Mental Health Literacies of Secondary School Teachers in Ontario: A Mixed Methods Study
Notice bibliographique
Résumé
The purpose of this mixed methods study is to investigate the mental health literacies (MHL) of secondary school teachers in Ontario – specifically, how they understand and address the mental health (MH) challenges of students. Over the past decade, the Ontario Ministry of Education (MOE) has encouraged the improvement of teachers’ MHL; this study, therefore, also investigates what opportunities teachers have access to and what barriers they face in supporting students’ MH. A total of 211 secondary school teachers completed an online survey and 21 teachers participated in one-on-one interviews. Approximately three-quarters of the interviewed teachers showed little interest in advancing their knowledge and understanding; the ones who showed interest either had someone in their family, extended family or friends’ circle impacted with MH challenges or their school had a strong focus on MH. Based on the 211 survey respondents, survey results showed that 61.1% of teachers did not support students with MH challenges in the academic session 2017-2018. For the interviewees and survey respondents who participated in the study, the study also showed that teachers from Co-op Education, Special Education, and Guidance Departments were more aware of MH challenges and had more confidence in assisting students with MH challenges. Analyses of the interview data suggest that motivation and exposure to opportunity are the two factors that could drive a teacher’s interest in learning about MH challenges. If a teacher with high intrinsic or extrinsic (administration driven) motivation is provided with many opportunities and/or resources, she or he will take interest and learn about MH of students. However, based on the survey results of survey respondents, only 24.6% of the teachers surveyed in this study worked in schools where principals were attempting to make teachers aware of MH resources. This study has implications for the MOE and the school boards. It is imperative for the MOE to ensure that the school boards provide consistent and continuous professional development to improve educators’ MHL so that they are able to assist students with MH challenges.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 tête enseignante, 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 ».