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Shedding Light on Online Health Communities

Assistant Professor of Communication Jingbo Meng’s research on social networks in online health communities sheds light on how those networks are formed and may have an impact on their design.


The current focus of her research is on online fitness programs where people form health buddy relationships as a way to help manage their weight. Participants of these self-organized communities seek and share information and encourage one another to achieve health goals.


As part of her research, Meng tracked a health buddy network of 709 users and its weight management activities and outcomes for four months to determine the influence the network had on individual health outcomes. Her research indicates that a person’s weight loss outcome is similar to the average of his or her health buddy network.


“So if the average of your health buddies are losing weight, then it’s more likely you also will lose weight, and if the average of your health buddies are gaining weight, then you too are more likely to gain weight,” Meng said. “This emphasizes the importance of studying how people select their health buddies, because your health buddies may have a great influence on your health behaviors and outcomes.”


Meng has researched how people select health buddies by collecting network data from these online communities. She also used content analysis to code demographic information and social network analysis.


“The basic findings are that people rely a lot on their offline demographic similarities when selecting their health buddies,” Meng said. “What I found is that people who are of a similar age, of the same gender and join the community around the same time, are more likely to become health buddies.”


Meng has found that a person’s health-related status also contributes to the selection of health buddies.


“In terms of health status, one variable is their starting weight when they joined the community. What I found is people who share the same starting weight are more likely to be health buddies,” Meng said. “Another significant predictor in the formation of health buddies is the similarity in the percentage of goal achievement. For example, someone who has achieved 10 percent of his or her goal and another who has achieved 70 percent are not likely to form health buddy ties. People are more likely to select health buddies at the same stage of their change.


“Combining these findings, it seems that people are looking for friends who are at the similar stage of change so they can support each other and serve as companions in the weight loss process.”


Meng’s research may have implications in terms of design of these online health communities.


“Now we know how people naturally form networks and how they choose health buddies,” Meng said. “Now we can design some mechanism to recommend health buddies to communities members who will have a positive influence throughout the network with the ultimate goal of promoting a successful online network.”


The next step in Meng’s research is to study the message exchange network in the discussion forum to determine what factors drive the formation of social networks and to see whether these discussion forums act as pathways through which health buddy relationships are formed.

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