Determinants of unintentional injuries in preschool age children in high‐income countries: A systematic review
Notice bibliographique
Résumé
BACKGROUND: Injuries are the leading cause of death and disability in preschool children who are subject to specific risk factors. We sought to clarify the determinants of unintentional injuries in children aged 5 years and under in high-income countries and report on the methodological quality of the selected studies. METHODS: A systematic review was conducted of observational studies investigating determinants of unintentional injury in children aged 0-5. Searches were conducted in Web of Science, Medline, Embase, PsycInfo and CINAHL. All methods of data analysis and reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2021) guidelines. Determinants are reported at the child, parental, household and area level. RESULTS: An initial search revealed 6179 records. Nineteen studies met the inclusion criteria: 17 cohort studies and 2 case control studies. While studies included longitudinal surveys and administrative healthcare data analysis, the highest quality studies examined were case-control designs. Child factors associated with unintentional injury include male gender, age of the child at the time of injury, advanced gross motor score, sleeping problems, birth order, attention deficit hyperactivity disorder (ADHD) diagnosis and below average score on the standard strengths and difficulties scale. Parental factors associated with unintentional injuries included younger parenthood, poor maternal mental health, hazardous or harmful drinking by an adult within the home, substance misuse, low maternal education, low paternal involvement in childcare and routine and manual socioeconomic classification. Household factors associated with injury were social rented accommodation, single-parent household, White ethnicity in the United Kingdom, number of children in the home and parental perception of a disorganised home environment. Area-level factors associated with injury were area-level deprivation and geographic remoteness. CONCLUSION: Child factors were the strongest risk factors for injury, whereas parental factors were the most consistent. Further research is needed to examine the role of supervision in the relationships between these risk factors and injury. Injury intent should be considered in studies using administrative healthcare data. Prospective research may consider utilising linked survey and administrative data to counter the inherent weaknesses of these research approaches.
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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,004 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| 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) | 0,000 | 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 ».