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Enregistrement W4293339979 · doi:10.2196/40431

Evaluating the Effectiveness of a Family-Based Virtual Childhood Obesity Management Program Delivered During the COVID-19 Pandemic in Canada: Prospective Study

2022· article· en· W4293339979 sur OpenAlexafffundvenueabout
Kayla Nuss, Rebecca Coulter, Bianca DeSilva, Jeann Buenafe, Ronak Sheikhi, Patti‐Jean Naylor, Sam Liu

Notice bibliographique

RevueJMIR Pediatrics and Parenting · 2022
Typearticle
Langueen
DomainePsychology
ThématiqueCOVID-19 and Mental Health
Établissements canadiensUniversity of Victoria
Organismes subventionnairesMinistry of Health, British Columbia
Mots-clésScreen timeOverweightMedicinePandemicChildhood obesityCoronavirus disease 2019 (COVID-19)ObesityRepeated measures designSedentary lifestylePhysical activityPhysical therapyGerontologyFamily medicine

Résumé

récupéré en direct d'OpenAlex

Background Generation Health (GH) is 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 uses a blended delivery format that involves 10 weekly in-person sessions, and self-guided lessons and activities on a web portal. The blended program was adapted to be delivered virtually due to the COVID-19 pandemic. Currently, the effectiveness of the virtual GH program compared with that of the blended GH program remains unclear. Objective We aimed to (1) compare the effectiveness of the virtual GH program delivered during the COVID-19 pandemic with that of the blended GH program delivered prior to the pandemic for changing child physical activity, sedentary and dietary behaviors, screen time, and parental support–related behaviors for child physical activity and healthy eating, and (2) explore virtual GH program engagement and satisfaction. Methods This study used a single-arm pre-post design. The blended GH program (n=102) was delivered from January 2019 to February 2020, and the virtual GH program (n=90) was delivered during the COVID-19 pandemic from April 2020 to March 2021. Families with children aged 8-12 years and considered overweight or obese (BMI ≥85th percentile according to age and sex) were recruited. Participants completed preintervention and postintervention questionnaires to assess the children’s physical activity, dietary and sedentary behaviors, and screen time, and the parent’s support behaviors. Intervention feedback was obtained by interviews. Repeated measures ANOVA was used to evaluate the difference between the virtual and blended GH programs over time. Qualitative interviews were analyzed using thematic analyses. Results Both the virtual and blended GH programs improved children’s moderate-to-vigorous physical activity (F1,380=18.37; P<.001; ηp2=0.07) and reduced screen time (F1,380=9.17; P=.003; ηp2=0.06). However, vegetable intake was significantly greater in the virtual GH group than in the blended GH group at the 10-week follow-up (F1,380=15.19; P<.001; ηp2=0.004). Parents in both groups showed significant improvements in support behaviors for children’s physical activity (F1,380=5.55; P=.02; ηp2=0.002) and healthy eating (F1,380=3.91; P<.001; ηp2=0.01), as well as self-regulation of parental support for children’s physical activity (F1,380=49.20; P<.001; ηp2=0.16) and healthy eating (F1,380=91.13; P<.001; ηp2=0.28). Families in both groups were satisfied with program delivery. There were no significant differences in attendance for the weekly in-person or group video chat sessions; however, portal usage was significantly greater in the virtual GH group (mean 50, SD 55.82 minutes) than in the blended GH group (mean 17, SD 15.3 minutes; P<.001). Conclusions The study findings suggested that the virtual GH program was as effective as the blended program for improving child lifestyle behaviors and parental support–related behaviors. The virtual program 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 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)0,003
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 enseignants0,212
Score d'incertitude au seuil0,834

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,058
Tête enseignante GPT0,401
Écart entre enseignants0,344 · 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

Citations15
Publié2022
Routes d'admission4
Résumé présentoui

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