Head-to-Head Comparison of Social Network Assessments in Stroke Survivors

Abstract

Background and Purpose: Social 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. Methods: In 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. Results: We 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. Conclusions: Personal 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.

Personal social networks of people with Down syndrome

“…We adapted the PERSNET personal networks instrument previously created, validated, and implemented by Dhand et al (2016Dhand et al ( , 2018 and Prust et al (2021). We created two versions of the survey: one for participants with DS and another for the study partners.…”

Leveraging Social Networks for the Assessment and Management of Neurological Patients

“…In a head-to-head comparison between PERSNET and the Lubben Social Network Scale-Revised and Stroke Social Network Scale in a clinical context, we found that PERSNET had similar psychometric properties to these core measures while allowing for social network visualization. 6 However, there are clear limitations to retrospective selfreports, particularly in clinical contexts. For example, we have found that 45% of patients who have a stroke cannot complete questionnaires during hospitalization due to cognitive or language deficits.…”

“…In a head-to-head comparison between PERSNET and the Lubben Social Network Scale–Revised and Stroke Social Network Scale in a clinical context, we found that PERSNET had similar psychometric properties to these core measures while allowing for social network visualization. 6 …”

“… 5 Social networks may be quantified using graph theory metrics so that their structure (e.g., size and density) and composition (e.g., proportion of family members vs. friends) are visually and statistically described. 6 Social interactions are the synchronous interactions between individuals through speech or computer-based communication (e.g., online interactions). The extent and nature of social interactions are the main constituents of social networks.…”

Social Network Structure Is Related to Functional Improvement From Home-Based Telerehabilitation After Stroke

“…To this end, we developed a 12-week home-based TR program for stroke patients and routinely assessed motor status and mood. We then used PERSNET, a validated personal network analytic tool, to quantify the structure and composition of each patient's social network and evaluated which social factors might be important to achieve motor gains and improved mood from TR ( 14 ).…”