Effectiveness of a Parent-Based eHealth Intervention for Physical Activity, Dietary Behavior, and Sleep Among Preschoolers: Protocol for a Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Preschoolers' lifestyles have become physically inactive and sedentary, their eating habits have become unhealthy, and their sleep routines have become increasingly disturbed. Parent-based interventions have shown promise to improve physical activity (PA), improve dietary behavior (DB), and reduce sleep problems among preschoolers. However, because of the recognized obstacles of face-to-face approaches (eg, travel costs and time commitment), easy access and lower costs make eHealth interventions appealing. Previous studies that examined the effectiveness of parent-based eHealth for preschoolers' PA, DB, and sleep have either emphasized 1 variable or failed to balance PA, DB, and sleep modules and consider the intervention sequence during the intervention period. There is an acknowledged gap in parent-based eHealth interventions that target preschoolers raised in Chinese cultural contexts. OBJECTIVE: This study aims to investigate the effectiveness of a parent-based eHealth intervention for PA, DB, and sleep problems among Chinese preschoolers. METHODS: This 2-arm, parallel, randomized controlled trial comprises a 12-week intervention with a 12-week follow-up. A total of 206 parent-child dyads will be randomized to either an eHealth intervention group or a control group. Participants allocated to the eHealth intervention group will receive 12 interactive modules on PA, DB, and sleep, with each module delivered on a weekly basis to reduce the sequence effect on variable outcomes. The intervention is grounded in social cognitive theory. It will be delivered through social media, where parents can obtain valid and updated educational information, have a social rapport, and interact with other group members and facilitators. Participants in the control group will receive weekly brochures on PA, DB, and sleep recommendations from kindergarten teachers, but they will not receive any interactive components. Data will be collected at baseline, 3 months, and 6 months. The primary outcome will be preschoolers' PA. The secondary outcomes will be preschoolers' DB, preschoolers' sleep duration, preschoolers' sleep problems, parents' PA, parenting style, and parental feeding style. RESULTS: Parent-child dyads were recruited in September 2023. Baseline and posttest data collection occurred from October 2023 to March 2024. The follow-up data will be obtained in June 2024. The results of the study are expected to be published in 2025. CONCLUSIONS: The parent-based eHealth intervention has the potential to overcome the barriers of face-to-face interventions and will offer a novel approach for promoting a healthy lifestyle among preschoolers. If this intervention is found to be efficacious, the prevalence of unhealthy lifestyles among preschoolers may be alleviated at a low cost, which not only has a positive influence on the health of individuals and the well-being of the family but also reduces the financial pressure on society to treat diseases caused by poor lifestyle habits. TRIAL REGISTRATION: ClinicalTrials.gov NCT06025019; https://clinicaltrials.gov/study/NCT06025019. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58344.
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 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 | 0,032 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,007 | 0,004 |
| Méta-épidémiologie (sens large) | 0,016 | 0,007 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,008 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,067 | 0,009 |
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 ».