In two previous posts, I reviewed studies of social contagion effects on alcohol use among adults and self-harm in adolescents. Prior studies of social contagion effects frequently focus on negative outcomes of such contagions, such as the spread of mass hysteria or depression. The present study focused on the construct of happiness and whether happiness can spread through a social network. If happiness can spread like a virus, it would represent a positive artifact of close human relationships.
Happiness has been extensively studied across a variety of disciplines, including medicine, psychology, and economics. However, prior to the publication of the present study, happiness had not been studied as an outcome of social contagion.
The researchers were particularly interested in identifying not only if happiness spreads to direct contacts, but if it can impact indirect contacts (i.e., friends of friends), as well as the geographical and temporal nature of the spread. The sample was derived from the offspring of subjects in the Framingham Heart Study, a longitudinal study initiated in 1948 in Framingham, Massachusetts. Of the 5124 offspring, 4739 who were alive in 1983 became the cohort for the present study. They were followed for a period of 20 years.
How were members of social networks identified? Subjects in the Framingham study identified their relatives, close friends, place of residence (neighbors), and place of employment (co-workers) allowing researchers to identify members of their social network.
What potential explanations for how happiness spreads across networks were considered in this study? The possibilities included: “induction, whereby happiness in one person causes the happiness of others; homophily, whereby happy individuals choose one another as friends and become connected; or confounding, whereby connected individuals jointly experience contemporaneous exposures (such as an economic downturn or living in the same neighbourhood)” (p. 5).
The study’s findings pointed to an induction effect across the network. Was happiness spread only to close friends and family? No—in fact they found an impact of up to three degrees of separation (a friend of a friend of a friend). However, the closer the connection, the higher likelihood of happiness: if your friend is happy, you have a 15.3% greater likelihood of happiness compared to only a 5.6% likelihood if separated by 3 degrees. There also appears to be a multiplicative effect: the more happy friends you have, the more likely you are to be happy. Interestingly, co-workers had no impact on others’ happiness.
Of note is the evidence that happiness was observed to spread across a friendship network and was not simply an artifact of people associating with people like them. “Clusters of happiness result from the spread of happiness and not just a tendency for people to associate with similar individuals” (p. 1).
What about unhappy people who later become happy? The effect of becoming happy increased the probability of happiness for a co-residential spouse by 8%. Similarly, the effect on siblings (residing near each other) was a 14% higher likelihood of happiness, compared to a 25% higher probability for friends residing nearby. Surprisingly, the strongest effect of becoming happy was observed between neighbors: if your next-door neighbor becomes happy, you are 34% more likely to become happy as well.
Certainly, pre-existing happiness, as well as other previously known factors, were influential in this study. Happiness assessed at a previous time raised the likelihood of happiness at later assessments. Also, women were less likely to be happy and educated people were more likely to be happy.
In summary, “happiness is a network phenomenon, clustering in groups of people that extend up to three degrees of separation (for example, to one’s friends’ friends’ friends)” (p. 8). This is not simply a function of happy people choosing to associate with one another. The effect is seen between family members, friends, and neighbors, but not among co-workers.
Using the results of this study, you can create a blueprint for how to increase your own happiness via social ties: initiate friendships with happy people and work to increase your network of happy relationships as broadly as possible. As this network broadens with you as a central component, your happiness will likely increase, and it will positively impact your geographically close associations with others, even those who are unhappy.
Citation: Fowler, J. H., & Christakis, N. A. (2008). Dynamic spread of happiness in a large social network: Longitudinal analysis over 20 years in the Framingham Heart Study. BMJ, 337.
©Jennie Dilworth, Ph.D