of standardised interprofessional competencies that are consistent across each station. Each station has two evaluators; one is an MD faculty member and one is a faculty member from another allied health profession such as nursing, social work, OT or chaplaincy. Each station includes 10 minutes for feedback given by the SP and the evaluators. Evaluation of results and impact Students and evaluators complete extensive surveys at the end of each TOSCE day. Both students (n = 141) and evaluators (n = 38) have reported a high degree of acceptability of the TOSCE, with 81–100% of respondents responding with ‘agree’ or ‘strongly agree’ to a series of acceptability questions. Similarly, the majority of both student and evaluator respondents (79–100%) agreed or strongly agreed that the TOSCE format was quite feasible. Of note, the students felt the 10 minutes of feedback following each station was amongst the most useful learning they had received in their training. Three more TOSCE stations are being introduced to evaluate the reliability and validity of the TOSCE. Student TOSCE scores are being compared with those on multiple-choice question tests and clinical application exercises in the same content areas. Thirty students will complete six TOSCE stations as part of this evaluation, which will include randomisation so that the effect of the group versus the individual can be investigated. The TOSCE holds promise for learners at all levels for a variety of clinical scenarios where both health care content and team-based skills are necessary. At the least, it is a formative educational tool, and current reliability and validity data will determine its effectiveness as an evaluation methodology.

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)0,480
score de la tête « metaresearch » (Gemma)0,522
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,480
Score d'incertitude au seuil0,641

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,4800,522
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0060,007
Études des sciences et des technologies0,0020,005
Communication savante0,0090,005
Science ouverte0,0040,007
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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 Opus0,165
Tête enseignante GPT0,578
Écart entre enseignants0,412 · 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.

Devis d'étudeQualitatif
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

Citations15
Publié2008
Routes d'admission1
Résumé présentoui

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