Experiences of service transitions in Australian early intervention psychosis services: a qualitative study with young people and their supporters
Notice bibliographique
Résumé
BACKGROUND: Different Early Intervention Psychosis Service (EIPS) models of care exist, but many rely upon community-based specialist clinical teams, often with other services providing psychosocial care. Time-limited EIPS care creates numerous service transitions that have potential to interrupt continuity of care. We explored with young people (YP) and their support people (SP) their experiences of these transitions, how they affected care and how they could be better managed. METHODS: Using purposive sampling, we recruited twenty-seven YP, all of whom had been hospitalised at some stage, and twelve SP (parents and partners of YP) from state and federally funded EIPS in Australia with different models of care and integration into secondary mental health care. Audio-recorded interviews were conducted face-to-face or via phone. A diverse research team (including lived experience, clinician and academic researchers) used an inductive thematic analysis process. Two researchers undertook iterative coding using NVivo12 software, themes were developed and refined in ongoing team discussion. RESULTS: The analysis identified four major service-related transitions in a YP's journey with the EIPS that were described as reflecting critical moments of care, including: transitioning into EIPS; within service changes; transitioning in and out of hospital whilst in EIPS care; and, EIPS discharge. These service-related transition affected continuity of care, whilst within service changes, such as staff turnover, affected the consistency of care and could result in information asymmetry. At these transition points, continuity of care, ensuring service accessibility and flexibility, person centredness and undertake bio-psychosocial support and planning were recommended. State and federally funded services both had high levels of service satisfaction, however, there was evidence of higher staff turnover in federally funded services. CONCLUSION: Service transitions were identified as vulnerable times in YP and SP continuity of care. Although these were often well supported by the EIPS, participants provided illustrative examples for service improvement. These included enhancing continuity and consistency of care, through informed and supportive handovers when staff changes occur, and collaborative planning with other services and the YP, particularly during critical change periods such as hospitalisation.
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 | 0,009 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,012 | 0,009 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,002 | 0,008 |
| Intégrité de la recherche | 0,002 | 0,004 |
| 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 ».