Adjusting Our Lens: Can Developmental Differences in Diagnostic Reasoning Be Harnessed to Improve Health Professional and Trainee Assessment?
Notice bibliographique
Résumé
OBJECTIVES: Research in cognition has yielded considerable understanding of the diagnostic reasoning process and its evolution during clinical training. This study sought to determine whether or not this literature could be used to improve the assessment of trainees' diagnostic skill by manipulating testing conditions that encourage different modes of reasoning. METHODS: The authors developed an online, vignette-based instrument with two sets of testing instructions. The "first impression" condition encouraged nonanalytic responses while the "directed search" condition prompted structured analytic responses. Subjects encountered six cases under the first impression condition and then six cases under the directed search condition. Each condition had three straightforward (simple) and three ambiguous (complex) cases. Subjects were stratified by clinical experience: novice (third- and fourth-year medical students), intermediate (postgraduate year [PGY] 1 and 2 residents), and experienced (PGY 3 residents and faculty). Two investigators scored the exams independently. Mean diagnostic accuracies were calculated for each group. Differences in diagnostic accuracy and reliability of the examination as a function of the predictor variables were assessed. RESULTS: The examination was completed by 115 subjects. Diagnostic accuracy was significantly associated with the independent variables of case complexity, clinical experience, and testing condition. Overall, mean diagnostic accuracy and the extent to which the test consistently discriminated between subjects (i.e., yielded reliable scores) was higher when participants were given directed search instructions than when they were given first impression instructions. In addition, the pattern of reliability was found to depend on experience: simple cases offered the best reliability for discriminating between novices, complex cases offered the best reliability for discriminating between intermediate residents, and neither type of case discriminated well between experienced practitioners. CONCLUSIONS: These results yield concrete guidance regarding test construction for the purpose of diagnostic skill assessment. The instruction strategy and complexity of cases selected should depend on the experience level and breadth of experience of the subjects one is attempting to assess.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,076 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».