Exploring the interconnectedness of fatigue, depression, anxiety and potential risk and protective factors in cancer patients: a network approach.
Acceptance
Anxiety
Cancer
Cancer-related fatigue
Coping
Depression
Helplessness
Network analysis
Journal
Journal of behavioral medicine
ISSN: 1573-3521
Titre abrégé: J Behav Med
Pays: United States
ID NLM: 7807105
Informations de publication
Date de publication:
08 2020
08 2020
Historique:
received:
04
02
2019
accepted:
17
07
2019
pubmed:
23
8
2019
medline:
7
2
2021
entrez:
23
8
2019
Statut:
ppublish
Résumé
Researchers have extensively studied fatigue, depression and anxiety in cancer patients. Several risk and protective factors have been identified for these symptoms. As most studies address these constructs, independently from other symptoms and potential risk and protective factors, more insight into the complex relationships among these constructs is needed. This study used the multivariate network approach to gain a better understanding of how patients' symptoms and risk and protective factors (i.e. physical symptoms, social withdrawal, illness cognitions, goal adjustment and partner support) are interconnected. We used cross-sectional data from a sample of cancer patients seeking psychological care (n = 342). Using network modelling, the relationships among symptoms of fatigue, depression and anxiety, and potential risk and protective factors were explored. Additionally, centrality (i.e. the number and strength of connections of a construct) and stability of the network were explored. Among risk factors, the relationship of helplessness and physical symptoms with fatigue stood out as they were stronger than most other connections in the network. Among protective factors, illness acceptance was most centrally embedded within the network, indicating it had more and stronger connections than most other variables in the network. The network identified key connections with risk factors (helplessness, physical symptoms) and a key protective factor (acceptance) at the group level. Longitudinal studies should explore these risk and protective factors in individual dynamic networks to further investigate their causal role and the extent to which such networks can inform us on what treatment would be most suitable for the individual cancer patient.
Identifiants
pubmed: 31435892
doi: 10.1007/s10865-019-00084-7
pii: 10.1007/s10865-019-00084-7
pmc: PMC7366596
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
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