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Home Science Mathematics

Mathematical equation predicts happiness

Scientists successfully predicted human happiness using a mathematical equation - you too can use the smartphone app they developed and be a part of the experiment.

by Dragos Mitrica
August 5, 2014
in Mathematics, News
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The happiness of over 18.000 people all around the world has been successfully predicted (to some extent) by a mathematical equation.

UCL (University College London) researchers showed that moment-to-moment happiness reflects not just how well things are going, but whether or not things are going better than expected, and this is key for happiness. The new equation accurately predicts how happy people will be based on recent events and their reactions to those events. The first thing which scientists concluded is that wealth is a lousy predictor of happiness.

It is clear that life events affect an individual’s happiness but how could you predict how happy people are going to be based on just past events? After all, they will make decisions and receive outcomes (positive or negative) based on those decisions. This is exactly what the new study published in Proceedings of the National Academy of Sciences describes. Scientists hope that understanding how people change their mental state in regards to events in their life can be very important not only to improve life quality, but also in predicting and treating ailments such as depression or mood swings.

For the study, 26 subjects completed a decision-making task in which their choices led to monetary gains and losses. Throughout the study, they were constantly asked “how happy are you now?”. Their brain response was also constantly monitored with a functional MRI. After this, scientists built a computational model in which self-reported happiness was related to recent rewards and expectations. The model was then tested on 18,420 participants in the game ‘What makes me happy?’ in a smartphone app developed at UCL called ‘The Great Brain Experiment‘. Interestingly enough, scientists found that the same equation they used for the original 26 subjects could be successfully used to predict how happy game users will be – even if they won just points, and not real money.

Lead author of the study, Dr Robb Rutledge (UCL Wellcome Trust Centre for Neuroimaging and the new Max Planck UCL Centre for Computational Psychiatry and Ageing), said:

“We expected to see that recent rewards would affect moment-to-moment happiness but were surprised to find just how important expectations are in determining happiness. In real-world situations, the rewards associated with life decisions such as starting a new job or getting married are often not realised for a long time, and our results suggest expectations related to these decisions, good and bad, have a big effect on happiness.”

He declared that he was surprised to see just how well the equation functions. He explains that your expected outcomes heavily impact your state of mind.

“Life is full of expectations — it would be difficult to make good decisions without knowing, for example, which restaurant you like better. It is often said that you will be happier if your expectations are lower. We find that there is some truth to this: lower expectations make it more likely that an outcome will exceed those expectations and have a positive impact on happiness. However, expectations also affect happiness even before we learn the outcome of a decision. If you have plans to meet a friend at your favourite 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.”

I’m already starting to feel a little Hari Seldon in here.

Scientific Reference: Robb B. Rutledge, Nikolina Skandali, Peter Dayan, and Raymond J. Dolan. A computational and neural model of momentary subjective well-being. PNAS, 2014 DOI: 10.1073/pnas.1407535111

Tags: equationhappinessmathematical modelUniversity College London

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