Co-designing action-oriented mental health conversations: the case for integration in home and community care.
Notice bibliographique
Résumé
Background: The COVID-19 pandemic has reinforced concerns for the mental health and wellness of older adults worldwide. Older adults experiencing poor mental health may face both mental health stigma and ageism, which act as barriers to talking about mental health and seeking needed supports, care, and treatment. In Canada and elsewhere, there is a lack of mental health parity. The healthcare system’s focus on the physical healthcare needs of older adults creates missed opportunities for intentional conversations about mental health between providers and older patients during routine interactions. Aims: This project responds to aging and mental health research priorities identified by aging Canadians during the pandemic through surveys (n=1,000) and workshops (n= 52 participants). Top priorities included the need for research and action supporting: 1) skill-building in non-mental health specialists; and 2) the application of user-friendly tools to identify signs of positive and poor mental health. The aim of this multi-year research study is to co-design and test an evidence-based approach to starting mental health conversations between home and community care providers, older adults and/or their family caregivers. Methods: This study applies a participatory mixed methods design across three phases, guided by a working group of experts-by-lived-experience (n=30). Phase 1 involved a modified ADAPTE process including online workshops (n= 57 participants) and surveys (n=~1000) of older adults, caregivers, and health/social care providers across Canada. The workshops explored the use of an evidence-based visual model, called the Mental Health Continuum, to guide mental health conversations in home and community care. Phase 2 will involve co-design workshops with community health/social care providers in six communities (n= 3 rural; n=3 urban) across three Canadian provinces. Phase 3 will involve pilot and feasibility testing of the co-designed conversations in routine care. This abstract focuses on the findings from Phase 1. Results: Workshop participants agreed that a visual model depicting mental health as a complex, multi-component construct ranging in state on a spectrum, was a helpful starting point for de-stigmatizing mental health between older adults, caregivers, and health/social care providers. However, participants felt the Mental Health Continuum needed to be adapted for use in promoting conversations in the context of home and community care. Suggested adaptations include the use of generic and action-oriented language across the model, more inclusive use of colours, capturing the element of change-over-time, removing clinical jargon from category names, and revising the signs and signals to be more aging context-relevant. Public consultation survey results are expected by the date of the conference. Learnings: Engaging experts-by-lived-experience in all study phases is crucial for building on existing evidence in new research through a realist lens and ensuring widespread health issues are met with context-specific and relevant solutions. Workshops reinforced research priorities identified during the pandemic and confirmed the study’s potential to address challenges with integration of health and social care for older adults through de-stigmatizing mental health conversations. Next steps: The adapted Mental Health Continuum model will guide the co-design and pilot-testing work in Phases 2 and 3 of the research study.
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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 | 0,134 | 0,129 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,030 | 0,031 |
| Communication savante | 0,017 | 0,016 |
| Science ouverte | 0,009 | 0,040 |
| Intégrité de la recherche | 0,009 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».