The Heartwarming Relationship Between Strong Ties and Rural Elders’ Well-being
https://journals.sagepub.com/doi/abs/10.2190/AG.70.2.b
Graph theory is applicable to many different situations, and its importance in social networks goes beyond just the strong and weak ties that classify relationships between people. In this case, it was found that strong ties between rural elderly people increased their well-being. This unexpected but unsurprising relationship shows how social ties have implications that go beyond classifying a relationship by a “strong” or “weak” tie; peoples’ well-beings can be reflected in these ties, and it prompted me to wonder how we could use this knowledge and our knowledge of graph theory to possibly increase human well-being.
In a study that looks at rural elderly people and investigates the relationship between strength of ties and well-being, researchers from the North Carolina State University looked at elders from rural to urban areas and measured their levels of relationships – which helped categorize the strength of their relationships – as well as their well-being – which included a variety of statistics, including overall happiness, mental health, attitude, and many more factors (Mair & Thivierge-Rikard). Ultimately, it was found that “a) strong ties increase subjective well-being; and b) the effect of informal strong ties differs by region” (Mair & Thivierge-Rikard). To address regional differences, it is emphasized that the relationship between social ties and well-being should only be applied to rural elders because urban elders receive less help from family or friends than rural elders do, meaning that rural elders have “a stronger response to strong ties” (Mair & Thivierge-Rikard). Thus, the study showed a relationship between strong ties and better well-being, indicating that, in the rural elderly population, that stronger ties generally corresponded with better well-being.
In the class book and lecture, it was discussed how strong and weak ties play out in a social network (Lecture on Graph Theory). This social network – rural elders and their friends and families – can be followed through to see the pattern of well-being among the people, or the nodes of the network. We also discussed the need to have triadic closure between nodes. Thus, if nodes A/B and A/C have strong ties, then there should be a tie between B/C; this makes sure that nodes do not violate the STCP (Lecture on Graph Theory). Applying this to the graph could potentially allow us to forge new relationships that may evolve into strong ties and thus be associated with better well-being. If more people create strong ties, then there may be a better chance of their well-being improving.
This also brings up the point that the ties between people may have some implication on the peoples’ wellbeing. This arguably does not mean that the ties in a social network have an influence on well-being – we don’t want to support correlation implying causation – but that the pattern could be followed to possibly create situations similar to the strong ties and apply those same circumstances to improve well-being. Using graph theory to explain patterns in social networks can highlight the beneficial and harmful effects of categorizing strong and weak ties; by looking at the ties’ relationship with well-being, we can find the ways to either improve or (in a very evil world) not improve well-being of the rural elderly population.
Ultimately, this idea that strong ties are associated with better well being is not surprising; if an elder is loved and loves someone else, then that person is more likely to help or reach out to them in times of need and thus increase the well-being of the elder. We can use this to our advantage; by knowing that stronger ties are associated with better well-being, we can encourage elders to reconnect and create strong bonds with their loved ones in order to hopefully achieve better well-being. This highlights an incredibly heartwarming part of human nature, and hopefully the usage of graph theory in the well-being of the rural elderly population can lead to more improvements in the quality of life.
Sources:
https://journals.sagepub.com/doi/pdf/10.2190/AG.70.2.b
https://www.cs.cornell.edu/home/kleinber/networks-book/networks-book-ch03.pdf