Symptoms of mood disorders in family carers of older people with dementia who experience caregiver burden: a network approach.
anxiety
caregiver
depression
network analysis
older people
Journal
Age and ageing
ISSN: 1468-2834
Titre abrégé: Age Ageing
Pays: England
ID NLM: 0375655
Informations de publication
Date de publication:
01 07 2020
01 07 2020
Historique:
received:
03
09
2019
revised:
04
12
2019
accepted:
08
01
2020
pubmed:
25
2
2020
medline:
29
7
2021
entrez:
25
2
2020
Statut:
ppublish
Résumé
informal carers of people with dementia are at greater risk of anxiety and depressive disorders if they find caregiving to be a burden. The aim of this study was to use a network analysis of cross-sectional data to investigate the relationships between anxiety and depressive symptoms in family carers of older people with dementia who experience burden. sixty family carers exhibiting high levels of burden using the Zarit Burden Interview were included in the study. Participants completed the Hospital Anxiety and Depression Scale. The network analysis identified the depression and anxiety symptom network using features including a topological graph, network centrality metrics and community analysis. The network was estimated through the graphical LASSO technique in combination with a walktrap algorithm to obtain the clusters within the network and the connections between the nodes (symptoms). A directed acyclic graph was generated to model symptom interactions. the resulting network architecture shows important bridges between depression and anxiety symptoms. Lack of pleasure and loss of enjoyment were identified as potential gateway symptoms to other anxiety and depression symptoms and represent possible therapeutic targets for psychosocial interventions. Fear and loss of optimism were highly central symptoms, indicating their importance as warning signs of more generalised anxiety and depression. this network analysis of depressive and anxiety symptoms in overburdened family carers provides important insights as to what symptoms may be the most important targets for behavioural interventions.
Sections du résumé
BACKGROUND
informal carers of people with dementia are at greater risk of anxiety and depressive disorders if they find caregiving to be a burden. The aim of this study was to use a network analysis of cross-sectional data to investigate the relationships between anxiety and depressive symptoms in family carers of older people with dementia who experience burden.
METHODS
sixty family carers exhibiting high levels of burden using the Zarit Burden Interview were included in the study. Participants completed the Hospital Anxiety and Depression Scale. The network analysis identified the depression and anxiety symptom network using features including a topological graph, network centrality metrics and community analysis. The network was estimated through the graphical LASSO technique in combination with a walktrap algorithm to obtain the clusters within the network and the connections between the nodes (symptoms). A directed acyclic graph was generated to model symptom interactions.
RESULTS
the resulting network architecture shows important bridges between depression and anxiety symptoms. Lack of pleasure and loss of enjoyment were identified as potential gateway symptoms to other anxiety and depression symptoms and represent possible therapeutic targets for psychosocial interventions. Fear and loss of optimism were highly central symptoms, indicating their importance as warning signs of more generalised anxiety and depression.
CONCLUSIONS
this network analysis of depressive and anxiety symptoms in overburdened family carers provides important insights as to what symptoms may be the most important targets for behavioural interventions.
Identifiants
pubmed: 32091573
pii: 5748087
doi: 10.1093/ageing/afaa008
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
628-633Informations de copyright
© The Author(s) 2020. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.