Medical faculty as humanistic physicians and teachers: the perceptions of students at innovative and traditional medical schools
Notice bibliographique
Résumé
BACKGROUND AND OBJECTIVES: The training of caring physicians represents an important goal of medical education. Little is known however, on whether medical faculty constitute good role models for teaching humanistic skills to medical students. In this study, we examined to what extent medical students at innovative and traditional schools perceived their teachers as humanistic physicians and teachers. We also explored whether pre-clinical and clinical students shared the same perceptions. METHODS: A mail survey was conducted in Canada of all second-year students and senior clerks at one innovative medical school (problem-based learning (PBL), patient-centred, community-oriented) and three traditional medical schools. Students were asked to what extent they agreed or disagreed that the majority of their teachers behaved as humanistic physicians and teachers; 10 statements were used. Overall, 65% of the 1039 students returned the questionnaire. RESULTS: Over 25% of second-year students and 40% of senior clerks did not agree that their teachers behaved as humanistic caregivers with patients or were good role models in teaching the doctor-patient relationship. More than half of second-year students and senior clerks did not agree that their teachers valued human contact with them or were supportive of students who had difficulties. There were few differences in the way medical students at innovative and traditional schools perceived their teachers' humanistic qualities. At the pre-clinical level however, there were more students from the innovative school than from the traditional schools (around 60% vs. 40%, P < 0.005) who agreed that their teachers valued human contact with them and were supportive of students. CONCLUSION: Our results indicate that the PBL curriculum fosters better teacher-student relationships during the pre-clinical years. They also suggest that an unacceptably large number of medical students are taught by physicians who seem to lack compassion and caring in their interactions with patients. This study questions the adequacy of medical faculty as role models for the acquisition of caring competence by medical students.
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 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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) | 0,026 | 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 ».