ArticleThe Neurohospitalist2021
Head-to-Head Comparison of Social Network Assessments in Stroke Survivors.
Article in The Neurohospitalist, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- Personal Social Network Analysis in Cerebellar Ataxia: Exploring Correlations with Quality of Life and Functional Outcomes.Cerebellum (London, England) · 2026Article
- Leveraging Social Networks for the Assessment and Management of Neurological Patients.Seminars in neurology · 2022Review
- Telerehabilitation of Post-Stroke Patients as a Therapeutic Solution in the Era of the Covid-19 Pandemic.Healthcare (Basel, Switzerland) · 2021Review
- Social Network Structure Is Related to Functional Improvement From Home-Based Telerehabilitation After Stroke.Frontiers in neurology · 2021Article
- Personal social network strengthens adherence to lifestyle changes in individuals with subjective cognitive decline.Alzheimer's & dementia (Amsterdam, Netherlands)Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
background and purposeSocial networks influence human health and disease through direct biological and indirect psychosocial mechanisms. They have particular importance in neurologic disease because of support, information, and healthy behavior adoption that circulate in networks. Investigations into social networks as determinants of disease risk and health outcomes have historically relied on summary indices of social support, such as the Lubben Social Network Scale-Revised (LSNS-R) or the Stroke Social Network Scale (SSNS). We compared these 2 survey tools to personal network (PERSNET) mapping tool, a novel social network survey that facilitates detailed mapping of social network structure, extraction of quantitative network structural parameters, and characterization of the demographic and health parameters of each network member.
methodsIn a cohort of inpatient and outpatient stroke survivors, we administered LSNS-R, SSNS, and PERSNET in a randomized order to each patient. We used logistic regression to generate correlation matrices between LSNS-R scores, SSNS scores, and PERSNET's network structure (eg, size and density) and composition metrics (eg, percent kin in network). We also examined the relationship between LSNS-R-derived risk of social isolation with PERSNET-derived network size.
resultsWe analyzed survey responses for 67 participants and found a significant correlation between LSNS-R, SSNS, and PERSNET-derived indices of network structure. We found no correlation between LSNS-R, SSNS, and PERSNET-derived metrics of network composition. Personal network mapping tool structural and compositional variables were also internally correlated. Social isolation defined by LSNS-R corresponded to a network size of <5.
conclusionsPersonal network mapping tool is a valid index of social network structure, with a significant correlation to validated indices of perceived social support. Personal network mapping tool also captures a novel range of health behavioral data that have not been well characterized by previous network surveys. Therefore, PERSNET offers a comprehensive social network assessment with visualization capabilities that quantifies the social environment in a valid and unique manner.
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