Évaluation du Plan d’action en santé mentale (2005-2015) : intégration et performance des réseaux de services
Notice bibliographique
Résumé
Objectives This study aimed to: 1) assess implementation of the 2005-2015 Quebec mental health (MH) reform, and its enabling and hindering factors as well as MH team performance, in 11 local health service networks; then, for a subset of 4 networks: 2) identify processes influencing service quality in MH teams, and 3) analyze effects of team structures and processes on outcomes for service users.Methods The networks were selected in consultation with 20 MH decision makers. Data sources included: 1) documentation on population, organization and service characteristics, integration strategies, and network challenges; 2) individual and group interviews with 102 regional managers, MH professionals and managers from primary care or specialized MH teams, community organization directors, respondent psychiatrists and general practitioners (GPs); and 3) questionnaires completed by 16 respondent psychiatrists, 90 managers, 315 MH professionals from primary care or specialized teams, and 327 service users.Results Objectives of the MH reform were only partially achieved across the 11 health service networks, given the limited availability of practice guidelines related to implementing new structures and services, and reluctance among MH professionals (mainly GPs) to adopt them. As well, most primary care teams lacked GPs or psychiatrists. Implementation was more successful in large networks with specialized services located in general hospitals. The use of clinical tools and approaches, and frequent interactions with other teams or organizations enhanced team performance. Several team process variables including autonomy, involvement in decision-making, and knowledge sharing were strongly associated with the performance of MH professionals and higher quality services. While geographic variables (e.g. frequency of interactions with GPs) had more influence on performance in specialized services, individual variables (e.g. lower seniority in the team) and organizational variables (e.g. lower proportion of service users with personality disorders) influenced performance in primary care teams. Work satisfaction was more strongly associated with team process variables (e.g. fewer conflicts, higher team support, greater collaboration) and recovery-oriented services with organizational variables (e.g. primary care team). Some types of organizational culture were strongly associated with team performance (clan and hierarchical cultures), and work satisfaction (market culture). Concerning effects of team structure and processes on service user outcomes, higher quality of life and recovery scores were strongly associated with continuity and diversity of services. Finally, high seriousness of needs among service users represented a major obstacle for MH services attempting to address their quality of life issues and recovery.Conclusion This study suggests various measures that may improve MH service quality: promotion of more results-oriented organizational cultures, and greater collaboration, professional training on evidence-based practices, greater support for professionals, increasing their autonomy and involvement in decision-making, and more formalized integration strategies. Diversified and continuous biopsychosocial support was also recommended for improving quality of life and recovery among service users.
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 | 0,062 | 0,073 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».