Protocol for READY2Exit: a patient-oriented, mixed methods study examining transition readiness in adolescents with co-occurring physical and mental health conditions
Notice bibliographique
Résumé
Abstract Background Up to 57% of adolescents and young adults (AYA) with chronic physical health conditions experience mental health conditions, the presence of which contributes to increased morbidity and poor quality of life. AYA with co-occurring physical and mental health conditions, therefore, may experience additional challenges as they transition from pediatric to adult services. While transition readiness – the acquisition of self-management and advocacy skills – contributes to successful transitions to adult care, this concept has not been adequately explored for AYA with co-occurring physical and mental health conditions. Research is needed to identify whether the presence of a mental health comorbidity is associated with transition readiness, and what the experiences of AYA with co-occurring conditions are as they exit pediatric services. This paper outlines the protocol for the R eadiness and E xperiences of AD olescents and Y oung Adults with Co-occurring Physical and Mental Health Conditions Exit ing Pediatric Services (READY2Exit) study; the first study to address this gap using a patient-oriented, mixed methods design. Methods A sequential explanatory mixed methods design will be used to understand the transition readiness of 16–21 year olds with physical and mental health conditions using quantitative and qualitative data. First, Transition Readiness Assessment Questionnaire (TRAQ) scores will be compared among AYA with chronic health conditions, with and without mental health comorbidity. Interviews will then be conducted with approximately 15 AYA with co-occurring health and mental health conditions and analyzed using qualitative description. The READY2Exit study will be conducted in collaboration with five Young Adult Research Partners (YARP) aged 18–30 with lived experience in the health/mental health systems across Canada. The YARP will partner in key tasks such as interview guide co-design, data interpretation, and knowledge translation tool development. Discussion AYA with co-occurring physical and mental health conditions may have unique needs as they prepare for health care transitions. The results of this study will inform the refinement of transition readiness practices to improve care for this group. The active involvement of the YARP across study phases will bring the critical perspectives of young adults to READY2Exit, ensuring the methods, research approaches and outputs align with their needs.
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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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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