A bibliometric analysis of health-related literature on natural disasters from 1900 to 2017
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
BACKGROUND: Worldwide, natural disasters have caused a large number of deaths and considerable morbidity. Nevertheless, limited information is available on how the health-related literature on natural disasters has evolved. The current study aims to assess the growth and pattern of health-related literature on natural disasters. METHOD: A bibliometric method was implemented using Scopus database for the period from 1900 to 2017. Keywords used in the search strategy were obtained from the classifications of natural disasters presented by the Centre for Research on the Epidemiology of Disasters. The health component was determined by selecting the health-related subject areas in Scopus. RESULTS: In total, 9073 documents were retrieved. The annual number of publications showed a noticeable sharp increase after 2004. The retrieved documents received 97,605 citations, an average of 10.8 per document. The h-index of the retrieved documents was 113. Author keywords with the highest occurrence were 'earthquakes' followed by 'disaster medicine', 'disaster planning', 'tsunami', 'mental health', 'disaster preparedness', 'PTSD', 'emergency preparedness', and 'public health'. Authors from the United States of America contributed to 3127 (34.5%) publications and ranked first, followed by those from Japan (700; 7.7%) and China (636; 7.0%). When research output was standardised by Gross Domestic Product per capita, India ranked first, followed by China and the United States. The United Kingdom had the highest percentage of documents with international authors, followed by those from Switzerland and Canada. The Prehospital and Disaster Medicine journal published the most articles (636; 7.0%). The Sichuan University and its affiliated hospital contributed to 384 (7.0%) documents and ranked first in the field. CONCLUSION: The current baseline information on health-related literature on natural disasters showed that this field is growing rapidly but with inadequate international research collaboration. Research collaboration in this field needs to be strengthened to improve the global response to natural disasters in any place in the world. There is a need to expand the research focus in this field to include communicable and non-communicable diseases. Finally, the health effects of other natural disasters, such as floods, droughts and disease outbreaks, need to be addressed.
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.
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 | 0,009 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,090 | 0,115 |
| Études des sciences et des technologies | 0,001 | 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 découle