Engaging a person with lived experience of mental illness in a collaborative care model feasibility study
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Notice bibliographique
Résumé
Researchers have explored different types of treatment to help people with a mental illness with other problems they might be experiencing, such as their health condition and quality of life. Care models that involve many different health care providers working together to provide complete physical and mental health care are becoming popular. There has been a push from the research community to understand the value of including people with lived experience in such programs. While research suggests that people with lived experience may help a patient's treatment, there is little evidence on including them in a team based program. This paper describes how our research team included a person with lived experience of psychosis in both the research and care process. We list some guiding principles we used to work through some of the common challenges that are mentioned in research. Lastly, experiences from the research team, lessons learned, and a personal statement from the person with lived experience (AA) are provided to help future researchers and people with lived experience collaborate in research and healthcare. Background In our current healthcare system, people with a mental illness experience poorer physical health and early mortality in part due to the inconsistent collaboration between primary care and specialized mental health care. In efforts to bridge this gap, hospitals and primary care settings have begun to take an integrated approach to care by implementing collaborative care models to treat a variety of conditions in the past decade. The collaborative care model addresses common barriers to treatment, such as geographical distance and lack of individualized, evidence-based, measurement-based treatment. Person(s) with lived experience (PWLE) are regarded as 'experts by experience' in the scope of their first-hand experience with a diagnosis or health condition. Research suggests that including PWLE in a patient's care and treatment has significant contributions to the patient's treatment and overall outcome. However, there is minimal evidence of including PWLE in collaborative care models. This paper describes the inclusion of a PWLE in a research study and collaborative care team for youth with early psychosis. Aims To discuss the active involvement of a PWLE on the research and collaborative care team and to describe the research team's experiences and perspectives to facilitate future collaborations. Method This paper describes the inclusion of a PWLE on our research team. We provide a selective review of the literature on several global initiatives of including PWLE in different facets of the healthcare system. Additionally, we outline multiple challenges of involving PWLE in research and service delivery. Examples are provided on how recruitment and involvement was facilitated, with the guidance of several principles. Lastly, we have included a narrative note from the PWLE included in our study, who is also a contributing author to this paper (AA), where she comments on her experience in the research study. Conclusion Including PWLE in active roles in research studies and collaborative care teams can enhance the experience of the researchers, collaborative care team members, and PWLE. We showcase our method to empower other researchers and service providers to continue to seek guidance from PWLE to provide more comprehensive, collaborative care with better health outcomes for the patient, and a more satisfying care experience for the provider.
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.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 découle