Implementation of a Novel Epidemiological Surveillance System for Children’s Mental Health and Well-Being in France: Protocol for the National “Enabee” Cross-Sectional Study
Notice bibliographique
Résumé
BACKGROUND: Children's mental health, including their well-being, is a major public health concern, as the burden of related disorders may last throughout one's life. Although epidemiological mental health surveillance systems for children and adolescents have been implemented in several countries, they are sorely lacking in France. OBJECTIVE: This study aims to describe the first step of the implementation of a novel surveillance system in France called Enabee (Etude nationale sur le bien-être des enfants), which focuses on the issue of mental health in children. The system aims to (1) describe the temporal trends in the population-based prevalence of the main mental health disorders and well-being in children aged 3 to 11 years, (2) explore their major determinants, and (3) assess mental health care use by this population. To do this, Enabee will rely on results from a recurrent national cross-sectional homonymous study. This paper presents the protocol for the first edition of this study (called Enabee 2022), as well as initial results regarding participation. METHODS: Enabee 2022 is a national cross-sectional study that was implemented in French schools in 2022. It used a probabilistic, multistage, stratified, and balanced sampling plan as follows: first, schools were randomly drawn and stratified according to the type of school. Up to 4 classes per school were then randomly drawn, and finally, all the pupils within each class were selected. The study covered children from preschool and kindergarten (aged 3 to 6 years, US grading system) to fifth grade (aged 6 to 11 years). Children from first to fifth grades provided a self-assessment of their mental health using 2 validated self-administered questionnaires: the Dominic Interactive (DI) and the KINDL. Parents and teachers completed a web-based questionnaire, including the Strengths and Difficulties Questionnaire. Parents also answered additional questions about their parenting attitudes; their own mental health; known social, economic, and environmental determinants of mental health in children; and their child's life habits. Health, education, and family stakeholders were involved in designing and implementing the study as part of a large consultation group. RESULTS: Data were collected from May 2, 2022, to July 31, 2022, in 399 schools across metropolitan France. Teachers completed questionnaires for 5721 pupils in preschool and kindergarten and for 15,263 pupils from first to fifth grades. Parents completed questionnaires for 3785 children in preschool and kindergarten and for 9227 children from first to fifth grades. Finally, 15,206 children from first to fifth grades completed the self-administered questionnaire. CONCLUSIONS: Enabee 2022 constitutes the first milestone in the development of a novel national epidemiological surveillance system, paving the way for improved children's mental health policies in France.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,054 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,003 |
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 source (Gemma direct ou Codex distillé), 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 ».