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Journal de recherche et de développement en éducation à la santé

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Sibling Caregivers: A Mixed Methods Study and Family-Based Intervention Model in a Pediatric Hospital

Abstract

Raymen Rammy Assaf, Sharon M Hudon, Stephanie Marcy, Linda Radbill, Alex Van Speybroeck, Connie Siskowski and Mona Patel

Background: Caregiving youth are minors providing significant assistance to relatives or household members who have chronic physical or mental illnesses and disabilities, yet in the US are relatively under supported.

Objective: We sought to introduce a hospital-based model for screening, referral, and intervention among a population of children who care for siblings with chronic and often complex medical conditions.

Methods: A descriptive, quantitative analysis was followed by a two-phase intervention (focus group and caregiver workshop) utilizing qualitative analysis in an academic children's hospital. Screening sites included the inpatient complex care team and three outpatient clinics.

Results: Sibling caregivers (N=21) spent an average of 2 hours a day on weekdays and 4 hours a day on weekends caring for a brother or sister with a chronic health condition. Common activities of daily living included: helping with mobility, bathing, dressing, and toileting. Advanced tasks included: giving medication, managing oxygen delivery, gastrostomy tube care, suctioning or medical interpreting. We applied the stress process and transition conceptual framework in analyzing emergent themes from dialogue with sibling caregivers and parents.

Conclusion: Key beneficial elements of our hospital-based intervention program identified by participants included: structured family-based dialogue, stress management techniques, and a peer-support environment. Interventions that target both the parent and caregiving sibling, with the goal of strengthening family communication, enhancing sense of community and understanding, and nurturing coping repertoires may help promote sibling caregiver resilience.

Avertissement: Ce résumé a été traduit à l'aide d'outils d'intelligence artificielle et n'a pas encore été examiné ni vérifié

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