Trends in neurology medical education: a bibliometric analysis (2000–2023)
Notice bibliographique
Résumé
Background The development of neurology closely correlates with improvements in medical education, which provides essential knowledge and skills to tackle the growing global challenge of neurological disorders. This study aimed to perform a bibliometric analysis to assess the key areas and trends concerning the interface between neurology and medical education for the period spanning from 2000 to 2023. Objective This study aimed to perform a bibliometric analysis to assess the key areas and trends concerning the interface between neurology and medical education for the period spanning from 2000 to 2023. Methods We gathered articles from the Web of Science Core Collection database and employed two bibliometric tools, CiteSpace and VOSviewer, to evaluate and quantify various impact and collaboration metrics. Our analysis included annual publication data, journals, co-cited journals, countries/regions, institutions, authors, and co-cited authors. Furthermore, we identified emerging research areas linked to neurology and medical education by investigating the co-occurrence and bursts of keywords and co-cited references. Results From 2000 to 2023, a total of 900 articles investigating the correlation between neurology and medical education were published in 297 academic journals. These articles were authored by 4,399 researchers from 893 institutions across 92 countries/regions. The United States, England, and Canada emerged as the leading countries in this field, with the United States maintaining a dominant position. Harvard University was identified as the most productive institution. Gilbert Donald L emerged as the top author, while Jozefowicz Rf recorded the highest number of co-citations. The journal Neurology was not only the most prolific in publishing articles at the intersection of neurology and medical education but was also the journal that received the most co-citations. The main themes of these articles centered around psychology, education, social health, nursing, and medicine, with keywords frequently relating to education, students, and neurological disorders. Conclusion Neurophobia within neurology medical education remains a significant area of research, contributing to a deeper understanding of the relationship between neurology and medical training. Emerging areas such as resident education, medical education training, developmental neurology, and parental involvement may offer valuable guidance and new insights for further research in the field of neurology education.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,124 | 0,199 |
| 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) | 0,001 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».