Parents’ Perceptions of Their Children’s Engagement in a Consumer-Based Meditation Mobile App: Cross-Sectional Survey Study
Notice bibliographique
Résumé
BACKGROUND: In the United States, nearly half (48%) of school-aged children experience sleep disturbance that results in less than the recommended sleep duration, which may negatively impact mental health and behavior. Mindfulness interventions may improve sleep and mental health in youth. However, there are gaps in the literature regarding how children (2-12 years) and adolescents (13-17 years) practice mindfulness and the extent to which they benefit from these practices. OBJECTIVE: The purpose of this study was to determine parents' perceptions of their children's engagement with a consumer-based mindfulness meditation app and the extent to which they believe their children have benefitted from using the app, particularly with regard to sleep. METHODS: This study is a secondary analysis of a cross-sectional survey in adult subscribers (N=11,108) to the mindfulness meditation mobile app Calm. Participants who indicated that they had a child or children younger than 18 years (2944/11,108) who used the Calm app were asked additional questions related to their perceptions of their children's engagement with Calm. Descriptive statistics were used to assess children's app engagement, and chi-square tests and binary logistic regression models were used to assess differences in children's usage based on gender and age. RESULTS: Among the survey respondents, approximately half of the parents (1537/2944, 52.21%) reported that their children used Calm. Children used Calm mostly for (1) sleep (1168/1537, 75.99%), (2) stress (491/1537, 31.95%), (3) depression or anxiety (430/1537, 27.98%), and (4) improvement of overall health (215/1537,13.99%). Older children were more likely to begin using Calm to reduce stress, depression, or anxiety, whereas younger children were more likely begin using Calm to improve sleep. Most children used Calm when lying down to go to bed (1113/1529, 72.79%). Children were most likely to use sleep stories at night (1144/1207, 94.78%), followed by music and soundscapes (749/1114, 67.24%), meditations (736/1120, 65.71%), and breathing exercises (610/1092, 55.86%). Nearly all parents believed that using sleep stories was helpful for their children's sleep (1090/1128, 96.63%), and the majority of parents felt that the other components were also helpful for their children's sleep (music and soundscapes [570/728, 78.30%], meditations [445/696, 63.94%], and breathing exercises [610/1092, 55.86%]). CONCLUSIONS: To our knowledge, this is the first study to explore parents' perceptions of how their children or adolescents use a popular consumer-based mindfulness mobile app (ie, Calm). As the majority of children use the app for sleep, mindfulness meditation mobile apps should consider incorporating age-appropriate sleep content to meet the needs of this audience. More research is needed to confirm the feasibility and effectiveness of mindfulness meditation apps for improving sleep and mental health in children and adolescents.
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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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».