Assessing the quality of feedback to general internal medicine residents in a competency-based environment.
Notice bibliographique
Résumé
CONSTRUCT: Competency Based Medical Education (CBME) is designed to use workplace-based assessment (WBA) tools to provide observed assessment and feedback on resident competence. Moreover, WBAs are expected to provide evidence beyond that of more traditional mid- or end-of-rotation assessments [e.g., In Training Evaluation Reports (ITERs)]. In this study, we investigated the quality of feedback in General Internal Medicine (GIM), by comparing WBA and ITER assessment tools. BACKGROUND: WBAs are hypothesized to improve written and numerical feedback to support the development and documentation of competence. In this study, we investigated residents' and preceptors' perceptions of WBA validity, usability, and reliability and the extent to which WBAs differentiate residents' performance when compared to ITERs. APPROACH: We used a mixed methods approach over a three-year period, including perspectives gathered from focus groups, interviews, along with numerical and narrative comparisons between WBA and ITERs in one GIM program. RESULTS: Our quantitative analysis of feedback from seven residents' clinical assessments showed that overall rates of actionable feedback, for both ITERs and WBAs, were low (26%), with only 9% of the total providing an improvement strategy. The provision of quality feedback was not significantly different between tools; although WBAs provided more actionable feedback, ITERs provided more strategies. We found that residents and preceptors indicated the narrative component of feedback was more constructive and effective than numerical scores. Both groups perceived the focus on specific workplace-based feedback was more effective than ITERs. CONCLUSIONS: Participants in this study viewed narrative, actionable, and specific feedback as essential, and an overall preference was found for written feedback over numerical assessments. However, our quantitative analyses showed that specific actionable feedback was rarely documented, despite finding an emphasis from both residents and preceptors of its importance for developing competency. Neither formative WBAs nor summative ITERs clearly provided better feedback, and both may still have a role in overall resident evaluation. Participant views differed in roles and responsibilities, with residents stating that preceptors should be responsible for initiating assessments and vice-versa. These results reveal an incongruence between resident and preceptor perceptions and practice around giving feedback and emphasize opportunities for programs adopting and implementing CBME to address how best to support residents and frontline clinical teachers.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,030 | 0,143 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».