PS201 - Intelligence - Lecture 3

This third lecture in the intelligence series shifts focus from what intelligence is and how we measure it, to what intelligence test scores actually predict in real life. By the end of it, you should be able to critically evaluate the links between IQ and important life outcomes like education, job performance, and health; describe other factors that contribute to success beyond IQ; explain the "Flynn effect" — the fascinating phenomenon of IQs rising across generations — and discuss the possible reasons behind it.

The lecture is structured around three main areas: what does IQ predict, why are IQs rising over time, and what does "successful" intelligence really look like?

Let's start with what IQ actually predicts. It's worth setting the scene with an important note of caution first. Benson, writing in 2003, argued that the capacity of intelligence tests to predict intellectual performance is often overplayed, overstated, and over-emphasised. So while IQ is definitely useful, we should be careful not to treat it as the be-all and end-all. That said, there are several areas of life where it genuinely does predict meaningful outcomes.

The first and most intuitive one is education. General intelligence does correlate meaningfully with academic achievement. Jencks in 1979 conducted a meta-analysis — a study that combines results from multiple other studies — pulling together six longitudinal studies and finding correlations between IQ and academic achievement ranging from r = 0.40 to r = 0.63. To give you a sense of scale, a correlation of 0 means no relationship at all, and 1.0 would be a perfect relationship, so these are moderate to strong associations. Kaufman in 1990, and then Kaufman and Lichtenberger in 2005, reviewed the key papers in this area and found that the correlation typically lands around r = 0.50. But the most striking study on this is from Deary and colleagues in 2007, who conducted a prospective longitudinal study — meaning they measured IQ first and then tracked what happened later — with over 70,000 participants. They measured IQ at age 11 and then looked at how those participants performed in their school exams at age 16. The overall correlation was 0.69, which is quite strong. Breaking it down by subject, the strongest association was in Maths (r = 0.77), followed by English (r = 0.67), Geography (r = 0.65), and French (r = 0.64). Even subjects you might not immediately associate with "raw intelligence," like Music (r = 0.54), Drama (r = 0.47), and Art and Design (r = 0.43), still showed real positive relationships with IQ. The takeaway from Deary et al.'s 2007 work is that IQ at age 11 is a genuinely strong predictor of academic performance across a very wide range of subjects five years later, suggesting that whatever IQ tests measure, it broadly captures something relevant to learning and performing in school.

Now, why doesn't IQ predict academic performance perfectly? A few reasons. Partly, IQ tests also pick up on test-taking ability — things like time management, reading questions carefully, and keeping calm under pressure — which are skills in themselves but aren't purely about intelligence. And performance in school is influenced by many factors IQ doesn't capture: motivation, illness (even something as mundane as hayfever during exam season), quality of teaching, and specific subject abilities that aren't measured by general IQ tests. There's also an important and genuinely tricky question here that Neisser and colleagues raised in 1996: does higher intelligence cause better educational achievement, or does better education actually lead to higher intelligence? It's likely a bit of both, but it's a relationship that's harder to untangle than it first appears.

Moving on to the workplace — intelligence tests are also reliably associated with job performance, and in some cases IQ can actually be a better predictor of job success than more traditional recruitment measures. Hunter and Hunter in 1984 conducted a large meta-analysis of 32,000 workers and found a correlation between IQ and job performance of r = 0.54. Crucially, they compared this to other common recruitment methods and IQ came out on top: a candidate's CV correlated with job performance at only r = 0.37, their previous work experience at just r = 0.18, job interviews at r = 0.14, and educational qualifications at only r = 0.10. The takeaway here is pretty striking — IQ scores predicted job performance better than interviews, CVs, and even educational qualifications. This challenges a lot of assumptions about what makes a good recruitment process. Bertua and colleagues in 2005 then replicated this kind of analysis in a UK-specific context with over 13,000 participants, and found that IQ correlated with both job performance and training success at around r = 0.50 to 0.60. Interestingly, they also found that the strength of the relationship varied depending on what you were looking at — perceptual ability was the best predictor of job performance specifically (r = 0.50), while numerical ability was the best predictor of training success (r = 0.54). And the relationship also varied by job type: for professional occupations (like medicine or law), the correlation between IQ and job performance was as high as r = 0.74, whereas for clerical occupations it was only r = 0.32. The takeaway is that IQ is particularly powerful as a predictor in cognitively demanding jobs, but is less predictive for more routine work.

In terms of practical advantages for recruitment, Schmidt and Hunter in 1998 noted that while IQ is a good predictor of job performance on its own, combining it with other measures makes it even better. Adding tests of integrity (honesty and work ethic) to an IQ test increased predictive power by 27%, and adding work samples or structured interviews added 24%. The takeaway here is that IQ is best used as part of a broader recruitment process, not as a standalone magic number.

The relationship between IQ and health is perhaps the most surprising area of all. Back in 1932, every school child in Scotland born in 1921 took the same IQ test — a remarkable 89,498 children in total. This was repeated in 1947 for children born in 1936 (70,805 children). These datasets became extraordinarily valuable for later researchers. Deary and colleagues in 2004 looked at the 1947 cohort and found that people who had died by the time of the study had a lower average IQ at age 11 (mean of 97.7) compared to those who were still alive (mean of 104.6). That's a difference of about 7 IQ points, and the takeaway is sobering: childhood IQ score was meaningfully predictive of whether you would still be alive decades later.

Similarly, Batty and colleagues in 2009 used data from Swedish military conscription records — up to 2010, Swedish men were required to take an IQ test for national service — and found that IQ was associated with an increased risk of overall mortality. Interestingly though, this association wasn't explained by the obvious health-related factors you might expect, like blood pressure, body mass index, or cigarette smoking. Instead, it was education level that significantly mediated the relationship — meaning that part of the reason higher IQ is linked to lower mortality is because smarter people tend to get more education, which in turn leads to better health outcomes. This connects to a broader model (from Batty and colleagues in 2007) suggesting that IQ affects mortality through several pathways: influencing how well people prevent and manage disease and injury, shaping their socioeconomic position (higher IQ generally leading to better jobs and income), and influencing vulnerability to psychiatric illness. Finally, Calvin and colleagues in 2011 conducted a meta-analysis of 16 studies examining the IQ-mortality link and found that each increase of one standard deviation in IQ scores — that's 15 IQ points — was associated with a 24% lower risk of death. The takeaway from the broader body of health and mortality research is compelling: IQ appears to be a meaningful predictor not just of academic and professional outcomes, but of how long you live.

Beyond education, job performance, and health, Gottfredson in 1997 noted that general intelligence also predicts things like poverty, likelihood of being in prison, being divorced, and being unemployed. However, there is a very important caveat here — it is genuinely difficult to separate the effects of IQ from socioeconomic status, as the two are deeply intertwined, and we'll be coming back to this in the next lecture.

What about emotional intelligence? Higher emotional intelligence (EI) is associated with better health and wellbeing. Schutte and colleagues in 2007 conducted a meta-analysis of 44 studies involving around 8,000 participants and found that higher EI was associated with better physical health (r = 0.22) and better mental health (r = 0.29). Other studies have linked higher EI to better coping behaviours (Mikolajczak and Luminet, 2008), greater life satisfaction (Extremera and Fernandez-Berrocal, 2005), higher levels of happiness (Chamorro-Premuzic and colleagues, 2007), and more positive and less negative teacher-rated behaviour in children (Mavroveli and colleagues, 2008). When it comes to education and job performance, though, the evidence for EI is more mixed — reviews by Charbonneau and Nicol in 2002 and van der Zee and colleagues in 2002 found inconsistent results. One interesting idea that has emerged from this is the "compensatory model," proposed by Petrides and colleagues in 2005 and Cote and Miners in 2006, which suggests that EI becomes a more important predictor of success specifically in people who have lower general cognitive intelligence. In other words, for people who don't have a high IQ, emotional intelligence may step in and compensate, helping them achieve better outcomes than their IQ alone would predict.

It's also worth acknowledging some of the limitations of what IQ tests can tell us. Yes, there are lots of positive correlations with various important life outcomes, which can make IQ seem like a very powerful and complete tool. But the predictive strength of IQ tests does fluctuate depending on context, and IQ tests don't tell you everything. A notable example of this comes from the President's Commission on Excellence in Special Education (PCESE) in 2002, which argued that IQ tests were too limited in educational contexts — specifically, that they provide no information about what you should actually do to support a child's learning or develop an educational programme for them. However, Kaufman and Kaufman in 2001 pushed back on this, arguing that IQ tests must be administered by specially trained practitioners who would naturally take a broader, more holistic approach anyway — so the test result is just one piece of a wider assessment.

Now let's talk about the Flynn effect, which is one of the most fascinating phenomena in the whole of intelligence research. The basic finding is this: year on year, scores on intelligence tests have been going up, all over the world. To put this in startling terms — if a person with average intelligence from 1940 sat today's IQ test, they would be assigned an IQ of around 70. That's the level at which a learning difficulty would typically be diagnosed today. So either people today are dramatically more intelligent than those in 1940, or something else is going on.

The discovery of this effect came from how IQ tests are normed and updated. Because IQ tests are periodically revised and re-standardised, researchers can compare how people perform on old versus new versions of the same test. What they consistently found was that people score higher on older tests — for example, people who averaged an IQ of 100 on the new version of the WISC averaged an IQ of 108 on the old version. This suggests that population-level intelligence has been rising since the older test was normed.

The key researcher here is James Flynn. In 1984, Flynn looked at 73 studies involving around 7,500 participants, all of whom had taken two versions of the Wechsler or Stanford-Binet IQ test. He found that Americans had gained approximately 14 IQ points between 1932 and 1978 — that's roughly 0.3 IQ points per year. This was a significant finding, and it raised an important question about what was driving it. Jensen, in a personal communication with Flynn at the time, suggested that the increase might be down to better schooling, and if that were the case, you would expect the biggest gains to be in verbal and crystallised intelligence (Gc) — knowledge-based abilities. But Flynn expanded his studies to include non-verbal matrix tests that measure fluid intelligence (Gf) and looked worldwide. His seminal 1987 paper published data from 14 countries using a variety of verbal and non-verbal tests, later expanded to 20 countries in a 1994 paper. What he found was that the IQ increases were confirmed globally, and crucially, the biggest rises were not in verbal IQ (which rose around 9 points per generation) but in non-verbal, fluid intelligence (Gf), which rose around 15 points per generation. This was the opposite of what you'd expect if schooling were the main driver — which made the mystery even more interesting. The effect has been documented across many countries including Britain, the Netherlands, Belgium, Norway, and Israel. This phenomenon became known as the Flynn effect, named after James Flynn himself.

So what's causing it? The effect is too rapid to be explained by genetics — evolution simply doesn't work that fast — so it almost certainly has an environmental cause. Neisser in 1998 proposed five possible mechanisms. The first is schooling. People today attend school for longer than previous generations did, and years of schooling is a good predictor of IQ — Cahan and Cohen in 1989 found that for verbal IQ, years in school is actually a better predictor than age itself. However, the problem with schooling as the main explanation is that it would predict bigger gains in verbal/crystallised intelligence, whereas the Flynn effect is strongest in fluid intelligence. So schooling is probably a contributing factor but not the main driver.

The second possible explanation is test-taking sophistication — the idea that people today are simply more familiar with the kinds of tasks that appear on IQ tests. Flynn in 1998 acknowledged this, but Williams in 1998 pointed out that even taking the same IQ test twice only leads to gains of 5 or 6 points, which is nowhere near enough to account for the Flynn effect on its own. The third is child-rearing practices — specifically, the idea that parents today are more engaged in their children's intellectual development (Flynn in 1998 and Williams in 1998). Some support for this comes from the "Head Start" programme in the US, a 1960s initiative designed to support disadvantaged children. Head Start did produce immediate IQ gains of 7 to 8 points. However, a meta-analysis by McKey and colleagues in 1985 found that these gains were not sustained in the longer term — after 3 to 4 years, the IQ advantage had faded. The fourth explanation is the cultural and technological environment — Flynn in 1998, Greenfield in 1998, and Schooler in 1998 all suggested that the increasingly visual and complex technological world we live in might be training our brains in ways that improve certain types of intelligence. Visual media like films, documentaries, and advertisements require us to process complex visual information, which might improve the kind of visual analysis skills measured by non-verbal matrix tests — which would help explain why fluid intelligence has risen more than crystallised intelligence. However, there is currently little direct evidence for this "visual analysis hypothesis." The fifth and final explanation is nutrition. Lynn in 1990 and 1998 suggested that improvements in nutrition and healthcare could account for rising IQs — better-nourished brains are known to develop better, and malnutrition has been directly linked to poor brain development. One study by Benton and Roberts in 1988 gave children multivitamin supplements and found no increase in verbal IQ but a 9-point increase in non-verbal (fluid) IQ — which is intriguingly consistent with the Flynn effect pattern. However, this study had methodological issues and has not been successfully replicated, so it should be treated with some caution. Nutrition is also tangled up with other variables like socioeconomic status, parenting style, and general health, making it hard to isolate as the cause.

In the end, the debate in the literature is broadly between two camps: those who emphasise nutrition (as part of a broader package of improved health and nurturing environments) and those who emphasise cognitive stimulation (including schooling, child-rearing, and the visual and technological environment). There is evidence on both sides, and there is no clear winner. The most likely answer is that the Flynn effect is driven by a combination of these factors working together.

There is also an important and thought-provoking question the Flynn effect raises. Because the effect is most pronounced in tests of fluid intelligence like Raven's Matrices — which are specifically designed to be culture-free — we need to ask: if performance on these supposedly culture-free tests has risen so dramatically in response to cultural and environmental changes, can we really claim that they are culture-free? This is a genuine challenge to the idea that Raven's Matrices measure pure, untainted abstract reasoning.

Finally, it's worth noting that some research suggests the Flynn effect may be slowing down or even reversing in some countries. Sundet and colleagues in 2004 found that non-verbal IQ stopped rising in Norway after the mid-to-late 1990s. Teasdale and Owen in 2005 found that IQs in Denmark peaked in the late 1990s and then declined back to pre-1991 levels. And Flynn himself in 2009 found that in the UK, IQ gains had been declining since 1979, with small losses recorded for 12 to 15 year olds. Whether this represents a genuine ceiling being reached, or a shift in the environmental factors that were driving the rise in the first place, is not yet clear.

The final section of the lecture moves beyond standard IQ to what Sternberg in 2003 called "successful intelligence" — defined as one's ability to choose, re-evaluate, and attain one's goals in life within one's sociocultural context. This framework embraces three things that standard IQ tests largely ignore: creativity, wisdom, and giftedness.

On creativity, studies of creative individuals and processes are often organised around what Rhodes in 1961 and 1987 and Runco in 2004 called the "4 Ps": Person (the personality traits associated with creativity), Process (the thought processes and behaviours that underpin creativity), Press (the environmental pressures and conditions that promote or inhibit it), and Product (what creative individuals actually produce). In terms of personality, scales like the Composite Creative Personality Scale (Harrington, 1972 and 1975) have identified traits like being active, artistic, assertive, clever, curious, imaginative, insightful, and inventive as characteristic of creative people. Similarly, Goldberg and colleagues' International Personality Item Pool in 2006 includes items like "vivid imagination," "full of ideas," and "think up new ways of doing things" as markers of creativity. In terms of process, the first formal theory of creativity was proposed by Wallas in 1926 and involves five stages: preparation (focusing on a problem), incubation (letting it sit in your mind), intimation (beginning to feel that a solution is coming), illumination or insight (the creative idea emerging from unconscious to conscious awareness), and verification (applying the idea). However, the most influential theory of the creative process is Guilford's from 1967, which distinguishes between convergent thinking (working towards one correct answer) and divergent thinking (generating multiple possible solutions). Guilford argued that creativity is fundamentally about divergent thinking, and Glazer in 2009 agreed that divergent thinking is the best single example of what creativity looks like in practice. In terms of press — the environmental conditions — Runco in 2004 listed factors that promote creativity (freedom, autonomy, good role models, encouragement, absence of criticism, and having creativity rewarded) as well as those that inhibit it (lack of respect, bureaucracy, negative feedback, time pressure, competition, and unrealistic expectations). These are genuinely useful things to think about if you're trying to create an environment that fosters creative thinking. And in terms of products, the lecture points to some famous examples: Mozart's extraordinarily early musical development, Byron's enthusiasm, Shakespeare's literary brilliance (Steptoe, 1998), and Einstein — whose brain was found after his death to have a smaller ratio of neurons to glial cells than average (Diamond and colleagues, 1995), suggesting possible physiological differences associated with extraordinary creative and intellectual ability. Murphy in 2009 suggested that Salvador Dali would have met the diagnostic criteria for several personality disorders, which raises the question of whether there is a link between creativity and psychopathology. Sternberg in 2005 argues that creativity is not some rare gift reserved for a special few — it is an ability that anyone can develop and use. He describes many different aspects of "creative leadership," including things like willingness to take sensible risks, tolerance of ambiguity, questioning assumptions, redefining problems, self-efficacy, and the recognition that creative ideas don't sell themselves and need to be communicated persuasively.

On wisdom, the lecture covers Sternberg's Balance Theory of Wisdom, which suggests that wise decision-making involves balancing intrapersonal needs (your own), interpersonal needs (others'), and extrapersonal needs (the broader community or world), while also considering both the short and long term, and always keeping the common good in view. Wisdom also involves balancing between adapting to your environment, shaping it, and selecting a new one when necessary.

On giftedness, the lecture covers several perspectives. Terman in 1925 defined giftedness as extreme natural intelligence from a young age — essentially the top 1 to 5% of the population — and argued that gifted children should be identified early, accelerated through school, and treated as a national resource. Terman also believed that gifted children were superior across multiple dimensions including physical and moral ones, though this view is now regarded as quite simplistic. Renzulli in 1978 and Renzulli and Reis in 1997 proposed a broader definition — the famous "three-ring" model — arguing that giftedness is best understood as gifted behaviour rather than gifted individuals, and that it arises from the overlap of above-average ability, high levels of task commitment, and creativity. Importantly, Renzulli wanted to move beyond simply equating giftedness with high IQ. Konstantopoulos and colleagues in 2001 linked giftedness to factors like self-reliance, spending more time on homework and leisure reading, high parental aspirations, and socioeconomic status — suggesting that while giftedness has an innate component, it is also shaped by environment and opportunity. Tannenbaum in 1986 took a psychosocial view, arguing that giftedness is really about the ability to produce rather than consume information — specifically, to produce work that enhances the moral, physical, emotional, social, intellectual, or aesthetic life of humanity. His "sea star" model identifies five factors that shape whether high potential is realised: general cognitive ability, domain-specific ability, environmental factors (like learning experiences and expectations), chance and opportunity (access to resources and experiences), and other dispositional factors like persistence and self-esteem. Finally, Feldman in 1986 proposed a "developmentalist" view, arguing that giftedness in adulthood is essentially a "coincidence of forces" — biological and physiological factors combining with historical opportunities, social and environmental support (like excellent teachers), and broader evolutionary and cultural factors. Feldman also noted that gifted children by no means always emerge as gifted adults, and highlighted particular barriers faced by women historically in realising their potential.

To wrap everything up, the key messages from this lecture are these: intelligence is meaningfully correlated with academic achievement, job performance, health, and longevity — but it is far from the only thing that matters. IQs have been rising over time across the world (the Flynn effect), probably because of environmental factors like nutrition, cognitive stimulation, and broader sociocultural changes, even though the precise mix of causes is still debated. And being truly "successful" in life involves more than just high IQ — creativity, wisdom, and giftedness are also important, and all of these are shaped by a combination of innate ability, environment, opportunity, and effort