Is the Ability to Make an Effort Also a Talent? The Heritability of Grit, Self-Control, and Motivation to Learn, and How Far These Traits Can Be Changed

What does “effort over talent” assume?

When people compare talent and effort, they usually treat the two as separate things. Talent is something given at birth, and effort is something a person chooses. Both the encouragement that “hard work can make up for a lack of talent” and the criticism that “that person did not try hard enough” rest on this division.

The question then becomes where the ability to keep making an effort comes from. It is not obvious that the difference between people who can keep practicing and people who cannot is determined only by personal choice. Twin studies have reported that genes are also involved in this difference. If the tendency to make an effort also contains differences present from birth, the division between talent and effort itself no longer holds.

This note examines this question using the academic literature. The construct problems of grit are discussed in Where Are the Seeds of Novelty Found? Surprise, Rereading, and Novelty That Is Only Apparent, and the relationship between grit and creative achievement is discussed in What Does It Take to Produce Novelty Now? Separating Traits, Attitudes, Stances, Abilities, and Skills. Here, grit is treated as one indicator for estimating the heritability of the tendency to make an effort.

Scope and method

• Topics: the heritability of traits related to effort (grit, conscientiousness, self-control, motivation to learn, and amount of practice), the relationship between grit and conscientiousness, the heritability of practice, causality in the association between effort and achievement, the limits of interpreting heritability (gene-environment interaction, genetic nurture, and within-family estimates), replications of willpower (ego depletion) research, and the effects of growth mindset interventions.
• Term: heritability is the proportion of the differences between people, in a given population and a given environment, that corresponds to genetic differences.
• Period: from classic papers (Turkheimer, 2000; Duckworth et al., 2007) to 2026.
• Corpus: 41 sources (source/review/effort-talent-heritability/papers.md). The corpus includes twin studies and their meta-analyses, molecular genetic studies, multisite preregistered replications, meta-analyses of interventions, and papers responding to them. The search collected 42 sources; one theoretical paper whose full text could not be obtained was removed, and one paper reviewing replications of willpower beliefs was added during verification.
• Verification: for 35 sources, the full text was obtained. The numbers, direct quotations, and mechanism claims used in this note were checked against the relevant passages. For six sources (Vukasović & Bratko, 2015; Carter et al., 2015; Job et al., 2010; Friese et al., 2019; Dang et al., 2025; Burnette et al., 2023), the full text could not be obtained through three or more routes; these sources were used only within the scope of their abstracts and are attributed to the abstracts in the text.

How heritable are traits related to effort?

Polderman et al. (2015) integrated twin studies of 17,804 traits reported in 2,748 publications, covering 14,558,903 partly dependent twin pairs, and estimated the heritability of human traits overall at 49%. For 69% of the traits, the resemblance of twins was consistent with a model in which only the additive effects of genes operate. The traits discussed below are compared with this figure.

Traits related to effort do not depart from this reference point. Willems et al. (2019) meta-analyzed 31 twin studies (more than 30,000 twins) and estimated the heritability of self-control at 60%. The monozygotic twin correlation was 0.58, the dizygotic twin correlation was 0.28, and heritability did not differ by gender or age. However, it differed by informant: parent-reported self-control showed higher heritability than self-reports or observations.

The same applies to grit. In 4,642 twins aged 16 in the United Kingdom, Rimfeld et al. (2016) estimated the heritability of the perseverance-of-effort facet of grit at 37% and that of the consistency-of-interest facet at 20%. No influence of the shared environment, such as the family that siblings have in common, was found. Motivation to learn shows a similar pattern. Kovas et al. (2015) studied enjoyment of learning and self-perceived ability in approximately 13,000 twins aged 9-16 from six countries. Genetic factors explained approximately 40% of the individual differences in both, and shared environmental factors, such as the home or the classroom, did not contribute to twin similarity. These results were largely consistent across ages, school subjects, and countries. For personality in general, the abstract of Vukasović and Bratko (2015) reports an average heritability of 0.40 in a meta-analysis of 62 effect sizes (more than 100,000 participants), and 0.47 when only twin studies are considered.

These results fit what Turkheimer (2000) summarized as the first law of behavior genetics: “All human behavioral traits are heritable.” The tendency to make an effort was not a special domain separate from height or intelligence.

How does grit differ from conscientiousness?

Grit became widely known as a concept representing the idea of “effort over talent.” Duckworth et al. (2007) defined grit as “perseverance and passion for long-term goals” and showed that grit accounted for an average of 4% of the variance in success outcomes, such as educational attainment, grade point average, retention at a military academy, and ranking in a spelling bee. Grit was not positively related to IQ and was highly correlated with conscientiousness.

However, later research questioned whether grit measures a new aspect of the tendency to make an effort. In Rimfeld et al. (2016), the correlation between grit perseverance and conscientiousness was 0.53 at the phenotypic level and 0.86 at the genetic level. In other words, most of the genetic influences on the two traits overlap. After the Big Five personality traits explained 5.6% of the variance in exam grades, adding grit increased the explained variance by only 0.5%. Credé et al. (2017) integrated 88 independent samples (66,807 individuals) and concluded that the higher-order structure of grit was not confirmed, that grit was only moderately correlated with performance and retention, and that grit was very strongly correlated with conscientiousness. The perseverance facet, however, still explained variance in academic performance after conscientiousness was controlled.

Therefore, the “ability to make an effort” that has been measured under the name of grit was, also from a genetic perspective, nearly the same as conscientiousness, a long-established personality trait.

Is the amount of practice itself heritable?

The traits discussed so far were measured with questionnaires. A further question is whether the amount of effort that people actually spend is also heritable. Research on expertise has long explained the difference between experts and novices by the amount of practice.

Mosing et al. (2014) examined the relationship between the amount of music practice and the ability to discriminate pitch, melody, and rhythm in 10,500 Swedish twins. The correlations between practice and ability ranged from r = .18 to .36. The amount of practice itself was substantially heritable, at 40-70%. The associations between practice and ability were predominantly genetic, and there was no difference in ability within monozygotic twin pairs who differed in their amount of practice. That is, when genetic background was held constant, the twin who practiced more did not show higher ability. The authors interpreted this result as suggesting that music practice may not causally influence this ability and that the same genetic differences affect both ability and the inclination to practice. The ability measured here was auditory discrimination, not skill in playing an instrument.

The size of the effect of practice also differs by domain. In the meta-analysis by Macnamara et al. (2014), deliberate practice explained 26% of the variance in performance for games, 21% for music, 18% for sports, 4% for education, and less than 1% for professions. Ullén et al. (2016) argued that theories explaining expertise by the amount of practice alone cannot account for such findings, and they proposed a multifactorial gene-environment interaction model of expertise.

Is effort a cause of achievement, or a route through which genes appear in achievement?

If the amount of practice is heritable, it is unclear how much of the association between effort and achievement reflects the effect of effort itself. In the domain of school performance, this question has been examined directly.

Kevenaar et al. (2023a) analyzed teacher ratings of school performance, self-control, and grit perseverance for 4,891 Dutch twin pairs aged 12. Genetic influences explained 74% of the variance in school performance, 69% in self-control, and 58% in grit. In standard regression, self-control and grit explained 28.4% of the variance in school performance (Kevenaar et al., 2023b). However, when genetic influences shared by the three traits (confounding) were allowed for, the direct effect of self-control and grit on school performance accounted for only 4.4%. The authors stated that self-control and grit predict school performance primarily because of shared genetic influences, and that interventions targeting self-control and grit alone may yield limited effects.

Other measures close to personality show the same pattern. Tucker-Drob et al. (2016) measured seven character measures (grit, intellectual curiosity, academic self-concept, mastery orientation, educational value, intelligence mindset, and test motivation) in 811 twins and triplets in the United States. These seven measures formed a highly heritable common dimension that combined openness and conscientiousness. The genetically influenced variance in these measures predicted academic achievement even after fluid intelligence was controlled, whereas the environmentally influenced variance was largely unrelated to achievement. Krapohl et al. (2014) also showed, in 13,306 twins aged 16 in the United Kingdom, that domains such as self-efficacy, personality, and well-being, together with intelligence, accounted for 75% of the heritability (62%) of exam grades.

This relationship strengthens over development. Malanchini et al. (2024) followed more than 10,000 children in the United Kingdom from age 7 to 16 and showed that the association between non-cognitive skills (such as motivation and self-regulation) and academic achievement increased across the school years, as did the genetic influences supporting this association. Within-family analyses indicated that these genetic effects could not be explained only by environmental differences between families. The authors raised the possibility of a process in which children evoke and select experiences that fit their genetic tendencies (evocative and active gene-environment correlation). Zhou et al. (2026) reported, in 5,016 children from the same British cohort, that non-cognitive skills mediated between less than 5% and up to 64% of the genetic prediction of academic achievement, and that mediation was larger for motivation and attitudes (β ≈ 0.13) than for emotional and behavioral functioning (β ≈ 0.01-0.03).

This series of results does not fit the picture that “effort can make up for a lack of talent.” The tendency to make an effort acts as one of the routes through which genetic differences appear in achievement.

What heritability figures do not say

Reading the figures above as “60% of the ability to make an effort is innate and cannot be changed” would be a mistake. Heritability is a figure about individual differences within a population; it does not mean that 60% of one person’s effort is determined by genes.

Heritability also changes with the environment. Although the result concerns intelligence and academic achievement rather than effort-related traits, Tucker-Drob and Bates (2016) used an international meta-analysis to examine whether heritability changes with family socioeconomic status (SES). In U.S. studies, they found clear support for a moderately sized interaction in which genetic influences appear more strongly in more advantaged families. In studies from Western Europe and Australia, where social policies ensure more uniform access to high-quality education and health care, the interaction was zero or reversed. When environmental opportunities are unevenly distributed, the degree to which genetic differences become visible is also uneven.

Harden and Koellinger (2020) reviewed misunderstandings that arise when genetic research is brought into the social sciences and stated that the observation that human behavior is influenced by genetic differences should not be misinterpreted as biological determinism. DNA sequences do not change after conception, but their influence on social and behavioral outcomes can vary across environments. The same paper quotes a passage from Rawls: the natural distribution is neither just nor unjust, and what is just and unjust is the way that institutions deal with these facts.

Turkheimer’s (2000) third law points in the same direction. A substantial portion of the variation in complex human behavior is not accounted for by the effects of genes or families.

How far has molecular genetics captured the genetics of “non-cognitive” skills?

Twin studies estimate the total amount of genetic influence, but they do not show which genes act and how. In recent years, polygenic scores (PGS), which are built from many variants across the genome, have been used to measure genetic influences on traits close to effort more directly.

Demange et al. (2021) combined genome-wide association studies of educational attainment (1,131,881 individuals) and cognitive test performance (257,841 individuals) to isolate the part of the genetics of educational attainment that is not explained by cognitive ability (NonCog). NonCog accounted for 57% of the genetic variance in educational attainment, and 157 genome-wide significant loci were identified. NonCog genetics were associated with personality traits, less risky behavior, and increased risk for certain psychiatric disorders. However, NonCog was defined as the residual of educational attainment after cognition was subtracted, and it does not measure effort itself. Its genetic correlation with openness (0.30) was also larger than that with conscientiousness (0.13). Therefore, “non-cognitive genetics” is better understood as a mixture of various non-cognitive tendencies related to educational attainment than as a set of genes for effort.

In addition, not all of the effect of a PGS comes directly from a person’s own genes. Kong et al. (2018) showed that a PGS for educational attainment computed from the parental alleles not transmitted to the child also predicted the child’s educational attainment, with an effect equal to 29.9% of that of the transmitted alleles, and they called this phenomenon genetic nurture. That is, parental genotypes affect children through the home environment that parents create. In a meta-analysis by Wang et al. (2021) covering 38,654 families in eight cohorts, genetic nurture effects (β = 0.08) were smaller than direct genetic effects (β = 0.17) but were consistently found. Using sibling, adoption, and parent-offspring designs, Demange et al. (2022) estimated that 36% of the association between the NonCog PGS and offspring educational outcomes runs through indirect effects of the environment shaped by parental genotypes. The authors noted, however, that the sibling-based and trio-based estimates may also include prenatal effects, population stratification, and assortative mating. When comparisons are made within sibships, estimates of genetic effects on traits such as educational attainment are smaller than population estimates (Howe et al., 2022). In an analysis of about three million individuals, direct effects accounted for roughly half of the association of the polygenic index with educational attainment (Okbay et al., 2022).

These results mainly concern educational attainment and do not directly measure self-control or grit. Even so, they show that the part that appears as “genetic differences” includes the environment created by parents and the structure of society. Consequently, the heritability of the tendency to make an effort cannot be read directly as a biological property of the individual.

Is willpower a fuel that is used up?

Apart from genetics, thinking about effort contains one more assumption. This is the idea of ego depletion: willpower is a resource that is used up, so the more it is used, the harder the next act of self-control becomes. If this idea were correct, the amount of effort a person can make would have an upper limit set by the amount of fuel each individual has.

Large-scale replications largely failed to reproduce this effect. In the preregistered replication by Hagger et al. (2016), 23 laboratories (2,141 participants) followed the same protocol, and the effect size was d = 0.04 (95% CI [-0.07, 0.15]), with a confidence interval that included zero. In the preregistered multisite test by Vohs et al. (2021), with 36 laboratories (3,531 participants), the confirmatory test yielded a nonsignificant effect of d = 0.06, and the Bayesian analysis found that the data were four times more likely under the null hypothesis than under the alternative. In exploratory analyses, the effect was larger for participants who reported more fatigue, but it was not moderated by trait self-control or willpower beliefs. The abstract of Carter et al. (2015) states that a series of focused meta-analytic tests found very little evidence for the depletion effect when it is assessed with the methods most frequently used in the laboratory.

However, the debate has not ended. The abstract of Friese et al. (2019) concludes that, despite several hundred published studies, the available evidence is inconclusive. The abstract of Dang et al. (2025) reports that a new procedure using a demanding task lasting 30-40 minutes was tested across 14 samples (2,078 participants) and consistently produced effects of d = 0.31-0.35 (the full text could not be obtained, and this study is treated within the scope of its abstract). The authors argue that the intensity of the manipulation determines whether the effect replicates.

Research on willpower beliefs followed a similar course. The abstract of Job et al. (2010) reports that people who believed that willpower is not limited did not show reduced self-control after a depleting task. Miyake and Carruth (2023) reviewed later studies that tested this moderating effect and concluded that the evidence was ambiguous in four of the five studies reporting the effect and that no large-sample preregistered study had yielded robust evidence for it.

After the view of effort as remaining fuel was shaken, a view that treats effort as a judgment of costs and value emerged. Inzlicht et al. (2018) reviewed evidence that effort is usually avoided as a cost but can also add value, and that people sometimes choose options precisely because they require effort. The same paper raises, as an open question, how willingness to exert effort changes over development among groups that are more likely to experience unrewarded effort, such as people with low SES. How much of the individual differences in the tendency to make an effort reflects differences in the experience of being rewarded has not yet been examined.

Can the tendency to make an effort be changed by intervention?

If heritability does not mean unchangeability, the next question is whether the tendency can actually be changed. Among the interventions tested on a large scale are growth mindset interventions, which teach that abilities can be developed.

The average effects are small. In the meta-analyses by Sisk et al. (2018), the correlation between mindset and academic achievement was r = .10, and the effect of interventions was d = 0.08. Macnamara and Burgoyne (2023) examined 63 studies (97,672 students) and found an overall effect of d = 0.05, which became nonsignificant after correction for publication bias; among the six highest-quality studies (13,571 students), the effect was d = 0.02. They also reported that studies by authors with a financial interest in the interventions showed larger effects.

In contrast, other studies narrowed the conditions under which effects appear. Yeager et al. (2019) conducted a preregistered experiment with an online intervention lasting less than one hour in a nationally representative sample of U.S. high schools. Among lower-achieving students, grades in core courses at the end of ninth grade rose by 0.10 grade points (standardized effect size 0.11), and the effect was sustained in schools where peer norms were aligned with the message of the intervention. The abstract of Burnette et al. (2023) reports that, when interventions were delivered with high fidelity to the subgroups expected to benefit, the effect was d = 0.14 for academic achievement and d = 0.32 for mental health, and that the 95% prediction interval for academic achievement ranged from -0.08 to 0.35. Tipton et al. (2023) explained the different conclusions of the two meta-analyses as a difference in method, namely whether effects are aggregated into a single average or whether variation across groups and contexts is modeled. Yeager and Dweck (2020) also stated that mindset effects vary meaningfully across individuals and contexts. Yeager and Dweck are researchers who have developed these interventions, and Yeager is also an author of the commentary by Tipton et al.

The current state of the evidence, therefore, is that the effects are small on average and appear only in part when conditions are selected. For grit, Credé et al. (2017) also stated that interventions designed to enhance grit may have only weak effects on performance and success.

Even so, differences in self-control leave a large mark on life outcomes. Moffitt et al. (2011) followed 1,000 children born in Dunedin, New Zealand, from birth to age 32 and showed that childhood self-control predicted adult physical health, substance dependence, personal finances, and criminal offending along a gradient, even after intelligence and social class were controlled. In another cohort of 500 sibling pairs, the sibling with lower self-control had poorer outcomes despite growing up in the same family. Traits related to effort are influenced by genes and also affect life outcomes. The average effects of the interventions tested on a large scale around these traits have, as shown above, been small.

An answer to “Is the ability to make an effort also a talent?”

Hypothesis 1: The tendency to make an effort is one of the routes through which genetic differences appear in achievement. Self-control, grit, motivation to learn, and the amount of practice are as heritable as other traits (Willems et al., 2019; Rimfeld et al., 2016; Kovas et al., 2015; Mosing et al., 2014). Much of the association between effort and achievement is explained by shared genetic influences (Mosing et al., 2014; Kevenaar et al., 2023b; Tucker-Drob et al., 2016), and this association becomes stronger over development (Malanchini et al., 2024; Zhou et al., 2026). In the terms of the question, “being able to make an effort” is part of talent in the sense that it includes the luck of birth. The part of this hypothesis stating that “much of the association between effort and achievement is due to shared genetic influences” would be weakened if evidence accumulated, for practice or learning behavior, that the member of an identical twin pair who makes more effort consistently achieves more.

Hypothesis 2: What heritability shows is where differences between people come from in the current environment; it does not answer whether effort may be treated as a personal merit or responsibility. Heritability changes with the environment (Tucker-Drob & Bates, 2016), and the part that appears as “genetic” in molecular genetics includes the environment created by parents (Kong et al., 2018; Demange et al., 2022). The fact that the tendency to make an effort is heritable does not, by itself, justify either praising or blaming effort. Following the passage from Rawls quoted by Harden and Koellinger (2020), the question to be asked is how institutions deal with the difference between people who can make an effort and people who cannot.

Taken together, the two hypotheses show that the question “Is the ability to make an effort also a talent?” combines a factual question and an evaluative question. Within the scope of the literature, the answer to the factual question is “to a considerable degree, yes.” The answer to the evaluative question, namely how to treat people who did not make an effort, cannot be derived from heritability figures.

Gaps (unresolved issues)

• Measured effort and actual effort: Most heritability estimates rely on questionnaires completed by the person, parents, or teachers. Twin studies that measured effort through actual time spent or behavior are limited to a few cases, such as the amount of music practice (Mosing et al., 2014). The finding that heritability differs by informant (Willems et al., 2019) also indicates the influence of the measurement method.
• Sample bias: The twin studies in this note mainly use samples from the United Kingdom, the Netherlands, Sweden, and the United States, and the molecular genetic studies are limited to individuals of European ancestry (Demange et al., 2021). The corpus does not include studies that examined the heritability of effort-related traits and their interaction with the environment in East Asian samples, including Japan.
• Interaction between effort-related traits and the environment: The international meta-analysis of differences in heritability by SES (Tucker-Drob & Bates, 2016) concerns intelligence and academic achievement, and no comparison of the same scale was found for self-control or grit.
• Whether the value of effort is learned: The question of whether rewarded experience creates willingness to exert effort (Inzlicht et al., 2018) bears directly on the interpretation of heritability, but longitudinal tests remain scarce.
• Conditions for ego depletion: The relationship between the negative results of multisite replications (Hagger et al., 2016; Vohs et al., 2021) and the report of effects under an intense manipulation (Dang et al., 2025) has not been resolved.

Unverified items

• The following six sources were used only within the scope of their abstracts because the full text could not be obtained through three or more routes. In the text, the relevant statements are attributed to the abstracts: Vukasović and Bratko (2015; figures for personality heritability), Carter et al. (2015; conclusion of the ego depletion meta-analysis), Job et al. (2010; conclusion of the willpower belief studies), Friese et al. (2019; conclusion of the analysis of arguments on ego depletion), Dang et al. (2025; effect sizes under an intense manipulation), and Burnette et al. (2023; effect sizes and prediction intervals for mindset interventions).
• Willems et al. (2019) was checked against the authors’ preprint (PsyArXiv). The number of studies, the twin correlations, and the heritability matched the abstract of the published version, but the sample size is described as “more than 100,000 individuals” in the preprint and as “more than 30,000 twins” in the abstract of the published version; this note uses the value from the published version.
• Kong et al. (2018) was checked against the bioRxiv preprint, and the figure (29.9%) was confirmed to match the abstract of the published version in Europe PMC.

References

All sources were accessed on 2026-10-07.

Reference points for heritability and its interpretation

• Polderman, T. J. C., Benyamin, B., de Leeuw, C. A., Sullivan, P. F., van Bochoven, A., Visscher, P. M., & Posthuma, D. (2015). Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nature Genetics, 47(7), 702–709. https://doi.org/10.1038/ng.3285
• Turkheimer, E. (2000). Three laws of behavior genetics and what they mean. Current Directions in Psychological Science, 9(5), 160–164. https://doi.org/10.1111/1467-8721.00084
• Tucker-Drob, E. M., & Bates, T. C. (2016). Large cross-national differences in gene × socioeconomic status interaction on intelligence. Psychological Science, 27(2), 138–149. https://doi.org/10.1177/0956797615612727
• Harden, K. P., & Koellinger, P. D. (2020). Using genetics for social science. Nature Human Behaviour, 4(6), 567–576. https://doi.org/10.1038/s41562-020-0862-5

Heritability of traits related to effort

• Vukasović, T., & Bratko, D. (2015). Heritability of personality: A meta-analysis of behavior genetic studies. Psychological Bulletin, 141(4), 769–785. https://doi.org/10.1037/bul0000017
• Willems, Y. E., Boesen, N., Li, J., Finkenauer, C., & Bartels, M. (2019). The heritability of self-control: A meta-analysis. Neuroscience & Biobehavioral Reviews, 100, 324–334. https://doi.org/10.1016/j.neubiorev.2019.02.012
• Rimfeld, K., Kovas, Y., Dale, P. S., & Plomin, R. (2016). True grit and genetics: Predicting academic achievement from personality. Journal of Personality and Social Psychology, 111(5), 780–789. https://doi.org/10.1037/pspp0000089
• Kovas, Y., Garon-Carrier, G., Boivin, M., Petrill, S. A., Plomin, R., Malykh, S. B., Spinath, F., Murayama, K., Ando, J., Bogdanova, O. Y., Brendgen, M., Dionne, G., Forget-Dubois, N., Galajinsky, E. V., Gottschling, J., Guay, F., Lemelin, J.-P., Logan, J. A. R., Yamagata, S., Shikishima, C., Spinath, B., Thompson, L. A., Tikhomirova, T. N., Tosto, M. G., Tremblay, R., & Vitaro, F. (2015). Why children differ in motivation to learn: Insights from over 13,000 twins from 6 countries. Personality and Individual Differences, 80, 51–63. https://doi.org/10.1016/j.paid.2015.02.006
• Friedman, N. P., Miyake, A., Young, S. E., DeFries, J. C., Corley, R. P., & Hewitt, J. K. (2008). Individual differences in executive functions are almost entirely genetic in origin. Journal of Experimental Psychology: General, 137(2), 201–225. https://doi.org/10.1037/0096-3445.137.2.201

Grit and conscientiousness

• Duckworth, A. L., Peterson, C., Matthews, M. D., & Kelly, D. R. (2007). Grit: Perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 92(6), 1087–1101. https://doi.org/10.1037/0022-3514.92.6.1087
• Credé, M., Tynan, M. C., & Harms, P. D. (2017). Much ado about grit: A meta-analytic synthesis of the grit literature. Journal of Personality and Social Psychology, 113(3), 492–511. https://doi.org/10.1037/pspp0000102

Amount of practice and expertise

• Mosing, M. A., Madison, G., Pedersen, N. L., Kuja-Halkola, R., & Ullén, F. (2014). Practice does not make perfect: No causal effect of music practice on music ability. Psychological Science, 25(9), 1795–1803. https://doi.org/10.1177/0956797614541990
• Macnamara, B. N., Hambrick, D. Z., & Oswald, F. L. (2014). Deliberate practice and performance in music, games, sports, education, and professions: A meta-analysis. Psychological Science, 25(8), 1608–1618. https://doi.org/10.1177/0956797614535810
• Ullén, F., Hambrick, D. Z., & Mosing, M. A. (2016). Rethinking expertise: A multifactorial gene–environment interaction model of expert performance. Psychological Bulletin, 142(4), 427–446. https://doi.org/10.1037/bul0000033

Genetic structure of the association between effort and achievement

• Kevenaar, S. T., Dolan, C. V., Boomsma, D. I., & van Bergen, E. (2023a). Self-control and grit are associated with school performance mainly because of shared genetic effects. JCPP Advances, 3(2), e12159. https://doi.org/10.1002/jcv2.12159
• Kevenaar, S. T., van Bergen, E., Oldehinkel, A. J., Boomsma, D. I., & Dolan, C. V. (2023b). The relationship of school performance with self-control and grit is strongly genetic and weakly causal. npj Science of Learning, 8, 53. https://doi.org/10.1038/s41539-023-00198-3
• Tucker-Drob, E. M., Briley, D. A., Engelhardt, L. E., Mann, F. D., & Harden, K. P. (2016). Genetically-mediated associations between measures of childhood character and academic achievement. Journal of Personality and Social Psychology, 111(5), 790–815. https://doi.org/10.1037/pspp0000098
• Krapohl, E., Rimfeld, K., Shakeshaft, N. G., Trzaskowski, M., McMillan, A., Pingault, J.-B., Asbury, K., Harlaar, N., Kovas, Y., Dale, P. S., & Plomin, R. (2014). The high heritability of educational achievement reflects many genetically influenced traits, not just intelligence. Proceedings of the National Academy of Sciences, 111(42), 15273–15278. https://doi.org/10.1073/pnas.1408777111
• Malanchini, M., Allegrini, A. G., Nivard, M. G., Biroli, P., Rimfeld, K., Cheesman, R., von Stumm, S., Demange, P. A., van Bergen, E., Grotzinger, A. D., Raffington, L., De la Fuente, J., Pingault, J.-B., Tucker-Drob, E. M., Harden, K. P., & Plomin, R. (2024). Genetic associations between non-cognitive skills and academic achievement over development. Nature Human Behaviour, 8(10), 2034–2046. https://doi.org/10.1038/s41562-024-01967-9
• Zhou, Q., Liao, W., Allegrini, A. G., Rimfeld, K., Wertz, J., et al. (2026). Non-cognitive skills mediate education-related polygenic score associations with academic achievement across development. Nature Communications, 17, 5133. https://doi.org/10.1038/s41467-026-72838-2

Molecular genetics and genetic nurture

• Demange, P. A., Malanchini, M., Mallard, T. T., Biroli, P., Cox, S. R., Grotzinger, A. D., Tucker-Drob, E. M., Abdellaoui, A., Arseneault, L., van Bergen, E., Boomsma, D. I., Caspi, A., Corcoran, D. L., Domingue, B. W., Harris, K. M., Ip, H. F., Mitchell, C., Moffitt, T. E., Poulton, R., Prinz, J. A., Sugden, K., Wertz, J., Williams, B. S., de Zeeuw, E. L., Belsky, D. W., Harden, K. P., & Nivard, M. G. (2021). Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction. Nature Genetics, 53(1), 35–44. https://doi.org/10.1038/s41588-020-00754-2
• Kong, A., Thorleifsson, G., Frigge, M. L., Vilhjalmsson, B. J., Young, A. I., Thorgeirsson, T. E., Benonisdottir, S., Oddsson, A., Halldorsson, B. V., Masson, G., Gudbjartsson, D. F., Helgason, A., Bjornsdottir, G., Thorsteinsdottir, U., & Stefansson, K. (2018). The nature of nurture: Effects of parental genotypes. Science, 359(6374), 424–428. https://doi.org/10.1126/science.aan6877
• Wang, B., Baldwin, J. R., Schoeler, T., Cheesman, R., Barkhuizen, W., Dudbridge, F., Bann, D., Morris, T. T., & Pingault, J.-B. (2021). Robust genetic nurture effects on education: A systematic review and meta-analysis based on 38,654 families across 8 cohorts. American Journal of Human Genetics, 108(9), 1780–1791. https://doi.org/10.1016/j.ajhg.2021.07.010
• Demange, P. A., Hottenga, J. J., Abdellaoui, A., Eilertsen, E. M., Malanchini, M., Domingue, B. W., Armstrong-Carter, E., de Zeeuw, E. L., Rimfeld, K., Boomsma, D. I., van Bergen, E., Breen, G., Nivard, M. G., & Cheesman, R. (2022). Estimating effects of parents’ cognitive and non-cognitive skills on offspring education using polygenic scores. Nature Communications, 13, 4801. https://doi.org/10.1038/s41467-022-32003-x
• Howe, L. J., Nivard, M. G., Morris, T. T., et al. (2022). Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects. Nature Genetics, 54(5), 581–592. https://doi.org/10.1038/s41588-022-01062-7
• Okbay, A., Wu, Y., Wang, N., Jayashankar, H., Bennett, M., et al. (2022). Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals. Nature Genetics, 54(4), 437–449. https://doi.org/10.1038/s41588-022-01016-z

Willpower and the value of effort

• Hagger, M. S., Chatzisarantis, N. L. D., Alberts, H., Anggono, C. O., Batailler, C., Birt, A. R., et al. (2016). A multilab preregistered replication of the ego-depletion effect. Perspectives on Psychological Science, 11(4), 546–573. https://doi.org/10.1177/1745691616652873
• Vohs, K. D., Schmeichel, B. J., Lohmann, S., Gronau, Q. F., Finley, A. J., Ainsworth, S. E., et al. (2021). A multisite preregistered paradigmatic test of the ego-depletion effect. Psychological Science, 32(10), 1566–1581. https://doi.org/10.1177/0956797621989733
• Carter, E. C., Kofler, L. M., Forster, D. E., & McCullough, M. E. (2015). A series of meta-analytic tests of the depletion effect: Self-control does not seem to rely on a limited resource. Journal of Experimental Psychology: General, 144(4), 796–815. https://doi.org/10.1037/xge0000083
• Friese, M., Loschelder, D. D., Gieseler, K., Frankenbach, J., & Inzlicht, M. (2019). Is ego depletion real? An analysis of arguments. Personality and Social Psychology Review, 23(2), 107–131. https://doi.org/10.1177/1088868318762183
• Dang, J., Xiao, S., Mao, L., Liu, X., Baumert, A., et al. (2025). Revisiting ego depletion: Evidence from multi-lab collaborations. Journal of Pacific Rim Psychology, 19. https://doi.org/10.1177/18344909251386084
• Job, V., Dweck, C. S., & Walton, G. M. (2010). Ego depletion—Is it all in your head? Implicit theories about willpower affect self-regulation. Psychological Science, 21(11), 1686–1693. https://doi.org/10.1177/0956797610384745
• Miyake, A., & Carruth, N. P. (2023). On the robustness and replicability of the moderating influence of willpower mindset on the ego-depletion effect: Existing evidence is weak at best. Frontiers in Psychology, 14, 1208299. https://doi.org/10.3389/fpsyg.2023.1208299
• Inzlicht, M., Shenhav, A., & Olivola, C. Y. (2018). The effort paradox: Effort is both costly and valued. Trends in Cognitive Sciences, 22(4), 337–349. https://doi.org/10.1016/j.tics.2018.01.007
• Moffitt, T. E., Arseneault, L., Belsky, D., Dickson, N., Hancox, R. J., Harrington, H., Houts, R., Poulton, R., Roberts, B. W., Ross, S., Sears, M. R., Thomson, W. M., & Caspi, A. (2011). A gradient of childhood self-control predicts health, wealth, and public safety. Proceedings of the National Academy of Sciences, 108(7), 2693–2698. https://doi.org/10.1073/pnas.1010076108

Growth mindset interventions

• Sisk, V. F., Burgoyne, A. P., Sun, J., Butler, J. L., & Macnamara, B. N. (2018). To what extent and under which circumstances are growth mind-sets important to academic achievement? Two meta-analyses. Psychological Science, 29(4), 549–571. https://doi.org/10.1177/0956797617739704
• Yeager, D. S., Hanselman, P., Walton, G. M., Murray, J. S., Crosnoe, R., Muller, C., et al. (2019). A national experiment reveals where a growth mindset improves achievement. Nature, 573(7774), 364–369. https://doi.org/10.1038/s41586-019-1466-y
• Macnamara, B. N., & Burgoyne, A. P. (2023). Do growth mindset interventions impact students’ academic achievement? A systematic review and meta-analysis with recommendations for best practices. Psychological Bulletin, 149(3–4), 133–173. https://doi.org/10.1037/bul0000352
• Burnette, J. L., Billingsley, J., Banks, G. C., Knouse, L. E., Hoyt, C. L., Pollack, J. M., & Simon, S. (2023). A systematic review and meta-analysis of growth mindset interventions: For whom, how, and why might such interventions work? Psychological Bulletin, 149(3–4), 174–205. https://doi.org/10.1037/bul0000368
• Tipton, E., Bryan, C., Murray, J., McDaniel, M. A., Schneider, B., & Yeager, D. S. (2023). Why meta-analyses of growth mindset and other interventions should follow best practices for examining heterogeneity: Commentary on Macnamara and Burgoyne (2023) and Burnette et al. (2023). Psychological Bulletin, 149(3–4), 229–241. https://doi.org/10.1037/bul0000384
• Yeager, D. S., & Dweck, C. S. (2020). What can be learned from growth mindset controversies? American Psychologist, 75(9), 1269–1284. https://doi.org/10.1037/amp0000794