Health Issues in Relation to Social Networks
Cohen et al argue that greater network diversity decreases the susceptibility to infectious diseases, even though they could not identify a specific pathway for this correlation. They also found that it was diversity and not the total number of relationships that had an effect on susceptibility. They suggest that social relationships have cognitive benefits, which in return influence people’s health.
One of the weaknesses of this study is that it does not accurately replicate real life situations. The subjects are quarantined and they are not allowed to come closer than 3ft to each other, which is not the case in real life. Therefore their findings are hard to generalize.
There might have been some problems with measurement as well. For instance, people’s metabolisms work differently, and considering that their methods for determining who is sick are not exactly accurate.
Yet it was still interesting to see such a study especially because we instinctively think about how people would contact more viruses by having larger and more diverse networks, yet it doesn’t come as naturally to think about our likeliness to fight off diseases based on the diversity of our social networks.
Dickens et al claim that lack of close confidants causes increased risk of cardiac events after myocardial infraction (MI). They could not find any relation between depression before MI and subsequent cardiac events.
Due to the nature of the study, which required very specific types of people, the retention rate of the subjects from the initial subject pool was not very high. The study could have had greater generalizability if this was not the case. Also since their sample was not big enough they could not assess certain aspects the study, such as looking at patients who develop new episodes of depression in the week after MI.
Nevertheless, this study still has some methodological strengths in terms of how they looked at each patient very carefully and acquired data that seems to be accurate. They also collected follow up data which proved to be helpful.
QUESTION: In both these studies, although the authors provide evidence about the correlation between social networks and health issues, they can only put forth possibilities as to how these could be related. For instance, they suggest that people who have low levels of social participation might be more likely to smoke and less likely to exercise, and that people who have close confidants might be more likely to seek help. In your opinion, how are the structure of our social networks related to our health? Could this be linked to Valente et al’s idea about network centrality and prestige in relation to teenage smoking? Or could Smith-Lovin and Putnam have a point about close confidants providing a special type of support by bringing you chicken soup?
Bearman et al’s study concentrates on the structure of adolescents’ romantic and sexual networks in relation to disease diffusion, and especially the spread of STDs.
Partnership patterns and network structures of these relationships lead them to believe that due to the role of homophily in choosing partners, which supports McPherson et al’s findings, a “spanning tree” model would be the most appropriate. They also specify that this pattern would hold true for adolescents but not adults.
Even though the sample size is pretty large and the retention rate was pretty high in this study, since the study is limited to a specific high school in a Midwestern town, the results are not generalizable to the entire population.
Yet, their results are still important as they suggest that creating structural breaks (similar to Burt’s structural holes) would be an efficient way to stop the spread of STDs since they are based on the “spanning tree” model. It was interesting to see the link between different network models and how diffusion would take place differently based on the model. This also suggests that the number of partners one has is less important than the structure of that person’s network in terms of the spread of STDs, which demeans the value of Hill & Dunbar’s study on network size. These findings show the importance of how social networks could be useful in disease prevention and how they can be integral to social policy.