Category: Stroke; Clinical Practice (assessment, diagnosis, treatment, knowledge translation/EBP, implementation science, program development); Cross-Cutting
Objective :
To (1) examine the network structure of post-stroke depressive symptoms, and (2) incorporate clinico-demographic characteristics (i.e., age, sex, race, self-care, sphincter, transfer, locomotion, communication, social cognition, social support, and pain) into the network to examine the extent of relationships between these characteristics and post-stroke depressive symptoms.
Design : Secondary data analysis of the Stroke Recovery in Underserved Population database. We estimated networks using regularized partial correlation models.
Setting : Eleven inpatient rehabilitation facilities.
Participants (or Animals, Specimens, Cadavers) : A subsample of 161 post-stroke patients with depression.
Interventions : Not applicable.
Main Outcome Measure(s) : The Center for Epidemiologic Studies Depression Scale (CES-D), DUKE-UNC Functional Social Support, and Functional Independence Measure (FIM) were administered at hospital discharge.
Results : The depressive symptoms network revealed that symptoms were positively connected within the network. In particular, strong connections appeared between feeling disliked and that others are unfriendly, depressed mood and feeling blue, feeling happy and enjoyed, and depressed mood and sadness. The most central symptoms were depressed mood and feeling disliked. Incorporating clinico-demographic covariates into the network revealed stronger relationships between social support and unfriendliness, social support and loneliness, and race and talking less.
Conclusions : Findings demonstrate the utility of a network approach in modeling the structure of depressive symptomatology and suggest unique associations between specific depressive symptoms and clinical variables in stroke. In particular, depressed mood and feeling disliked could be target symptoms for post-stroke psychosocial interventions. Given that social support is highly connected with feeling loneliness and unfriendliness, empowering depressed persons after stroke via the social support intervention could be a viable approach to enhance health outcomes.
Eunyoung Kang
– Ph.D. Student, Washington University in St.Louis, St.louis, Missouri
Mandy W.M. Fong
– Instructor, Washington University School of Medicine in St. Louis, St. Louis , MissouriEric Lenze
– Professor of Psychiatry, Washington University School of Medicine, St.Louis, Missouri
Carolyn M. Baum
– Professor of Occupational Therapy, Neurology and Social Work, Washington University School of Medicine, St.Louis, Missouri
Kenneth Ottenbacher
– Professor, Director, University of Texas Medical Branch, Galveston, Texas
Alex Wong
– Assistant Professor, Washington University School of Medicine, St. Louis, Missouri