A recent study published in Intelligence & Cognitive Abilities suggests that specific mental skills, such as technical knowledge or math and verbal abilities, play a significant role in predicting a person’s future income, education, and career path. The research provides evidence that these specific cognitive abilities are at least a third as important as general intelligence in shaping a person’s social and economic standing. This implies that educational and career guidance programs might benefit from looking beyond overall intelligence scores to help people find paths suited to their unique strengths.
Tobias Edwards, a postdoctoral scholar in behavioral genetics and individual differences at the University of Minnesota, explained the motivation behind the research. “Intelligence is multidimensional,” Edwards said. “There is your overall performance on cognitive ability tests, known as general intelligence, and then there are your relative strengths and weaknesses, known as specific abilities.”
To illustrate this concept, Edwards noted that mental profiles can vary widely among individuals. “For example, someone who generally scores average, but shows strong performance in verbal abilities can be said to have high verbal specific ability, but an average level of general intelligence,” he said. General intelligence represents an individual’s overall capacity to solve problems, reason, and learn.
Psychologists often estimate this underlying capacity using a standardized metric known as an Intelligence Quotient, or IQ score. An IQ score is derived from cognitive tests and serves as a practical measure of a person’s general intelligence. Higher IQ scores consistently predict higher socioeconomic status. Socioeconomic status refers to a person’s class standing, usually measured by a combination of education level, income, and job prestige.
Standard cognitive tests also capture specific abilities, such as how fast someone processes information, their vocabulary, or their mechanical knowledge. Early intelligence research noticed that performance on all cognitive tests tends to be positively correlated. If someone does well on a math test, they tend to do well on a vocabulary test. This phenomenon implies the existence of a general factor of intelligence that influences performance across all mental tasks. However, test scores also capture domain-specific abilities that operate independently of general intelligence.
The authors of the new study argue that past research looking at specific abilities frequently used flawed mathematical methods. These prior studies often relied on calculating the difference between two test scores, such as subtracting a person’s verbal score from their math score. This difference is known as a tilt. The researchers assert that the tilt approach makes it impossible to know which specific ability is actually driving a person’s life outcomes.
The researchers note that the tilt method also fails to properly separate the influence of overall general intelligence from the specific skill being measured. Because of these methodological issues, many experts assumed that specific abilities offered almost no extra predictive power beyond general intelligence. “There is a common perception among intelligence researchers that general intelligence matters a lot more than specific abilities in predicting life outcomes,” Edwards said.
“I wanted to put that view to the test, at least with regard to socioeconomic outcomes: income, occupation, and education,” Edwards said. “I found that, collectively, specific abilities are roughly a third to a half as predictive as general intelligence for predicting these outcomes.” The authors aimed to precisely quantify the importance of specific abilities using more advanced statistical models to understand how cognitive strengths guide occupational choices.
The researchers analyzed data from two large, nationally representative samples in the United States. They used the National Longitudinal Surveys of Youth from the years 1979 and 1997. The 1979 group included 11,914 participants aged 14 to 22 at the start, and the 1997 group included 7,008 participants aged 12 to 16. Both groups completed the Armed Services Vocational Aptitude Battery, a multiple-choice test used by the military to assess mental skills and guide career placement.
This battery includes ten subtests that measure areas like arithmetic reasoning, paragraph comprehension, general science, and knowledge of electronics or auto repair. The researchers adjusted all test scores to account for differences in sex, self-identified ethnicity, and the age at which participants took the test. The scientists then used a statistical technique called factor analysis. This process allowed them to isolate overall general intelligence from three specific abilities, which they labeled as tech, speed, and a combined math-verbal factor.
The tech ability involved practical vocational skills, measured by tests of auto, shop, and electronics knowledge. The speed ability measured how fast individuals completed simple mental tasks, such as translating numbers into letters. The math-verbal factor captured relative performance between mathematical and language-based tests. To track life outcomes, the authors looked at the participants’ highest level of education completed and their self-reported income over many years.
The researchers also calculated the prestige of the participants’ occupations. They assigned each job a socioeconomic index score, which is a weighted average of the typical income and education levels of people working in that occupation. The data included information on family relationships, allowing the authors to identify full siblings. By comparing siblings who grew up in the same household, the researchers could control for the effects of shared family upbringing and parental background.
The scientists found that specific abilities are highly relevant to predicting long-term socioeconomic status. They calculated that specific abilities have between 30 percent and 57 percent of the importance of general intelligence in predicting education, income, and job prestige. These associations remained even when comparing siblings. This suggests that shared family environments do not completely explain the link between specific mental skills and life outcomes.
The influence of these cognitive abilities changed over the lifespan. Before the age of 25, general intelligence had a very small effect on a person’s income, but this effect grew substantially as people aged. The tech ability showed a reversed pattern, predicting positive income during a person’s early twenties before becoming neutral or negative later in life. Despite the shifting effects on income, the tech ability consistently predicted lower educational attainment and lower overall occupational prestige across both generations.
The effects of the tech ability on income also differed by sex. A higher tech ability tended to predict greater income in men, but lower income in women. The effects of the speed and math-verbal abilities were less consistent across the two different generations, showing varying associations with income and education. The math-verbal factor predicted higher education and job prestige in the 1979 group, but it only predicted higher income in the 1997 group.
The study also provided evidence that people group into specific occupations based on their cognitive strengths. The average abilities in different occupations generally aligned with common stereotypes. Mechanics, construction workers, and precision metal workers scored highly in tech ability. Lawyers, judges, and religious workers showed low tech ability.
Professions like engineering, medicine, and computer science were associated with a high level of math-verbal ability. Occupations heavily reliant on administrative tasks, such as secretaries and typists, showed high speed ability. Agricultural workers and cleaners tended to score lower on the speed ability.
The scientists calculated the degree to which occupations cluster around these cognitive abilities. The strongest clustering occurred for general intelligence, meaning jobs are highly sorted by overall brainpower. However, the clustering around specific abilities was also substantial. The clustering of men into specific jobs based on their tech ability was nearly 80 percent as strong as their clustering based on general intelligence.
The causal relationship between specific abilities and socioeconomic outcomes remains uncertain. “Our study could quantify prediction, but it could not determine causation,” Edwards said. “It is unclear to what extent specific abilities influence life outcomes.”
Other factors might explain the associations observed in the data. “An alternative explanation for our findings might be that our interests in youth, or the school subjects we like, could simultaneously affect our specific abilities as well as our careers,” Edwards said. An individual who likes cars might spend time learning about them, scoring higher on the automotive test primarily because of their pre-existing interests.
Another potential limitation is that the tests used heavily featured technical and mechanical questions. These topics are not usually found on standard intelligence assessments. This means the high predictive power of the tech ability might not appear in studies that rely exclusively on traditional cognitive tests. The statistical structure of the specific abilities also changed slightly between the 1979 and 1997 survey groups.
These changes suggest that specific mental categories might shift over time or vary between different formats of a test. Model misspecification could also be a factor, meaning the statistical categories created by the researchers might mix together slightly different underlying mental traits. If the categories are not perfectly accurate, the measured effects might be slightly distorted.
Future research needs to explore the causal links between personal interests, specific mental abilities, and later social status. Understanding exactly how different cognitive profiles interact with the economy could help educators tailor school curricula to develop the most useful skills for students.
The study, “More Than General Intelligence: Cognitive Abilities and Class Structure,” was authored by Tobias Edwards and Colin G DeYoung.