Smiling Mind Mindfulness in Schools Program as a Classroom-Based Self-Regulation Intervention: A Case Study
Notice bibliographique
Résumé
The number of Canadian children experiencing mental health concerns, including both internalizing and externalizing difficulties, continues to be on the rise. Coincidingly, the education system in Saskatchewan continues to experience strained resources. Thus, finding an efficacious, cost-effective, and accessible mental health intervention is vital. Both internalizing (e.g., anxiety, depression) and externalizing (e.g., hyperactivity, aggression) mental health in children are correlated with poor self-regulation. Recent reviews of the literature suggest mindfulness is a promising self-regulation intervention, particularly for clinical populations, as it targets the underlying neural mechanisms related to emotion dysregulation. The current case study aimed to provide insight into the potential value of a specific mindfulness intervention, Smiling Mind, within the context of the BALANCE classroom in Saskatoon, SK. The research questions were as follows: (a) How does incorporating a mindfulness intervention into a tier-three (high support) elementary school classroom routine affect the self-regulation (e.g., ability to appropriately manage thoughts, emotions and behaviour) of students with internalizing or externalizing mental health difficulties/disorders? (b) How does a mindfulness intervention help or hinder student readjustment to the classroom setting following a prolonged absence from school due to COVID-19? And (c) What opinions, attitudes, and feelings do the students have towards incorporating mindfulness into their school day? Data sources for this study included audiotaped semi-structured interviews, a self-report measure on self-regulation, and a Daily Recording Checklist. Semi-structured interviews were completed in place of direct observations due to the COVID-19 pandemic related restrictions and the requirement of completing the research virtually. Four methods of data analysis were employed in this case study: categorical aggregation, pattern identification, direct interpretations, and naturalistic generalizations. This in-depth process led to the formation of three main themes: The Smiling Mind Program: A General Overview; Students with Exceptionalities: “Mindful Considerations”; and Responsive Teaching and Pedagogical Considerations. Results from this research could influence educators as they attempt to meet the mental health needs of all their students within an inclusive classroom environment. Having one more tool in their professional toolboxes, like the Smiling Mind Program, can empower teachers while at the same time enhance the overall well-being of their students. Additionally, future researchers will benefit from seeing how completion of an intervention case study during the COVID-19 pandemic demands flexibility, creativity and determination. The need to pivot and adapt to changing public health or school division policies and directives became the norm during this innovative study.
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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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| 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 ».