Current Practices and Experiences Accessing Care for Mental Health Issues of Inflammatory Arthritis Patients from the Rheum4U Precision Health Registry
Notice bibliographique
Résumé
Objectives To understand how patients with inflammatory arthritis (IA) currently obtain access to mental healthcare resources and identify strategies to enhance support during rheumatology clinic visits. Methods Patients and healthcare providers participated in semi-structured interviews or focus groups. Patients were recruited from the Rheum4U Precision Health Registry using purposive sampling. Healthcare providers from 2 rheumatology clinics were approached in-person or by email to participate. Prior to interviews/focus groups, participants completed a survey with closed-ended questions about mental healthcare resources. The interviews/focus groups explored the use of mental health screening questionnaires and experiences of patients accessing mental healthcare resources themselves or through healthcare providers. Cognitive task analysis,[1] and service blueprinting,[2] organized and mapped current practices. The analysis will be used to create recommended care pathways, which will be later reviewed for feedback by participants. Results Six patients and 3 rheumatologists participated in interviews. Two allied health professionals and 5 nurses participated in interviews or focus groups. Four patients reported having anxiety/depression, 4 patients indicated they never discussed their mental health at rheumatology clinic visits, and none of them were using any mental healthcare resources at the time. All healthcare providers have referred patients to mental health resources, and almost all would like to discuss their patients’ mental health. Key findings included: Patients with strong social-support networks did not require assistance from healthcare providers to access resources. Some patients preferred to get assistance at the rheumatology clinic, while others consulted their general practitioner (GP), or were unsure of where to seek help for mental health concerns. After inquiring about mental health, clinic staff would refer patients to the social worker or provide relevant information. Some rheumatologists screened patients themselves to assess needs and resources and sometimes referred them to the social worker. Commonly used resources included employment assistance programs, community resources, mental health websites, and crisis lines. Rheumatologists sometimes informed their patient’s GP about mental health concerns through summaries sent via the electronic medical record system, but follow-up communication was often lacking. Figure 1 depicts a summarized journey of how patients with IA currently receive support for mental health concerns. Conclusion Access to mental health resources for patients with IA varies significantly. Streamlining support for patients could involve allied health professionals assisting rheumatologists with screening, developing a quick reference guide with available resources, and enhancing communication between involved healthcare providers to ensure continuity of care. [1.] Clark R. Handbook of research on educational communications and technology. Springer Science & Business Media; 2014:541-55. [2.] Bitner MJ. California Management Review 2008;50(3):66-94.
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 | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».