Development and validation of a screener based on interRAI assessments to measure informal caregiver wellbeing in the community
Notice bibliographique
Résumé
BACKGROUND: Informal caregivers are invaluable partners of the health care system. However, their caring responsibilities often affect their psychological wellbeing and ability to continue in their role. It is of paramount importance to easily identify caregivers that would benefit from immediate assistance. METHODS: In this nonexperimental cohort study, a cross-sectional analysis was conducted among 362 informal caregivers (mean age 64.1 years, SD ± 13.1) caring for persons with high care needs (mean age 78.6 years, SD ± 15.0). Caregivers were interviewed using an interRAI-based self-reported survey with 82 items covering characteristics of caregivers including key aspects of wellbeing. A factor analysis identified items in the caregiver survey dealing with subjective wellbeing that were compared against other wellbeing measures. A screener, called Caregiver Wellbeing Index (CWBI), consisting of four items with response scores ranging from 0 to 2 was created. The CWBI was validated in a follow-up study in which 1020 screeners were completed by informal caregivers of home care clients. Clinical assessments of the care recipients (n = 262) and information on long-term care home (LTCH) admission (n = 176) were linked to the screener dataset. The association between the CWBI scores and caregiver and care recipient characteristics were assessed using logistic regression models and chi-square tests. The reliability of CWBI was also measured. RESULTS: The CWBI scores ranging from zero to eight were split in four 'wellbeing' levels (excellent, good, fair, poor). In the validation study, fair/poor psychological wellbeing was strongly associated with caregiver reports of inability to continue in their role; conflict with family; or feelings of distress, anger, or depression (P < 0.0001). Caregivers caring for a care recipient that presented changes in behavior, cognition, and mood were more likely to present fair/poor wellbeing (P < 0.0001). Additionally, caregivers with high CWBI scores (poor wellbeing) were also more likely to provide care for someone who was admitted to a LTCH (OR 3.52, CI 1.32-9.34) after controlling for care recipient and caregiver characteristics. The Cronbach alpha value 0.89 indicated high reliability. CONCLUSION: The CWBI is a valid screener that can easily identify caregivers that might benefit from further assessment and interventions.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».