Sort reasonable claims about emotional intelligence from overstated ones, and ask the right questions of any study.
Posts about emotional intelligence (EI) at work circulate often. Some are partly right. Many take a modest research finding and stretch it into a big promise. You can sort one kind from the other with three questions, and you do not need a statistics degree to ask them.
The central debate in the research is what EI adds beyond measures psychologists already have. There are good measures of general intelligence and of the main personality traits, such as conscientiousness, agreeableness and emotional stability. Those measures already predict a fair amount about how people perform at work. The open question is whether an EI score tells you anything extra once you know someone's intelligence and personality.
The answer depends heavily on the type of EI test. Self-report and mixed-model scores overlap a lot with personality, so some of what they appear to predict is really personality. Ability-based scores overlap less with personality, but their links to everyday outcomes are weaker and less consistent. Lesson 1.2, "Why different emotional intelligence tests disagree", explains these test types, and it is the reason results depend on the test used. How much EI predicts after accounting for personality and intelligence is still argued over in the journals, and a post that skips this debate is selling something.
Studies linking EI to job performance usually find modest relationships. The relationships are real in many studies, but they are much smaller than popular claims suggest, and they vary with two things: the type of test used and the type of job.
A meta-analysis by Dana Joseph and Daniel Newman, published in 2010, found the link between EI and performance was stronger in jobs with heavy emotional demands, such as customer service and sales, where workers manage their own and other people's feelings all day. In jobs with less emotional demand, the link was weaker. Reading a frustrated customer matters more at a service counter at Changi Airport than in a role spent mostly on spreadsheets. So when someone tells you "EI predicts performance", a fair reply is: measured how, and in which jobs?
You get further by looking at individual skills than at a single EI score. Several skills have been studied directly, often more carefully than the umbrella term. Reappraisal, changing how you interpret an event so your feeling about it changes, has a large body of research, much of it from James Gross and colleagues at Stanford. Affect labelling, putting feelings into words, has been studied by Matthew Lieberman's lab at UCLA. You will meet both in detail in Modules 2 and 3.
These studies do not depend on settling what EI is. Each asks a narrower question: if people do this one thing, does a particular outcome change? The course is built around skills for this reason. You can argue about the definition of EI for years, but you can test in a week whether pausing before replying to an angry email improves the next day.
The first question is which measure was used: an ability test, a self-report questionnaire or a mixed-model tool. If a claim does not say, that is already a warning sign.
The second is what the high scorers were compared with. A finding that high scorers do better means little if they were also more experienced, more senior or higher on conscientiousness. Better studies check whether EI predicts anything after taking those factors into account, so look for whether the study controlled for them.
The third is how large the difference was. "Linked to" can mean a strong relationship or a barely detectable one, and popular articles rarely say which. If a source will not state the effect size, assume it was small until shown otherwise.
A week after the test brochures, Hui Min's director forwards a post to the HR team. In this invented example, the post claims EI explains more than half of success at work, that high scorers earn far more, and that the company should train EI into every manager. It has a chart, a confident tone and no link to a study. The director's note asks whether they can do something like this.
Hui Min works through the claims in order:
She looks for a published study behind each claim. She cannot find one for the "more than half" figure, so she drops it entirely. She drops any claim with no stated measure and no comparison. The earnings claim gives neither, so she cannot support it either. She keeps only what the evidence supports, with its limits: the relationships are modest, they depend on how the skills are measured, and they are stronger in emotionally demanding roles. She points to specific skills that have their own evidence.
Her rewrite says that studies link some emotional skills to job performance; that the link is clearer in roles with heavy emotional demands such as service and sales; that the links are usually modest and depend on how the skills are measured; and that specific skills such as reappraisal have their own evidence and can be practised.
The rewrite is less exciting than the original post. Hui Min could defend every word of it to a sceptical finance director, and it still justifies building training around specific skills. Any fair rewrite you write should meet the same standard: defensible word for word to a sceptic.
In the activity below you find a claim of your own and give it the same treatment. Keep only what the evidence behind it could carry.
Find one article or post that makes a claim about emotional intelligence. Rewrite the claim so it says only what the evidence behind it could support.
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