The contributions of knowledge and trust involving the use of child car seats among Indigenous Peoples in Canada
Notice bibliographique
Résumé
OBJECTIVE: The purpose of the current study was to examine the effects of child vehicle restraint-related knowledge and trust in information on car seat use among Indigenous Peoples in Canada. METHODS: An in-person survey was administered to participants who identified as Indigenous (i.e., First Nation or Métis). Participants included those from the Canadian provinces of Ontario, New Brunswick, Nova Scotia, Alberta, British Columbia, and Quebec. The sample consisted of 536 Indigenous adults, ages 18 and older, who reported having children aged 12 or younger or reported transporting other children in vehicles. The analysis focused on the prediction of consistent car seat use. Logistic regression models were used to test the main predictive effects of gender, living on reserve, levels of child vehicle restraint-related knowledge, and levels of trust in information. An interaction effect of child vehicle restraint-related knowledge by trust in information on consistent car seat use was also tested. RESULTS: Gender did not significantly predict consistent car seat use. However, those who reported living on reserve were 52% less likely to report consistently using car seats than those who reported not living on reserve. Additionally, those who exhibited high levels of child vehicle restraint-related knowledge were two and a half times more likely to report consistent car seat use than those with low knowledge levels. Respondents' level of trust in information was also significantly related to consistent car seat use. Respondents who reported high levels of trust in information were nearly twice as likely to report consistent car seat use than those who reported low levels of trust. Finally, among respondents who demonstrated low knowledge, those who showed high trust in information were nearly two and half times as likely to report consistent car seat use than those who showed low trust. CONCLUSIONS: The current study provided evidence that having the requisite knowledge and trust in information was found to be associated with caregiver compliance in using car seats on a regular basis.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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 | 0,000 |
| 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 ».