Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2016 Oct;12(10):605-12.
doi: 10.1038/nrneurol.2016.119. Epub 2016 Sep 12.

Social networks and neurological illness

Affiliations
Review

Social networks and neurological illness

Amar Dhand et al. Nat Rev Neurol. 2016 Oct.

Abstract

Every patient is embedded in a social network of interpersonal connections that influence health outcomes. Neurologists routinely need to engage with a patient's family and friends due to the nature of the illness and its social sequelae. Social isolation is a potent determinant of poor health and neurobiological changes, and its effects can be comparable to those of traditional risk factors. It would seem reasonable, therefore, to map and follow the personal networks of neurology patients. This approach reveals influential people, their habits, and linkage patterns that could facilitate or limit health behaviours. Personal network information can be particularly valuable to enhance risk factor management, medication adherence, and functional recovery. Here, we propose an agenda for research and clinical practice that includes mapping the networks of patients with diverse neurological disorders, evaluating the impact of the networks on patient outcomes, and testing network interventions.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1. The personal network of a patient
The ego (that is, the patient) is connected to members of his personal network, known as alters, by either a strong or a weak tie. In this figure, the personal network of the patient includes subgroups of family members, friends and a co-worker. By evaluating the architecture and composition of relationships among network members, neurologists might be able to identify patients who are at risk of poor outcomes.
Figure 2
Figure 2. Social network mechanisms that influence health behaviour
Networks affect behaviour through at least five pathways; person to person contact, social engagement, social influence, access to resources and material goods, and social support. Social support comes in four forms; instrumental and financial support, informational support, appraisal support and emotional support. Appraisal support relates to how an alter can provide an ego with appropriate feedback or help with decision making. The influence of a pathway on the ego–alter relationship can change over time. Some ties operate through several pathways, while others are more specialized. The ego is the patient at the centre of the network, an alter is an individual in a network, and a tie is the connection between individuals in a network.
Figure 3
Figure 3. Personal network composition for two patients with stroke
The composition of a network includes information about alters and their habits, such as diet and the frequency of exercise. a | Patient 1 has a kin-based network with pervasive unhealthy habits. b | Patient 2’s network is mixed with kin and non-kin who are the same gender and race with healthy habits.
Figure 4
Figure 4. Personal network structure for two patients with stroke
The structure of a network is the organization of ties and their patterns in quantitative terms. Patients who are at risk of poor outcomes are typically surrounded by a small number of close-knit alters. a | Patient 1 has a high-constraint network in which all members are closely knit together. b | Patient 2 has a low-constraint network that includes unconnected individuals and structural holes.
None

References

    1. Turner MW. The King of Attolia. Harper Collins; 2009.
    1. Berkman LF, Syme SL. Social networks, host resistance, and mortality: a nine-year follow-up study of Alameda County residents. Am J Epidemiol. 1979;109:186–204. - PubMed
    1. Seeman TE, Kaplan GA, Knudsen L, Cohen R, Guralnik J. Social network ties and mortality among the elderly in the Alameda County Study. Am J Epidemiol. 1987;126:714–723. - PubMed
    1. House JS, Landis KR, Umberson D. Social relationships and health. Science. 1988;241:540–545. - PubMed
    1. Holt-Lunstad J, Smith TB, Layton JB. Social relationships and mortality risk: a meta-analytic review. PLoS Med. 2010;7:e1000316. - PMC - PubMed

Publication types