Evolution of public health policy on healthcare self-management: the case of Ontario, Canada
Notice bibliographique
Résumé
Abstract Background As people live longer, they are at increased risk for chronic diseases and disability. Self-management is a strategy to improve health outcomes and quality of life of those who engage in it. This study sought to gain a better understanding of the factors, including digital technology, that affect public health policy on self-management through an analysis of government policy in the most populous and multicultural province in Canada: Ontario. The overarching question guiding the study was: What factors have influenced the development of healthcare self-management policies over time? Methods Archival research methods, combining document review and evaluation, were used to collect data from policy documents published in Ontario. The documents were analyzed using the READ approach, evaluated using a data extraction table, and synthesized into themes using the model for health policy analysis. Results Between January 1, 1985, and May 5, 2022, 72 policy documents on self-management of health were retrieved from databases, archives, and grey literature. Their contents largely focussed on self-management of general chronic conditions, while 47% (n = 18/72) mention diabetes, and 3% (n = 2/72) focussed solely on older adults. Digital technologies were mentioned and were viewed as tools to support self-management in the context of healthcare delivery and enhancing healthcare infrastructure (i.e., telehealth or software in healthcare settings). The actors involved in the policy document creation included mostly Ontario government agencies and departments, and sometimes expert organizations, community groups and engaged stakeholders. The results suggest that several factors including pressures on the healthcare system, hybrid top-down and bottom-up policymaking, and political context have influenced the nature and implementation timing of self-management policy in Ontario. Conclusions The policy documents on self-management of health reveal a positive evolution of the content discussed over time. The changes were shaped by an evolving context, both from a health and political perspective, within a dynamic system of interactions between actors. This research helps understand the factors that have shaped changes and suggests that a critical evidence-based approach on public health policy is needed in understanding processes involved in the development of healthcare self-management policies from the perspective of a democratic governing system.
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 | 0,011 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,009 |
| Études des sciences et des technologies | 0,027 | 0,012 |
| Communication savante | 0,011 | 0,003 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,002 |
| 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 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 ».