Relationship between mutuality and depression in patients with chronic heart failure and caregivers in China: An actor-partner interdependence model analysis
Ting Zhou, Jiling Qu, Huiping Sun and 2 more
Frontiers in Psychology · 2022
doi:10.3389/fpsyg.2022.928311 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
BackgroundPatients with chronic heart failure and their family caregivers may experience adverse emotional problems, such as depression. Mutuality, which refers to the relationship between caregivers and those they care for, is an important factor affecting depression in the dyads. The purpose of this study was to investigate the relationship between mutuality and depression in patients with CHF and their caregivers in China.MethodsIn this cross-sectional study, we used the Mutuality Scale and the Self-Rating Depression Scale to measure mutuality and depression of patients and caregivers. We used SPSS version 26.0 and AMOS version 21.0 to analyze the data. An APIM was established to analyze the actor-partner effects of patient-caregiver mutuality and depression.ResultsA total of 250 dyads of patients and caregivers were included in the study. There were statistically significant differences in mutuality and depression between CHF patients and caregivers. The 4 dimensions of patients’ mutuality all have the actor effect on depression. There were 3 partner effects of caregivers’ “pleasurable activities”, “shared values”, and “reciprocity” on depression. Regarding caregiver depression, we only found an actor effect of caregivers’ “shared values” on depression.ConclusionThe relationship between patients and caregivers should be evaluated in the clinical setting, and it is very important to develop intervention measures to improve the adverse emotional problems affecting both patients and their caregivers.
Abstract licence: CC BY
References25
25 more references, whose wording the paper’s licence keeps private.
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.