Capturing Home Care Information Management and Communication Processes Among Caregivers of Older Adults: Qualitative Study to Inform Technology Design (Preprint)
Notice bibliographique
Résumé
BACKGROUND The demand for complex home care is increasing with the growing aging population and the ongoing COVID-19 pandemic. Family and hired caregivers play a critical role in providing care for individuals with complex home care needs. However, there are significant gaps in research informing the design of complex home care technologies that consider the experiences of family and hired caregivers collectively. OBJECTIVE The objective of this study was to explore the health documentation and communication experiences of family and hired caregivers to inform the design and adoption of new technologies for complex home care. METHODS The research involved semistructured interviews with 15 caregivers, including family and hired caregivers, each of whom was caring for an older adult with complex medical needs in their home in Ontario, Canada. Due to COVID-19–related protection measures, the interviews were conducted via Teams (Microsoft Corp). The interview guide was informed by the cognitive work analysis framework, and the interview was conducted using storytelling principles of narrative medicine to enhance knowledge. Inductive thematic analysis was used to code the data and develop themes. RESULTS Three main themes were developed. The first theme described how participants were continually updating the caregiver team, which captured how health information, including their communication motivations and intentions, was shared among family and hired caregiver participants. The subthemes included binder-based health documentation, digital health documentation, and communication practices beyond the binder. The second theme described how participants were learning to improve care and decision-making, which captured how they acted on information from various sources to provide care. The subthemes included developing expertise as a family caregiver and tailoring expertise as a hired caregiver. The third theme described how participants experienced conflicts within caregiver teams, which captured the different struggles arising from, and the causes of, breakdowns in communication and coordination between family and hired caregiver participants. The subthemes included 2-way communication and trusting the caregiver team. CONCLUSIONS This study highlights the health information communication and coordination challenges and experiences that family and hired caregivers face in complex home care settings for older adults. Given the challenges of this work domain, there is an opportunity for appropriate digital technology design to improve complex home care. When designing complex home care technologies, it will be critical to include the overlapping and disparate perspectives of family and hired caregivers collectively providing home care for older adults with complex needs to support all caregivers in their vital roles. CLINICALTRIAL
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 | 0,018 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,007 | 0,005 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».