Evaluating the Effectiveness of a Canadian Family-Based Childhood Obesity Management Virtual Program Delivered During the COVID-19 Pandemic (Preprint)
Notice bibliographique
Résumé
BACKGROUND Generation Health (GH) was a 10-week family-based lifestyle program designed to promote a healthy lifestyle for families with children who are off the healthy weight trajectory in British Columbia, Canada. GH used a blended delivery format which consisted of 10 weekly in-person sessions and self-guided lessons and activities on a web portal. The blended GH was adapted to be delivered virtually due to the COVID-19 pandemic. Currently, the effectiveness of the virtual GH compared with the blended GH remains unclear. OBJECTIVE 1) to compare the effectiveness of virtual GH delivered during the COVID-19 pandemic with the blended GH delivered prior to the COVID-19 pandemic in changing child physical activity, sedentary, dietary behaviours, screen time behaviours and parental support related behaviours for child physical activity and healthy eating; 2) to explore virtual GH program engagement and satisfaction. METHODS This study used a single-arm design. The blended GH (n=102) was delivered from October 2018 to February 2020, and the virtual GH (n=90) was delivered during the COVID-19 pandemic from April 2020 to March 2021. Families with children between the ages of 8-12 years old and a BMI ≥85th percentile for age and sex were recruited. Participants completed pre-and post-intervention questionnaires to assess the child’s physical activity, dietary, sedentary, screen time and parent support behaviours. Repeated measure ANOVA was used to evaluate the difference between the virtual and blended GH over time. RESULTS Both the virtual and blended GH improved child MVPA (F(1,380)=18.37, p<.00001, ηp2=.07) and reduced screen time (F(1,380)= 9.17, p=.003, ηp2=.06 ). However, participants in the virtual GH reported significantly greater vegetable intake than in blended GH at 10-week follow-up (F(1,380)=15.19, p<.001, ηp2 =.004).. Parents in both virtual and blended GH showed significant improvements in support behaviours for child physical activity (F(1,380)=5.55, p<.02, ηp2 =.002) and healthy eating (F(1,380)=3.91, p<.001, ηp2=.01), as well as self-regulation of parent support for child physical activity (F(1,380)=49.20, p<.0001, ηp2=.16) and healthy eating (F(1,380)=91.13, p<.0001, ηp2) =.28). Families in both the virtual and blended GH were satisfied with the program delivery. There were no significant differences in attendance for the weekly in-person (77%) or group video chat sessions (76%) for the blended and virtual GH, respectively (p>.05). However, webportal usage was significantly greater in the virtual GH (50 [55.82] minutes) compared with blended GH (17 [15.3] minutes) (p<.001). CONCLUSIONS Findings from this study suggested that virtual GH was as effective in improving child lifestyle behaviours and parental support-related behaviours as the blended program. Virtual GH has the potential to improve the flexibility and scalability of family-based childhood obesity management interventions.
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 | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 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 ».