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Enregistrement W4205508915 · doi:10.21009/jpud.142.13

Understanding Parental Health Literacy for Clean and Healthy Behavior in Early Childhood During the Covid-19 Pandemic

2020· article· en· W4205508915 sur OpenAlexaboutno aff
Safuri Musa, Sri Nurhayati

Notice bibliographique

RevueJPUD - Jurnal Pendidikan Usia Dini · 2020
Typearticle
Langueen
DomaineMedicine
ThématiquePublic Health and Nutrition
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésRespondentPandemicHealth literacyPsychologyLiteracyClean waterPerceptionDevelopmental psychologyCoronavirus disease 2019 (COVID-19)Health educationEarly childhoodMedicineEnvironmental healthPublic healthNursingHealth carePedagogyPolitical scienceDisease

Résumé

récupéré en direct d'OpenAlex

In the COVID-19 pandemic scenario, parents need to be familiar with health literacy by applying clean and healthy living habits to their family members, especially those with early childhood. This study aims to explain parents' perceptions of health literacy for a clean and healthy behavior in their children during the COVID-19 pandemic. The method used in this study is a cross-sectional study involving 22 men and 62 female respondents. Respondent requirements were used in data analysis to determine parents' perceptions of health literacy and the efforts they have made to practice clean and healthy lifestyle in their children. The research findings show that knowing the health awareness of parents has an impact on a child's balanced lifestyle. Based on six measures of clean and healthy behavior for children, three indicators were determined in the category of discipline and high discipline: using clean water, using the toilet, and doing physical activity. The act of washing children's hands with soap indicators has a high discipline score and the use of masks in children has low discipline. If the use of masks is not disciplined by parents, exposure to COVID-19 in early childhood can be disrupted.
 Keywords: Early Childhood, Parental health literacy, Clean and healthy behaviors
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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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,036
Score d'incertitude au seuil0,691

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,153
Tête enseignante GPT0,387
Écart entre enseignants0,234 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2020
Routes d'admission1
Résumé présentoui

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