Abstract
Social networks are conduits of support, information, and health behavior flows. Existing measures of social networks used in clinical research are typically summative scales of social support or artificially truncated networks of ≤ 5 people. Here, we introduce a quantitative social network assessment tool on a secure open-source web platform, readily deployable in large-scale clinical studies. The tool maps an individual’s personal network, including specific persons, their relationships to each other, and their health habits. To demonstrate utility, we used the tool to measure the social networks of 1493 persons at risk of multiple sclerosis. We examined each person’s social network in relation to self-reported neurological disability. We found that the characteristics of persons surrounding the participant, such as negative health behaviors, were strongly associated with the individual’s functional disability. This quantitative assessment reveals the key elements of individuals’ social environments that could be targeted in clinical trials.
Highlights
Social networks are conduits of support, information, and health behavior flows
We demonstrate the utility of the tool by quantifying the personal networks of 1493 individuals at risk for multiple sclerosis
The participants are enrolled in the Genes and Environment in Multiple Sclerosis (GEMS) project, a prospective cohort study of people with first-degree family history of MS13
Summary
Social networks are conduits of support, information, and health behavior flows. Existing measures of social networks used in clinical research are typically summative scales of social support or artificially truncated networks of ≤ 5 people. We used the tool to measure the social networks of 1493 persons at risk of multiple sclerosis. We found that the characteristics of persons surrounding the participant, such as negative health behaviors, were strongly associated with the individual’s functional disability This quantitative assessment reveals the key elements of individuals’ social environments that could be targeted in clinical trials. Social connections are potentially modifiable, making them ideal targets for changing habits such as smoking, exercise, and diet[5] Despite their promise in health, social networks are poorly understood in patient populations, and interventions aimed at networks are nascent. We demonstrate that quantifying social networks in large-scale clinical studies offers an effective platform to identify previously unknown social environment risk factors that are potentially modifiable
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