The Implementation of Person-Centred Plans in the Community-Care Sector: A Qualitative Study in Ontario, Canada
Notice bibliographique
Résumé
Background: Person-centred planning (PCP) refers to a model of care in which programs and services are developed in collaboration with persons-supported (i.e., persons receiving care) and tailored to their unique needs and goals. In recent decades, governments around the world have enacted policies requiring community-care agencies to adopt an individualized or person-centred approach to service delivery. Although regional mandates provide a framework for directing care, it is unclear how this guidance is implemented in practice given the diversity and range of organizations within the sector. Objective: This study aims to address a gap in current literature by describing how person-centred plans are implemented in community-care organizations. By describing existing practices, we aim to provide insight on how to optimize care delivery to improve outcomes for community-care populations. Methods: We collaborated directly with knowledge users at each stage of the research process (i.e., study design and conception, interview guide development, recruitment, knowledge translation, etc.) through our formal partnership with PHSS, a not-for-profit community-care organization based in a large urban city in Ontario, Canada. We conducted semi-structured interviews with administrators from community-care organizations in the region. We asked participants about their organization’s approach to developing and updating person-centred plans, including relevant supports and barriers. We analyzed the data thematically using a pragmatic, qualitative, descriptive approach. Results: We interviewed administrators across 12 community-care organizations in Ontario, Canada. We identified three overarching themes related to organizational characteristics and the PCP process: (1) organizational context, (2) organizational culture, and (3) the design and delivery of person-centred plans. The context of care and the type of services offered by the organization were directly informed by the needs and characteristics of the population served. The culture of the organization (e.g., their values, attitudes and beliefs surrounding persons-supported) was a key influence in the development and implementation of person-centred plans. Participants described the PCP process as being iterative and collaborative, involving initial and continued consultations with persons-supported and their close family and friends, while also citing implementation challenges in cases where persons had difficulty communicating or were non-verbal, and in cases where they preferred not to have a formal plan in place. Conclusions: These findings provide valuable insight into the implementation of person-centred plans in the community-care sector. The important role of organizational culture and context offers universal lessons for community-care stakeholders. We also identified implementation challenges, highlighting a gap between policy and practice and suggesting a need for comprehensive guidance and enhanced adaptability in current regulations. Policymakers, administrators, and service providers can leverage these insights to refine policies, advocating for inclusive, flexible approaches that better align with diverse community needs.
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 | 0,012 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,033 | 0,014 |
| Communication savante | 0,006 | 0,002 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,003 |
| 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 ».