Supporting population mental health and wellness during the COVID-19 pandemic in Canada: protocol for a sequential mixed-method study
Notice bibliographique
Résumé
INTRODUCTION: The global COVID-19 pandemic has reported to have a negative impact on the mental health and well-being of individuals around the world. Mental health system infrastructure, primarily developed to support individuals through in-person care, struggled to meet rising demand for services even prior to COVID-19. With public health guidelines requiring the use of physical distancing during the pandemic, digital mental health supports may be one way to address the needs of the population. Despite this, barriers exist in promoting and supporting access to existing and emerging digital resources. Text messaging may address some of these barriers, extending the potential reach of these digital interventions across divides that may separate some vulnerable or disadvantaged groups from essential mental health supports. Building on an existing knowledge synthesis project identifying key digital resources for improved mental health, this research will establish low-tech connections to assess need and better match access to services for those who need it most. The aim of this study is to codesign a customised two-way texting service to explore need and better align access to mental health supports for Canadians located in Saskatchewan during the COVID-19 pandemic. METHODS AND ANALYSIS: This study will be completed in Saskatchewan, Canada. For this project, the RE-AIM (reach, effectiveness, adoption, implementation, maintenance) framework will be used to support three phases of a sequential mixed-method study. An advisory committee of Saskatchewan residents will guide this work with the study team. A 10-week service will be launched to connect individuals with appropriately suited digital mental health interventions through the use of text messaging. In phase 1, implementation and prototyping will be conducted with collaborative codesign for key elements related to features of an enrolment survey and initial messaging content. Phase 2 will focus on advancing the effectiveness of the service using quantitative user data. In phase 3, an embedding approach will be used to integrate both qualitative and quantitative data collected to understand the overall acceptability, satisfaction and perceived benefit of the text messaging service. Thematic analysis and descriptive statistics will be used as analytic methods. ETHICS AND DISSEMINATION: This study has received approval from the Research Ethics Board at the University of Saskatchewan. A knowledge dissemination plan has been developed that includes traditional academic approaches such as conference presentations, and academic publications, as well as mainstream approaches such as social media, radio and dissemination through the advisory committee.
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 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 | 0,069 | 0,049 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,005 |
| Méta-épidémiologie (sens large) | 0,006 | 0,005 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,009 | 0,004 |
| Communication savante | 0,007 | 0,003 |
| Science ouverte | 0,006 | 0,003 |
| Intégrité de la recherche | 0,006 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,095 | 0,014 |
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 ».