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Enregistrement W2936360554 · doi:10.2196/12512

Physical Activity and Mobile Phone Apps in the Preschool Age: Perceptions of Teachers and Parents

2019· article· en· W2936360554 sur OpenAlexvenueno aff
Anna Ek, Johanna Sandborg, Christine Delisle Nyström, Anna-Karin Lindqvist, Stina Rutberg, Marie Löf

Notice bibliographique

RevueJMIR mhealth and uhealth · 2019
Typearticle
Langueen
DomaineHealth Professions
ThématiqueMobile Health and mHealth Applications
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFacilitatorThematic analysisPsychological interventionMobile phonePsychologyPerceptionDevelopmental psychologyMedicineQualitative researchNursingSocial psychology

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Physical activity (PA) is already beneficial at the preschool age. In many countries, young children spend most of their days in the preschool setting, making it a common arena for PA interventions. Mobile health tools are becoming increasingly popular to promote PA in different populations; however, little is known about the interest for and how the preschool setting could incorporate such a tool. OBJECTIVE: This study aimed to examine how teachers and parents perceive PA in preschool-aged children in general and their perceptions of how a mobile phone app could be used to promote PA in the preschool setting. METHODS: Semistructured interviews were conducted with 15 teachers (93%, [14/15] women, mean age 43.5 years, 47%, [7/15] with a university degree and 10 parents [91%, 9/10] women, mean age 38.9 years, all with a university degree) recruited from 2 urban preschools in central Sweden. The interviews were recorded, fully transcribed, coded, and analyzed using thematic analysis by means of an inductive approach. RESULTS: The analysis revealed 4 themes: (1) children are physically active by nature, (2) the environment as a facilitator or a barrier, (3) prerequisites of the adult world, and (4) an app in the preschool setting-challenges and possibilities. Parents and teachers perceived preschoolers as being spontaneously physically active; however, high-intensity PA was perceived as low. The PA was specifically performed during the day in the preschool. Identified facilitators of PA were access to safe and engaging outdoor environments such as forests, spacious indoor areas, and adult involvement. Adult involvement was considered especially important for children preferring sedentary activities. Identified barriers for PA were restricted indoor and outdoor space, rules for indoor activities, and lack of adult involvement because of time constraints. The teachers perceived that they had limited skills and experiences using apps in general, although they also acknowledged the increasing role of technological tools in the curriculum. Thus, the teachers expressed an interest for an app designed as a support tool for them, especially for situations when PA was limited because of perceived barriers. They suggested the app to include accessible information regarding the health benefits of PA in children linked to a library of activities for different settings and seasons. Parents suggested interactive app features including problem-solving tasks and music and dance, but not video clips as they made children passive. CONCLUSIONS: Vigorous PA was perceived as low in preschool-aged children. Future tailoring of interventions in the preschool setting should work around barriers and support facilitators to PA, especially PA of high intensity. In such work, an app could serve as a source of inspiration for PA in different ages, settings, and seasons and thus reduce environmental and structural inequalities in the preschool setting.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,008
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,015
Score d'incertitude au seuil0,030

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,008
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0020,001
Communication savante0,0030,001
Science ouverte0,0000,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,048
Tête enseignante GPT0,452
Écart entre enseignants0,404 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
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

Citations22
Publié2019
Routes d'admission1
Résumé présentoui

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