A scoping review of female drowning: an underexplored issue in five high-income countries
Notice bibliographique
Résumé
BACKGROUND: Drowning is a significant public health issue, with females accounting for one third of global drowning deaths. The rate of female drowning has not decreased within high-income countries and presentations to hospital have increased. This scoping review aimed to explore adult female unintentional drowning, including risk factors, clinical treatment and outcomes of females hospitalised for drowning. METHODS: A systematic search of the literature following the PRISMA-ScR framework was undertaken. The databases OVID MEDLINE, Embase, CINAHL, OVID Emcare, Web of Science, Informit and Scopus were accessed. Study locations of focus were Australia, Canada, New Zealand, the United Kingdom, and the United States. Studies from January 2003 to April 2019 were included. The quality of evidence of included studies was assessed using GRADE guidelines. RESULTS: The final search results included 14 studies from Australia (n = 4), Canada (n = 1), New Zealand (n = 1), United States (n = 6), United Kingdom (n = 1), and one study reporting data from both Australia and United States. Nine studies reported risk factors for female drowning including age, with the proportion of female drowning incidence increasing with age. Although females are now engaging in risk-taking behaviours associated with drowning that are similar to males, such as consuming alcohol and swimming in unsafe locations, their exposure to risky situations and ways they assess risk, differ. Females are more likely to drown from accidental entry into water, such as in a vehicle during a flood or fall into water. This review found no evidence on the clinical treatment provided to females in hospital after a drowning incident, and only a small number of studies reported the clinical outcomes of females, with inconsistent results (some studies reported better and some no difference in clinical outcomes among females). CONCLUSION: Adult females are a group vulnerable to drowning, that have lacked attention. There was no single study found which focused solely on female drowning. There is a need for further research to explore female risk factors, the clinical treatment and outcomes of females hospitalised for drowning. This will not only save the lives of females, but also contribute to an overall reduction in drowning.
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 | 0,010 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,005 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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; 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 ».