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Enregistrement W2157604776 · doi:10.2196/mhealth.3420

Parent-Targeted Mobile Phone Intervention to Increase Physical Activity in Sedentary Children: Randomized Pilot Trial

2014· article· en· W2157604776 sur OpenAlexvenueno aff
Robert L. Newton, Arwen M. Marker, H. Raymond Allen, Ryan Machtmes, Hongmei Han, William D. Johnson, John M. Schuna, Stephanie T. Broyles, Catrine Tudor‐Locke, Timothy S. Church

Notice bibliographique

RevueJMIR mhealth and uhealth · 2014
Typearticle
Langueen
DomaineMedicine
ThématiquePhysical Activity and Health
Établissements canadiensnon disponible
Organismes subventionnairesNational Institute of General Medical SciencesNational Institutes of HealthLouisiana Clinical and Translational Science Center
Mots-clésRandomized controlled trialPhysical activityMobile phoneIntervention (counseling)Pilot trialPhysical therapySedentary behaviorMedicinePsychologyComputer sciencePsychiatryTelecommunications

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Low levels of moderate-to-vigorous physical activity are associated with adverse health consequences. OBJECTIVE: The intent of the study was to determine the feasibility and efficacy of a 12-week physical activity promotion program targeting children, which was delivered to parents through mobile phones. METHODS: Potential participants were recruited through advertisements placed in the newspaper, local hospitals and schools, and an email listserv. Sedentary children aged 6-10 years were randomly assigned to a minimal (MIG) or intensive (IIG) intervention group. Parents in the MIG were given a goal to increase (within 1 month) and maintain their child's activity at 6000 pedometer steps/day above their baseline levels and to monitor their child's steps daily. Parents in the IIG were given the same steps/day and monitoring goals, in addition to text messages and articles containing additional behavioral strategies (based on the Social Cognitive Theory) designed to promote their child's physical activity. The intervention components were delivered via mobile phone. Anthropometrics, body composition, and questionnaires were administered in a clinic. Children wore a New Lifestyles pedometer (NL-1000) each day throughout the intervention and parents were to monitor their child's step counts daily. RESULTS: Out of 59 children who screened for the study, a total of 27 children (mean age 8.7, SD 1.4 years; 56%, 15/27 female; 59%, 16/27 African American) were enrolled and completed the study. Overall, 97.90% (2220/2268; 98.20%, 1072/1092 for MIG; 97.60%, 1148/1176 for IIG) of expected step data were successfully entered by the parent or study coordinator. Parents in the MIG and IIG were sent approximately 7 and 13 text messages per week, respectively, averaged over the course of the study. IIG parents accessed an average of 6.1 (SD 4.4) articles over the course of the intervention and accessed a fewer number of articles in the last month compared to the first 2 months of the study (P=.002). Children in both the MIG and IIG significantly increased their physical activity, averaged over 12 weeks, by 1427.6 (SD 583.0; P=.02) and 2832.8 (SD 604.9; P<.001) steps/day above baseline, respectively. The between group difference was not statistically significant (P=.10; effect size=.40), nor was the group by time interaction (P=.57). Regardless of group assignment, children who significantly increased their physical activity reported greater increases in physical activity enjoyment (P=.003). The number of behavioral articles accessed by IIG parents was significantly correlated with change in children's steps/day (r=.575, P=.04). Changes in children's steps/day were unrelated to changes in their body composition, mood, and food intake. CONCLUSIONS: Parent-targeted mobile phone interventions are feasible, yet more intense interventions may be needed to support parents' efforts to increase their children's physical activity to levels that approximate national recommendations. TRIAL REGISTRATION: Clinicaltrials.gov NCT01551108; http://clinicaltrials.gov/show/NCT01551108 (Archived by WebCite at http://www.webcitation.org/6TNEOzXNX).

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)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,246
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
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 Opus0,045
Tête enseignante GPT0,393
Écart entre enseignants0,349 · 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.

Devis d'étudeEssai randomisé
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

Citations66
Publié2014
Routes d'admission1
Résumé présentoui

Explorer davantage

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