Collidoscope, The Wire‘s weekly newsletter on social science research by Jahnavi Sen, brings together different ways of understanding and analysing society, focusing on a new theme every week. This week’s topic: happiness.
Every week, you can receive a curated update on who-is-saying-what in the world of social science research by subscribing here. I’d love to hear what you liked or disliked, and if you have any suggestions. Email me at email@example.com.
You can read previous issues of Collidoscope here.
If you’re happy and you know it…believe a lie
Are happier people more gullible?
As populist politics and leaders gain traction across the world, the role of misinformation and fake news has been widely debated. Some have argued that it’s anger or disillusionment that makes people so ready to believe things that support their viewpoint – but new research suggests that might not be the case.
In his article in the Journal of Psychological Science, Joseph P. Forgas talks about certain experiments he conducted to try and work out when people are more likely to believe false information. His result is surprising – he found that people are more likely to be gullible when they’re happy.
If you’re not in a great mood, Forgas found, you’re more likely to pay attention to what you’re being told and think critically – a phenomenon called “depressive realism”. “…negative moods can trigger a more detailed, attentive, and data-driven processing style, and positive moods produce more creative, theory-driven, and heuristic thinking.”
The author relied on four different experiments to reach his conclusions. First, he tested the claim that people “often rely on simple heuristics such as familiarity and ease of processing (fluency) to decide whether to believe or disbelieve a claim with unknown truth value”. He found that mood does have an effect here: “negative mood eliminated and positive mood maintained people’s reliance on processing fluency as a heuristic cue indicating truth”.
Second, he looked at people’s tendency to infer meaning from statements that have none, such as “Good health imparts reality to subtle creativity”. Here too, people in a better mood were more willing and eager to find meaning, while those in negative moods were more dismissive.
Third, Forgas compared how people in different moods judged interpersonal deception. The result was the same. “For example, when rating the genuineness of positive and negative facial expressions displayed by professional actors, participants in a positive mood believed the expressions to be more genuine than did those in the neutral- and negative-mood conditions.”
In his last experiment, the author looked at gullibility on eyewitness accounts.
“In several experiments, we found that negative mood significantly reduced eyewitness gullibility. For example, students in a lecture hall first witnessed a staged aggressive incident between a lecturer and a female intruder. A week later, when in a manipulated negative or positive mood, eyewitnesses received misleading information (embedded in leading questions) about the witnessed encounter. Positive mood increased and negative mood almost completely eliminated eye- witness gullibility…”
Where does that leave us? Writing about Forgas’s work, Raj Persaud says in Project Syndicate:
“Some say that it is impossible not to like [Boris] Johnson once you have met him. Yet his likeability and talent for inducing a positive mood also conveniently deflect attention away from the more important question of his ability to govern. The affability of populist politicians such as Johnson may be the real secret of their success, but, according to this new research, it might also be the source of the danger they pose.”
The pursuit of happiness in a digital age
Can online connections make us as happy as in-person ones do?
They can’t, according to Efstratia Arampatzi, Martijn J. Burger and Natallia Novik. In an article in the Journal of Happiness Studies, they argue that friendships made on the internet cannot replace in-person (or what they call “real life”) connections, and can at best complement them.
“One of the key factors that affect happiness is the level of individual social capital, or an individual’s pattern and intensity of social contacts with other people,” they write. Given how we connect with people has changed dramatically since the spread of the internet, the authors decided to look at whether it is fair to say that people’s social contacts are on the decline.
Their research is based in the Netherlands, for people aged between 15 and 44. Their findings are based on a data set in which 1,339 individuals self-reported their happiness, internet use and individual social capital.
The authors found that the time spent on social media had an insignificant – though negative – impact on happiness. What they did find, though, was that people who felt isolated and lonely were likely to be less and less happy as the time they spent on social media increased.
“Although there is no relationship between excessive SNS use and happiness for young adults with a high quality of individual social capital, excessive SNS use negatively affects the happiness of individuals who feel lonely and dissatisfied with their social contacts.”
The frequency of in-person interactions with families and friends, however, did not moderate the relationship between social media use and happiness, they found.
This has led the authors to the conclusion that while online connections cannot replace those you have with the people you meet in person, watching other people’s lives play out on social media while you feel isolated yourself can have a negative impact. Given that social media envy has been widely written about – and experienced at one point or the other by any young person who uses the internet – their findings aren’t surprising.
Taxing to make people happier
Can a country’s taxation structure impact how happy citizens are?
In an article in the American Psychologist, Shigehiro Oishi, Kostadin Kushlev and Ulrich Schimmack look at taxation policies in the United States in the last 40 years to see how progressive taxation impacts income inequality and happiness. Public policy, they argue, shouldn’t be analysed only on the basis of its economic impact – we should also be paying attention to its psychological impact.
Based on existing research, the authors assumed that progressive taxation reduces income inequality, and years which see less income inequality are associated with more happiness. They then tested these assumptions.
First, they compared historical tax rate data with the Gini coefficient, a measure of inequality, and were proved right:
“As predicted, the degree of progressive taxation is strongly inversely associated with income inequality measured by the Gini coefficient… The more progressive the tax system, the less income in- equality there was in the United States. Specifically, a 10% increase in progressiveness of taxation (e.g., 20% to 30%) was associated with a 1.2 decrease in Gini coefficient (which ranges from 0 to 100).”
They then moved on to the next part of their hypothesis, and compared tax rates with self-reported data on happiness from General Social Surveys in the US. Overall, they found that while there was a positive correlation, it was statistically nonsignificant.
That changed, though, when they separated the data by different income groups.
“…the poorest 20% of Americans were happier when the income taxation was more progressive… Specifically, a 10% increase in progressiveness of income taxation was on average associated with a .012 increase in the 3-point scale’s self-reported happiness, or an increase of .24 of the standard deviation.”
Americans in the 20th-40th percentiles of the income distribution were also happier in years with more progressive taxation, the authors found. The correlation for the 40th-60th percentiles was positive but nonsignificant, and negative but nonsignificant among the richest 20% of Americans.
While Oishi, Kushlev and Schimmack use self-reported happiness data for their analyses, there have been others who argue that this data is non-comparable for inter-group analysis. Timothy N. Bond and Kevin Lang, for instance, have written about how different groups have different baselines when answering questions like ‘How happy are you: very happy, pretty happy or not too happy’.
Despite that, the authors’ analysis is useful because it looks at happiness indicators within the same income groups across different years. As they put it:
“Our most important finding…is that progressive taxation is not a zero-sum game where a large group of poor people benefit from a big loss of a small group of wealthy citizens. Rather, poorer citizens benefit without a notable loss in happiness among the wealthiest citizens. Reversing the current trend toward less progressive taxation in the United States might be an important tool in reversing the trend toward widening income inequality and declining happiness of poorer Americans.”
That’s all for this week! If you liked what you read, you can subscribe to this weekly newsletter here.