Overview – Van Leeuwen et al (2008)

Van Leeuwen, M., Van den Berg, S. M. & Boomsma, D. (2008) A twin-family study of general IQ. Learning and Individual Differences, 18, 76–88.

Van Leeuwen et al (2008) is a key study in the psychology of individual differences that investigated the extent to which genetic and environmental factors contribute to differences in intelligence. Van Leeuwen et al studied twins, their siblings, and their parents using intelligence tests to examine the relative contributions of genetic and environmental influences on IQ. The study found that genetic factors accounted for a large proportion of individual differences in intelligence, with environmental factors accounting for a smaller proportion of the variation. The study also found evidence that people tend to choose partners with similar levels of intelligence, providing support for phenotypic assortment. Overall, the study provided evidence that genetic differences are an important influence on why individuals differ in intelligence.

You can jump to different sections of this article via the links below:

• Aim
• Method (sampling and procedure)
• Results
• Conclusions
• Evaluation and methodological issues
• Relation to other psychological studies of individual differences

Van Leeuwen et al (2008)

Aim

The aim of Van Leeuwen et al (2008) was to investigate the extent to which genetic factors contribute to individual differences in intelligence.

Intelligence is broadly defined as cognitive ability – the ability to think, reason, learn, and solve problems. Intelligence is an example of an individual difference because people vary considerably in their cognitive abilities. These differences tend to run in families (e.g. intelligent parents, on average, tend to have intelligent children), which suggests a genetic component to intelligence. However, the fact that intelligence is related between family members does not necessarily mean that it is caused by genes because family members also share environments, experiences, and cultural influences.

One way of investigating the origins of individual differences is through twin studies. Identical (monozygotic) twins share ~100% of their genes whereas non-identical (dizygotic) twins share approximately 50% of their genes. So, if identical twins are more similar in intelligence than dizygotic twins, this provides evidence for a genetic influence on intelligence. However, twin studies can also reveal the influence of environmental factors, particularly when twins are raised in the same family.

Previous twin research had estimated that genetic factors accounted for around 25-50% of the variation in intelligence, with the influence of shared family environment appearing to decrease as children got older. Van Leeuwen et al used an extended twin-family design, including identical and non-identical twins, their siblings, and their parents to investigate the relative contributions of genetic and environmental influences on general intelligence. They also investigated processes such as assortative mating, cultural transmission, and gene-environment relationships. Van Leeuwen et al predicted that genes would make an important contribution to why some people have higher or lower intelligence than others.

So, in short, the aim of Van Leeuwen et al (2008) was to investigate how much individual differences in intelligence can be explained by genetic and how much by environmental factors.

Method

Van Leeuwen et al (2008) used an extended twin-family design, comparing intelligence test scores between identical and non-identical twins, their siblings, and their biological parents. The study also involved correlational analysis, as the researchers examined relationships between intelligence and genetic and environmental factors.

Participants and sampling

The researchers used a volunteer (self-selected) sample. Families from the Netherlands Twin Registry who met the selection criteria were invited to participate and those who agreed formed the final sample:

• 214 families with twins were invited to participate
  • 112 families (52%) agreed to take part
  • 103 of these families also had a full biological sibling who participated

The researchers invited families in which the twins were approaching their ninth birthday. The twins had a mean age of 9.1 years, while the siblings had a mean age of 11.9 years. The sample included identical and non-identical twin pairs, including male, female, and opposite-sex pairs:

Zygosity was determined using DNA testing for almost all twin pairs, with questionnaire information used for the remaining two pairs.

The parents also participated in the study. The mean age of the biological mothers was 41.9 years, and the mean age of the biological fathers was 43.7 years.

Families were excluded if the children had self-reported psychiatric problems, major medical conditions, special educational needs, or physical or sensory disabilities. Families were also excluded where children had conditions that would prevent them from participating in the associated MRI research.

Procedure

The study used an extended twin-family design, comparing intelligence test scores between identical and non-identical twins, full biological siblings, and their biological parents:

• The children completed Raven’s Standard Progressive Matrices (SPM) individually. This is a test of general intelligence consisting of 60 problems divided into five sets of 12 questions, with the problems becoming increasingly difficult. Children received verbal instructions and completed the test at their own pace.
• The parents completed Raven’s Advanced Progressive Matrices (APM), a more difficult version suitable for adults. They received written instructions and also completed the test at their own pace. Using different versions allowed the researchers to measure comparable general intelligence in both children and adults while ensuring that the test was appropriately difficult for each age group.

The researchers then analysed the relationships between the intelligence scores of different family members. They used different theoretical models to investigate whether the resemblance between spouses was better explained by phenotypic assortment – people choosing partners with similar levels of intelligence – or social homogamy – people with similar intelligence being more likely to meet because they live or work in similar environments. The researchers also examined gene–environment relationships to investigate how genetic and environmental factors may interact in explaining individual differences in intelligence.

So, in short, the parents and children took intelligence tests and the researchers looked for similarities and differences between the different family members’ results.

Results

The researchers converted participants’ scores on the Raven’s intelligence tests into IQ measures using the Rasch Model, a statistical method for estimating ability from test performance. The table below shows the number of participants in each group, their minimum and maximum scores, mean IQ, and standard deviation:

No statistically significant sex differences were found in IQ – either across the whole sample or within the parent, sibling, or twin groups. There was also no significant interaction between age and sex among the children.

The researchers found that identical (monozygotic) twins had higher correlations in IQ than non-identical (dizygotic) twins, siblings, and parent–offspring pairs. Siblings had greater variation in their IQ scores than twins, although this could partly be explained by the siblings being older. Older siblings also had higher mean IQ scores than the younger twins.

The correlation between spouses’ IQ scores was 0.33, which was statistically significant and quite high.

The researchers found that cultural transmission and non-additive genetic effects were not statistically significant. In other words, there was no significant evidence that differences in intelligence were explained by environmental influences passed from parents to children or by interactions between different genes. After correcting for measurement error, genetic differences accounted for about 67% of the differences in IQ between people.

The researchers also found evidence of a gene–environment interaction. Environmental factors accounted for more of the variation in intelligence among children with a genetic disposition towards lower IQ than among children with a genetic disposition towards higher IQ. In other words, the influence of the environment on intelligence depended partly on a child’s genetic characteristics, with environmental factors having a greater effect on children who were genetically more likely to have a lower IQ.

Conclusions

The results support the following conclusions:

Genetic factors are the main influence on individual differences in intelligence

The researchers concluded that genetic factors make a large contribution to individual differences in intelligence. Additive genetic effects – the combined effects of many different genes, each making a small contribution – accounted for approximately 67% of the variation in IQ after correcting for measurement error. This suggests that genetic differences are an important reason why some people have higher or lower levels of intelligence than others.

However, the findings also showed that genes and the environment interact to influence intelligence. Environmental factors had a greater influence on children who were genetically more likely to have a lower IQ than on children who were genetically more likely to have a higher IQ. This suggests that the same environment may not affect everyone in the same way, because its influence can depend partly on a person’s genetic characteristics.

Cultural transmission does not have a significant influence on individual differences in IQ

The researchers concluded that cultural transmission from parents does not make a significant contribution to individual differences in intelligence. In other words, the similarity between parents and their children in IQ was better explained by genetic inheritance than by parents passing on environmental or cultural influences that affect their children’s intelligence.

Phenotypic assortment better explains spousal resemblance than social homogamy

The researchers found a significant correlation of 0.33 between spouses’ IQ scores – i.e. people with higher IQs tended to have partners with higher IQs and people with lower IQs tended to have partners with lower IQs.

The researchers concluded that this similarity in intelligence was better explained by phenotypic assortment rather than by social homogamy. Phenotypic assortment means that people tend to choose partners who are similar to themselves (in this case in terms of intelligence). Social homogamy, in contrast, says that partners become similar because they live, work, or socialise in similar environments.

In simple terms, this means that people tend to pick partners of similar intelligence rather than the partners gradually converging on intelligence over time.

Evaluation

Research methods and techniques

Van Leeuwen et al used an extended twin-family design, combining a correlational approach with comparisons between identical and non-identical twins, siblings, and parents. This allowed the researchers to examine relationships between intelligence and genetic and environmental factors, as well as investigate possible explanations for similarities between spouses.

• Extended twin design: Including siblings and parents provided more information than a traditional twin study (i.e. just comparing identical and non-identical twins). Comparing identical and non-identical twins helped the researchers estimate genetic influences, while including parents and siblings allowed them to investigate cultural transmission and other environmental influences.
• Useful comparison groups: Identical twins share almost all of their genes, whereas non-identical twins share around 50% on average. Comparing the similarity of their IQ scores therefore provided a way of estimating the contribution of genetic factors.
• Standardised measurement: Intelligence was measured using Raven’s Progressive Matrices. Children completed the Standard Progressive Matrices, while adults completed the more difficult Advanced Progressive Matrices. Both tests provided a measure of general intelligence and were completed using standardised instructions.
• Can’t separate genetic and environmental influences: The estimates of genetic influence depend on assumptions about the environments experienced by the twins. For example, if identical twins are treated more similarly or have more similar experiences than non-identical twins, their greater similarity in IQ could partly be due to these environmental differences rather than their greater genetic similarity.
• Complex statistical modelling: The researchers used statistical models to estimate the contributions of different genetic and environmental factors. These estimates depend on assumptions made by the models, meaning that the precise percentages attributed to genetic and environmental influences should not be interpreted as directly measured quantities.

Population and sampling

The final sample consisted of 112 families from the Netherlands, including twins, siblings, and parents. The families were recruited through the Netherlands Twin Registry.

• Large family sample: The study included 112 families, providing considerably more participants than many classic twin studies and allowing the researchers to compare different types of biological relationships.
• Self-selected sample: Families volunteered to participate after being invited, so the participants may have differed from families who chose not to take part. Only 52% of the invited families participated.
• Restricted sample: Families were excluded if children had major medical or psychiatric problems, special educational needs, or physical or sensory disabilities. The findings may therefore not generalise fully to children with these characteristics.

Types of data

The study produced primarily quantitative data. Participants received numerical scores on Raven’s Progressive Matrices, which were used to estimate IQ and calculate correlations between family members.

• Precise: IQ scores allowed the researchers to precisely quantify the variable being studied (intelligence).
• Easy to compare: Quantitative IQ scores allowed for easy analysis and comparison using correlations and statistical models to estimate the relative contributions of genetic and environmental factors.
• Limited information about individual experiences: Numerical IQ scores provide little information about the specific environmental experiences that may have influenced each participant’s intelligence.

Representativeness and generalisability

The study provides useful evidence about genetic and environmental influences on intelligence, but there are some limitations when applying the findings to the wider population.

• Families from across the Netherlands: The 112 families came from different parts of the Netherlands rather than from a single local area, increasing the geographical diversity of the sample within the country.
• Different types of relatives: Including identical twins, non-identical twins, siblings, and parents made the sample more informative than a study based on one type of family relationship alone.
• Volunteer sample: Because families chose whether to participate, the final sample may not be fully representative of all families in the Netherlands.
• Limited cultural range: All participants were recruited in the Netherlands. The findings may therefore not apply equally to populations with substantially different cultural, educational, or environmental conditions.

Ethical issues

• Informed consent: Parents gave informed consent for themselves and their children, and the children also gave their own consent.
• Protection from harm: The cognitive testing involved completing intelligence tests and did not expose participants to significant physical risk.
• Confidentiality: The study collected DNA samples to determine whether twins were identical or non-identical. Genetic information is potentially sensitive, so appropriate confidentiality and handling of participants’ genetic data would be important.

Overall, the study raises no serious ethical issues and was approved by the Central Committee on Research involving Human Subjects.

Validity

• Internal Validity: Do the findings accurately identify the relative contributions of genetic and environmental factors?
  • Strong design for investigating heredity: Comparing identical and non-identical twins provides a useful way of estimating genetic influences because the two types of twins differ in their degree of genetic similarity while generally sharing a family environment.
  • Extended family information: Including siblings and parents provided additional information that helped the researchers distinguish genetic transmission from environmental and cultural transmission.
  • Cannot establish direct causation: The study was not a true experiment, so the researchers could not manipulate genes or environmental conditions. The estimated genetic and environmental contributions are therefore based on patterns of similarity and statistical modelling rather than direct experimental evidence.
  • Environmental factors are difficult to isolate: Family members share many aspects of their environment, making it difficult to identify exactly which environmental experiences contribute to differences in intelligence.
• Ecological Validity: Do the findings relate to intelligence as it exists in real life?
  • Real-world participants: The study measured intelligence in children and adults living in their normal family environments rather than creating an artificial environment specifically for the research.
  • Established intelligence tests: Raven’s Progressive Matrices measure general reasoning ability and can therefore provide a meaningful measure of an important aspect of real-world cognitive ability.
  • Intelligence is broader than one test: Raven’s tests measure particular aspects of cognitive ability – particularly reasoning and problem-solving. However, IQ scores from these tests may not capture every aspect of intelligence relevant to everyday life.

Reliability

• Internal Reliability: Is the measurement consistent within the study?
  • Standardised intelligence tests: Raven’s Progressive Matrices use standardised questions and instructions, making the measurement of intelligence consistent across participants.
  • Good test-retest reliability: Raven’s Standard Progressive Matrices (children) has reported test-retest reliability of approximately 0.88 and the Advanced Progressive Matrices (adults) has reported reliability of approximately 0.91. This suggests the measures of intelligence were consistent and reliable.
• External Reliability: Could the study be repeated and produce similar findings?
  • Replicable measures: Raven’s Progressive Matrices are standardised tests that can be administered to other groups using the same basic procedure so the intelligence testing is easy for other researchers to replicate.
  • Large family dataset: The inclusion of 112 families and several types of relatives provides a substantial amount of data for statistical analysis and reduces the likelihood that the findings were based on one or two unusual families.
  • Statistical estimates: The estimated contributions of genetic and environmental factors depend partly on the particular sample and statistical models used. A replication using a different population could therefore produce somewhat different estimates.

Ethnocentrism

The study was conducted using families from the Netherlands, meaning that the findings were obtained within one particular cultural and educational context.

• Western sample: The Netherlands is a Western country with particular educational, social, and cultural conditions. The relative contribution of genes and environment to intelligence may not be identical in populations living in very different environments.
• Biological processes: The study investigated genetic influences on intelligence, which are not specific to Dutch culture. The basic principles of genetic inheritance are applicable across human populations.
• Environmental differences still matter: Although genetic inheritance is a biological process, its expression can be influenced by environmental conditions. Findings from Dutch families should therefore not automatically be assumed to apply in populations with substantially different educational or environmental conditions.

Evaluation summary table

Relation to the psychology of individual differences more broadly

Van Leeuwen et al (2008) contributes to the psychology of individual differences by demonstrating that people vary in their intelligence and that these differences are influenced substantially by genetic factors. By comparing identical and non-identical twins, siblings, and parents, the study provided evidence that genetic differences account for a large proportion of the variation in intelligence. The study also showed that environmental factors contribute to individual differences, although they had a smaller overall influence than genetic factors.

The table below summarises how this study compares with other core studies in this area and evaluates its contribution and current relevance: