u/darkmoonselena

RIOT IQ's Chief Scientist, Dr. Russell Warne, used a method that jointly models test item responses and item response times. This study has been submitted for peer review at a journal, but it was also released as a public pre-print today.

Highlights of the results:

➡️ All 9 core RIOT subtests conform well to model expectations. Where there is misfit, it is in the hardest items, most of which few examinees see anyway. The images above displays the best, median, and worst fitting items for the fluid (first image) and spatial (second image) subtests. Even when the departures are noticeable, the models still do a good job at anticipating how long examinees will take to respond to test items.

➡️ The correlations between subtest performance and response times are spurious and are the product of a person's natural test-taking speed (which is not cognitive) and item characteristics. In other words, how long it takes someone to respond to test items cannot be used to measure intelligence.

➡️ But response times still contain valuable information. They can be used to identify unusual response behaviors, such as being rushed by a tight time limit or cheating. There was very little unusual response behavior in this sample, with the exception of the Figure Weights subtest, which has 17.5% of its examinees take statistically significantly longer to respond to items than the model expected.

There are other interesting findings in the preprint, and you are encouraged to check it out.

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There's new progress on understanding the genetics of cognitive abilities! Diego Alejandro Londono-Correa and his coauthors examined the molecular genetics of cognitive abilities and how they relate to personality and mental health conditions. Results from this important GWAS include:

➡️ Overlap for genetic loci associated with fluid intelligence, crystallized intelligence, and reaction time. but there are also DNA variants that are only associated with one ability. We can't just assume that a gene that impacts one cognitive ability will impact others.

➡️ Among loci with known functions, most are expressed in the brain. But there are some surprises, including DNA variants association between crystallized intelligence possibly being expressed in the ovaries (2nd image).

➡️ Different genetic correlations with mental health conditions (3rd and 4th images). For example, there is a positive genetic correlation between crystallized intelligence and autism spectrum disorder, but a negative genetic correlation between crystallized intelligence and ADHD. This may explain why some common DNA variants associated with mental health conditions remain in the human gene pool: maybe some of these variants are sometimes beneficial.

➡️ Personality traits also showed differing genetic correlations with the cognitive traits. The strongest genetic correlation was between crystallized intelligence and openness to experience (r = .465; 4th image). These correlations give important clues into the development of these cognitive abilities and how they build phenotypes like knowledge, reasoning ability, etc.

➡️ New genetic loci associated with crystalliezed intelligence.

This study shows convincingly the value of examining the genetics of broad cognitive abilities--instead of just focusing on general intelligence. It also provides insight into the genetics of intelligence and how it relates to other abilities.

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IQ matters, but it is not the only cognitive ability that matters. One of the most important is quantitative ability and a new article explores its genetic origins and impacts.

The authors (including Emily Willoughby) conducted a GWAS to identify genetic variants that are associated with people's self-reported (1) math ability and (2) highest math class taken. This measure of self-reported quantitative ability was found to be associated with 53 variants scattered throughout the genome (pictured above).

Generally, these portions of the genome are associated with brain development, which shows that even these self-report variables are measuring something cognitive.

What's more interesting is that the genes with known function relate to brain functioning or development at the microscopic level (e.g., neurotransmitter functioning, dendrite and axon development). The quantitative ability polygenic score does NOT correlate genetically with overall brain size (even though the IQ and educational attainment polygenic scores do).

The polygenic scores don't just measure something important in biology; they also have practical implications. A higher polygenic score for quantitative ability has a positive genetic correlation with working as a software analyst, mathematician, and physicist and a negative genetic correlation with working as a writer, NGO/union organizer, or government official.

This study provides tantalizing clues about how genes get translated into behaviors and real-world outcomes. Genes are just portions of DNA. They don't think, and they don't have any awareness of the outside world. Studies like this one shows how genes may influence cognitive traits and life outcomes: by building a better functioning brain, which then can learn from and respond better to the environment.

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A new article in the ICA Journal by Thomas R. Coyle explores the development of intraindividual differences in cognitive abilities, called "tilt." The findings show the importance of understanding people's relative strengths and weaknesses.

Coyle investigated the relative strengths of adolescents' mechanical, spatial, and academic strengths (or weaknesses). Among his findings:

➡️ Sex differences were larger for mechanical tilt, with more males showing a relative strength in mechanical abilities (compared to academic abilities). But for spatial tilt, there were "negligible" sex differences.

➡️ Processing speed and general intelligence (g) were important in developing mechanical tilt. The influence of processing speed and g were stronger for males than females.

➡️ Sex differences in spatial tilt do not increase with age, indicating that the maturation and education processes do not have an impact on the relative numbers of males and females showing greater spatial tilt.

The results were generally supporting of investment theory, which is that individuals' strengths are (partially) a product of what they invest their time into learning. It also supports cascade theory, which states that the development of tilt is mediated by both g and processing speed (not just speed).

In the real world, this study has some implications because relative strengths and weaknesses are very common. This study shows that, to a degree, tilt may be malleable. In other words, it may be possible to work on your weaknesses and bring them closer to your typical cognitive ability level. It also raises the possibility that schools could see academic benefits from training students' spatial abilities, which are important for many STEM fields and vocations.

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Good news for efforts to raise educational achievement in developing countries! A new article in the ICA Journal uses cross-national data to find evidence that improved nutrition can increase academic achievement scores.

The authors compared average height differences between males and females in over 100 countries, which is an indirect measure of nutritional quality before adulthood: because males are more vulnerable to stunting, countries with a larger male-female height difference have better nutrition. These differences were then compared to average academic achievement scores for the different countries to find if there was a relationship.

The results indicate that countries with a larger male-female height difference do indeed have higher academic achievement scores. However, this relationship levels off after an 8% height difference (grey scatterplots in 2nd image), but it's still large: a 1% difference in male-female heights is associated with a d = .2 to .3 increase in academic achievement. This provides circumstantial evidence that improving nutrition in developing nations will provide educational benefits down the road. However, the leveling off also shows that there are limits to the cognitive gains that can be expected from improved nutrition.

The results were replicated with datasets at the region/state level within 5 of 7 countries (see 3rd image). But, for unknown reasons, it did not replicate within Russia or India. Additionally, this study does not state how much of the increase in test scores is due to actual nutrition, or to other influences that might also emerge at the same time as nutrition improvements, such as increased economic development or a better education system. The study is very informative regarding about the origin of cross-national differences in academic achievement.

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The ICA Journal has a new article by Dr. Richard Haier about the connections between IQ scores, genes, and brain functioning (with some evolutionary biology and environmental influence thrown in, too).

It's an information-packed article that connects findings from different branches of psychology, neuroscience, and biology to show (1) how humans evolved such smart brains and (2) the biological process that connects each individual's genetic blueprint to brains that show individual differences in intelligence.

Here are some highlights:
➡️Regions of the brain that have experienced large changes in recent evolutionary history seem to be more important for intelligence.
➡️There has been a evolutionary tradeoff: in exchange for a larger, smarter brain (and enhanced regions of the brain), the brain has been more hungry for energy. Balancing these two conflicting demands has been an evolutionary tightrope that humans seem to have walked.
➡️There are specific genes (discussed in the paper) with common variants that are very likely to have biological functions that result in smarter brains. The function of these genes are understood, and though their relationship with IQ is modest, they give us important clues into how genes result in smarter brains. (After all, the genes don't whisper the answer to an IQ test question into your ear. Any impact they have on IQ must be via biology.)
➡️Fetal development seems to be fine tuned for building a smart brain (under normal conditions), especially in the timing of uptake of polyunsaturated fatty acids during the third trimester.

There is a lot more in the article. It doesn't answer every question about how intelligence develops (either in the species at large or in individual humans), but it pulls together a great deal of interesting evidence in one place.

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A new article written by Thomas Coyle and published in the ICA Journal provides more information about how personal strengths and weaknesses in academic abilities develop.

Using archival data, Coyle examined "tilt," which is the relative strength someone has in either technical or academic abilities, or in math vs. language. Previous research had already shown that tilt increases through adolescence, meaning that the difference between a person's strengths and their weaknesses grew larger over time. The question is whether this change is a linear effect, or whether the magnitude of tilt increased with age and processing speed levels (i.e., had nonlinear effects).

The results indicated that effects were mostly linear, indicating that changes in tilt are mostly consistent from one age to another or from one processing speed level to another. However, there were some interesting exceptions:

Processing speed had a non-linear effect on math and verbal tilt, indicating that a faster mental speed facilitates building these academic abilities. There was also a weak age non-linear effect, but it is much weaker.

This paper provides more evidence for the importance of considering test subscores in addition to global scores (like IQ). Because tilt is not related to IQ, it has unique predictive power and can provide insights that overall scores cannot.

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This article from the ICA Journal examines sex differences in achievement in reading, math, and science across different countries and achievement levels.

Using data from the international PISA assessment, the authors investigated whether within-individual strengths and weaknesses impacted overall sex differences in these topics.

Key findings:
- Boys show consistent edges in math (0.33-0.71 SD) and science (0.19-0.39 SD) strengths; girls dominate reading (0.52-0.94 SD).

- In countries with more gender equality, the sex differences in math, science, and reading are wider than in less equal countries. This is a phenomenon that is the exact opposite of what feminist and culture-only theories of sex differences predict and is known as the "gender equality paradox.:

- For the most part, the same sex differences are observed among high, average, and low achievers (second photo).

Because it focuses on inter- and intra-individual differences, this article can shed light on how sex differences develop. Gender egalitarianism seems to encourage adolescents of both sexes to develop pre-existing strengths in reading and science even further (third photo). This occurs, despite the fact that average achievement in all subjects tends to be higher in these countries. In a way, "the rich get richer" and "the poor get somewhat less poor."

Finally, high-achievers have the same intra-individual strengths and weaknesses that the rest of the population does: females generally having their greatest strength in reading and males in science and math. As a result, even though these females have high math and science achievement, it's still usually lower than their reading achievement. The authors theorize that this may be one reason why bright women choose non-STEM careers: they have other options (e.g., verbal careers) that draw on their greatest strengths.

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This is the first peer-reviewed article using the RIOT IQ data published in a scholarly journal. In this study, Dr. Russell Warne analyzed how response times on IQ test items related with performance on the same questions. Some findings include:

- Each person has a default test-taking speed that is most unrelated to test performance. But the nature and strength of that relationship varies across tasks.

- On verbal subtests (e.g., vocabulary), fast responders tend to be more accurate. In other words, you either know the answer quickly or you don't know it at all.

- On fluid and spatial reasoning tasks, the reverse is true. Slower responders are more accurate. This is an artifact of these items being longer and more complex, especially as they get more difficult. (Training people to take more time on these items won't improve their score.)

- It is possible to identify people with unusual response patterns on the test, which can help flag cheaters or careless responders.

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The heritability of general is well established at ~50%. But what about more specific abilities? A meta-analysis of nearly 750,000 twins reveals fascinating results:

- Specific cognitive abilities average 56% heritability, which is about the same as for general intelligence. But there was a substantial variability, ranging from 39% for auditory processing to 64% for quantitative knowledge (see 2nd image).

- Unlike intelligence, specific cognitive abilities don't have an apparent developmental trajectory in heritability. Instead of increasing with age, specific cognitive abilities seem to maintain the same level of heritability at different age spans.

- The heritability of specific cognitive abilities seems to be independent of the genetic influence of general intelligence.

- Specific abilities within the same category sometimes differ in their heritability. Reaction time heritability was 42%, but processing speed heritability was 64%, even though both are classified as "mental speed."

- Substantial heritability does not rule out important environmental effects. Shared environmental influence was as high as 26% for knowledge scores and 20% for fluid intelligence.

This meta-analysis isn't just useful as a research summary. It also reveals the potential for future research. The authors point out that some abilities have little or no research on their heritability, others don't have enough information at some age ranges to draw conclusions about developmental trajectories. This is meta-analysis is definitely not the last word on this topic.

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Raise a glass to the newest study in the ICA Journal from Maximilian Krolo and Timothy Bates, who find that smarter people know more about wine.

In a sample of 525 respondents, IQ and wine knowledge were positively correlated (r = .31), and this relationship did NOT diminish after controlling for exposure to the wine industry or drinking habits.

If you're not a sommelier, this correlation doesn't matter much in real life. But the study has a lot of theoretical importance. Wine knowledge is complex, sophisticated, not taught in schools, and has little practical application for most people. This undermines the theory that smarter people know more facts because they have economic incentives to learn more or because they attend school longer.

The people who knew the most about wine were those who had both (1) high IQ and (2) exposure to the wine industry. This likely means that exposure to a knowledge domain occurs that smarter people benefit more from that environment than less intelligent people.

Cheers to the authors!

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It's a classic "chicken and the egg" problem: does high intelligence cause better educational outcomes, or does succeeding in school cause improved performance on intelligence tests?

A study in Germany investigated this question with six longitudinal samples and found that the relationship between fluid intelligence and academic achievement is reciprocal. In other words, there is a feedback loop in place:

high fluid intelligence -> higher academic achievement -> higher fluid intelligence test performance -> higher academic performance -> etc.

As the authors stated, "Not only did fluid intelligence foster the development of achievement; achievement also fostered the development of fluid intelligence.... any measure of prior achievement is already a function of that person's fluid intelligence (p. 6)

This feedback loop applies to both math and reading achievement and for both males and females.

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A new study in the ICA Journal investigates the utility of general cognitive ability (g), specific cognitive abilities (s), individual tests, and personality traits for predicting college GPA in college graduates. The findings:

• g is the best single predictor of college GPA.
• The only personality trait with predictive power was conscientiousness.
• After controlling for g, almost all individual tests had little predictive power. This means that when the individual test scores did predict college grades, it was because the test was measuring general intelligence.
• There was a conscientiousness x g interaction, but it had no practical significance. This means that the effects of being smart and being conscientious are additive. You don't get an extra academic boost from being both smart and conscientious.

From the authors: "Those looking to predict college performance would do well to use a g-loaded predictor, instead of predictors in sub-areas or domain-specific abilities" (p. 14).

The general findings support previous work and supports the mainstream view that (1) IQ is a powerful and (2) personality covers important non-cognitive behaviors that IQ tests don't measure. That can give researchers and the public more confidence in using these tests when making predictions.

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