Bibliometric Analysis of Emergency Medicine in Disasters: 2004-2023
Notice bibliographique
Résumé
Objective: This study aims to conduct a bibliometric analysis of research on "emergency medicine in disasters" published between 2004 and 2023, highlighting the scientific developments, key themes, and research gaps in this growing field.With the increasing frequency of disasters due to factors like climate change, urbanization, and population growth, the importance of disaster emergency medicine has become more critical.While technological advancements have improved emergency medical responses, research shows that further development is needed.This analysis seeks to evaluate global trends and collaborations in disaster medicine research to provide a strategic roadmap for future studies and enhance the preparedness and effectiveness of health systems in responding to disasters. Methods:A bibliometric review of 1,532 articles published between January 1, 2004 and December 31, 2023, was conducted using the Web of Science Core Collection database.The analysis focused on articles published in peer-reviewed journals, limited to the "emergency medicine" field, written in English, and meeting the defined timeframe.The selected articles were examined based on publication trends, citation counts, journal distribution, most-cited authors, and collaborative networks between institutions and countries.Tools such as keyword networks, bibliographic coupling, co-authorship analysis, and citation mapping were used to visualize research collaborations and thematic focus areas.VOSviewer software was employed to map research collaborations and identify the most influential studies in disaster medicine.Results: The study's findings reveal a significant increase in research output, particularly following global crises such as coronavirus disease-2019 (COVID-19).Countries like the United States of America (USA), Canada, the United Kingdom, and China lead in both publications and international collaborations, demonstrating strong partnerships in disaster medicine research.Institutions such as Harvard University and Johns Hopkins University stand out for their high productivity and impact, with highly cited articles focusing on disaster-related health impacts, triage, and the mental health of responders.Key research themes include disaster preparedness, emergency medical services, and global health crises, underscoring the growing importance of international collaboration in advancing disaster medicine. Conclusion:The bibliometric analysis of research on "emergency medicine in disasters" from 2004 to 2023 demonstrates a substantial increase in scientific output, especially following the COVID-19 pandemic.Key findings highlight the central role of journals like Prehospital and Disaster Medicine and the influential contributions of institutions such as Harvard University and Johns Hopkins University.Frequently cited articles focus on disaster health impacts, triage, and mental health support for healthcare workers, reflecting the critical importance of preparedness and response strategies.International collaborations, particularly among countries like the USA, Sweden, Iran, and Turkey, have expanded, underlining the growing global significance of disaster medicine.These results underscore the vital role that disaster emergency medicine plays in strengthening global health systems and the increasing academic focus on this field.
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 | 0,021 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,087 | 0,178 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 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 ».