The research project of the team from University College London (UCL) in the UK involved over 18,000 participants from around the world and found that moment-to-moment happiness was more likely to be predicted by a person's recent history of expectations, with regard to whether choices could lead to good or bad outcomes.
Published in the Proceedings of the National Academy of Sciences, the research team focused on how the decisions that people make and the outcomes resulting from those decisions affected how happy people said that they were, moment by moment.
Finding out precisely what impacts the most on happiness could lead to more effective treatments for people with mood disorders, as well as helping governments such as the UK's, who are currently measuring the well-being of the public in order to inform policy.
The accumulation of wealth was found to not be a good predictor of happiness. The authors write, "our computational model suggests momentary happiness is a state that reflects not how well things are going but instead whether things are going better than expected."
'The Great Brain Experiment'
An equation to predict happiness could help improve the treatment of various mood disorders, as well as governments who measure well-being to inform policy.
The research began with asking 26 participants to complete a decision-making task, where the choices could lead to monetary gains and losses. During the task, the participants were repeatedly asked the question, "how happy are you right now?"
The neural activity of the participants was also observed during this investigation using functional MRI, and the data were used by the scientists, along with the answers given to the question, to create a computational model that related self-reported happiness to recent rewards and expectations.
The next stage of the study involved testing this model on 18,420 participants with a smartphone app, a game called "The Great Brain Experiment." The game replaced winning and losing money with a point-scoring system.
The scientists found that the equation they had built during the study's initial decision-making task to predict how happy participants were still worked during the second stage.
Lead author of the study Dr. Robb Rutledge is pleased with how effective the smartphone app was in conducting the research. He says the fact that their happiness equation worked for both the app users and those examined in the initial experiment demonstrated "the tremendous value of this approach for studying human well-being on a large scale."
Dr. Rutledge was surprised that the study found expectations to have such an important role in determining happiness, observing that "the rewards associated with life decisions [...] are often not realized for a long time, and our results suggest expectations related to these decisions, good and bad, have a big effect on happiness."
"Expectations also affect happiness even before we learn the outcome of a decision. If you have plans to meet a friend at your favorite restaurant, those positive expectations may increase your happiness as soon as you make the plan. The new equation captures these different effects of expectations and allows happiness to be predicted based on the combined effects of many past events."
The functional MRI utilized by the team observed that neural signals made in an area of the brain called the striatum during the decisions and outcomes of the task could be used to predict changes in momentary happiness.
The signals in this area of the brain are believed to be partially reliant on the neurotransmitter dopamine, suggesting that it could be possible that dopamine plays a part in determining happiness.
Taking the equation out of the rigid structure of a game would be a way of finding out whether the research adds up, but if these findings can make the treatment of mood disorders and certain government policies more effective, they could make a great number of people very happy indeed.
Recently, Medical News Today reported on a study that suggested genetics could influence happiness.