Preparing for Potential Health and Safety Risks at the Olympic Games: Scoping Review
Notice bibliographique
Résumé
Background: The Olympic Games are an example of a mass gathering that involves a complex and large crowd composition, with a large number of illnesses and injuries occurring at previous Olympic Games, and the Olympic Games also becoming a target for terrorist attacks. Objective: With the help of mass-gathering medicine as a guide, this study aims to critically summarize and analyze the state of illness, injury, and terrorism during the Olympic Games in order to reduce the incidence of illnesses and injuries in crowds and to offer lessons for the organization of major international sporting events such as the Olympics. Methods: The procedure for this scoping review followed the 5-step methodological framework of Arksey and O'Malley. We searched electronic databases such as PubMed, Web of Science, and Scopus. We extracted, summarized, and categorized general information on each study, game characteristics, illness and injury profiles, terrorism characteristics, preventive measures, and surveillance paradigms. Results: We conducted a database search and retrieved a total of 9587 studies on 2 occasions. After removing duplicates and screening, we included 120 studies. Only 12 studies on the Summer, Winter, and Paralympic Games published before 2000, and 108 studies from 2000 onward, comprise the 120 studies, marking an unprecedented number of studies in this field of research, particularly in recent times. Of the 120 studies, 80 were illness-related, 81 were injury-related, and 2 were terrorism-related. Nine studies explicitly assessed body parts, including shoulders, feet, and dentistry; 26 studies specifically investigated certain illnesses and injuries, such as COVID-19 disease, heat-related illnesses, and concussions. Of the 120 research studies, 18 specifically analyzed sports such as gymnastics and weight lifting, with 11 studies focusing especially on COVID-19 disease. The most studied games were the Tokyo 2021 Olympic or Paralympic Games, the London 2012 Olympic or Paralympic Games, and the Rio 2016 Olympic or Paralympic Games. The system of injury and illness surveillance in the Olympic Games goes through 3 stages of development: the first trial of information technology, the construction of networks, and the enhancement of intelligence. Conclusions: A critical summary of studies of illness, injury, and terrorist attacks at previous Olympic Games is important for injury and terrorism prevention at major sporting events such as the Olympic Games. Surveillance methods require improvements in surveillance technology, data sharing, and privacy protection.
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 | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,005 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 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 ».