An integrated model of psychosocial correlates of insomnia severity in family caregivers of people with dementia.

Autor: Jiménez-Gonzalo, Lucía, Vara-García, Carlos, Romero-Moreno, Rosa, Márquez-González, María, Olazarán, Javier, von Känel, Roland, Mausbach, Brent T., Losada-Baltar, Andrés
Předmět:
Zdroj: Aging & Mental Health; Jul2024, Vol. 28 Issue 7, p969-976, 8p
Abstrakt: Research has shown the relevance of stress and coping factors in explaining caregivers' insomnia symptoms. However, few attempts have been made to empirically test an integrative model for insomnia severity in family caregivers of people with dementia. The aim of this study was to test such a model, in which insomnia severity is proposed to be influenced by predisposing factors, precipitated by stressors, and perpetuated by behaviors to cope with these stressors. 311 family caregivers of people with dementia were assessed for variables categorized as predisposing (e.g. female gender), precipitating (e.g. care-recipient's behavioral and psychological symptoms of dementia [BPSD]), and perpetuating factors (e.g. sleep aids). A theoretical model was developed and then statistically tested using structural equation modelling, analyzing the direct and indirect effects of the assessed variables on caregivers' insomnia severity. Distress, sleep aids, and experiential avoidance showed a direct association with insomnia severity. Female gender, younger age, cognitive fusion, leisure activities, dysfunctional thoughts, frequency and distress caused by care-recipient's BPSD showed indirect associations with insomnia severity. The model explained 22% of the variance of caregivers' insomnia severity. The results provide additional empirical support for the importance of predisposing, precipitating and perpetuating factors associated with caregivers' insomnia severity. The integrative model we propose may also be useful for developing interventions targeting insomnia symptoms in family dementia caregivers. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index