Editorial: For better or for worse? Intended and unintended consequences of science communication.

Recently, more effort has been devoted to ensuring that scientific knowledge can be mobilised to make a positive impact on individuals and society. Scientists are encouraged, and even required, to communicate their findings beyond academic circles - to inform interested groups. However, there can be challenges with language use and communicating concepts; interpreting results; and from time pressure to communicate results rapidly. Here, we discuss intended and unintended consequences of science communication. We emphasise the importance of training to achieve these communication skills and working with non-academic partners - to mitigate potential harm from misinterpreted results and to ensure that science communication is maximally beneficial.

What Do People Know About the Heritability of Sleep?

STUDY OBJECTIVES: Twin studies have provided data about the relative weight of genetic and environmental factors on sleep variables over the last few decades. However, heritability is a non-intuitive concept and it is often misunderstood even amongst the scientific community. This study aimed to analyze: (1) understanding of the meaning of heritability of insomnia; (2) the accuracy of estimations of heritability in the general population regarding three sleep traits (sleep duration, sleep quality and insomnia); (3) perceptions of the effectiveness of different treatments for insomnia depending on how the disorder is presented (i.e. having an environmental or genetic etiology) and whether the subject's estimate of genetic influence on sleep traits impacted beliefs about the effectiveness of different treatments. METHODS: Participants (N = 3658) completed a survey which included: questions about general genetic knowledge; a specific question about the meaning of heritability; estimates of heritability of three different sleep traits; and the effectiveness of different treatments for insomnia depending on how the etiology of this condition was presented. RESULTS: Fewer than 25% of the participants selected the correct description of the heritability of insomnia. Almost half of the sample incorrectly believed that heritability refers to the chance of passing a disorder onto their children. We also found that participants provided different estimates for the effectiveness of different treatments depending on the presumed etiology of the disorder. CONCLUSION: Most people do not have accurate knowledge about the concept of heritability. People's assumptions about the etiology of a disorder may influence which treatments they consider most effective.

School quality ratings are weak predictors of students' achievement and well-being.

BACKGROUND: In England, all state-funded schools are inspected by an independent government agency, the Office for Standards in Education, Children's Services and Skills (Ofsted). Inspections aim to hold schools accountable and to promote the improvement of education, with the results made available to the public. Ofsted reports intend to index school quality, but their influence on students' individual outcomes has not been previously studied. The aim of the current study was to explore the extent to which school quality, as indexed by Ofsted ratings, is associated with students' educational achievement, well-being and school engagement. METHODS: We use an England population-based sample of 4,391 individuals, for whom school performance at age 11 and GCSE grades at age 16 were accessed from the National Pupil Database, and who completed measures of well-being and school engagement at age 16. RESULTS: We found that Ofsted ratings of secondary school quality accounted for 4% of the variance in students' educational achievement at age 16, which was further reduced to 1% of the variance after we accounted for prior school performance at age 11 and family socioeconomic status. Furthermore, Ofsted ratings were weak predictors of school engagement and student well-being, with an average correlation of .03. CONCLUSION: Our findings suggest that differences in school quality, as indexed by Ofsted ratings, have little relation to students' individual outcomes. Accordingly, our results challenge the usefulness of Ofsted ratings as guides for parents and students when choosing secondary schools.

Phenotypic and genetic evidence for a unifactorial structure of spatial abilities.

Spatial abilities encompass several skills differentiable from general cognitive ability (g). Importantly, spatial abilities have been shown to be significant predictors of many life outcomes, even after controlling for g. To date, no studies have analyzed the genetic architecture of diverse spatial abilities using a multivariate approach. We developed "gamified" measures of diverse putative spatial abilities. The battery of 10 tests was administered online to 1,367 twin pairs (age 19-21) from the UK-representative Twins Early Development Study (TEDS). We show that spatial abilities constitute a single factor, both phenotypically and genetically, even after controlling for g This spatial ability factor is highly heritable (69%). We draw three conclusions: (i) The high heritability of spatial ability makes it a good target for gene-hunting research; (ii) some genes will be specific to spatial ability, independent of g; and (iii) these genes will be associated with all components of spatial ability.

Dysfunctional beliefs about sleep and insomnia symptoms in early adulthood: A twin and sibling study.

This study examines the associations between dysfunctional belief about sleep (DBAS), its subtypes and insomnia symptoms and estimates the relative contribution of genetic and environmental influences to these variables and the associations between them. The data came from G1219, a twin/sibling study that comprises 862 individuals (aged 22-32 years, 34% male). The Insomnia Symptoms Questionnaire was used to measure insomnia symptoms and a 10-item version of the Dysfunctional Beliefs and Attitudes about Sleep Scale was used to assess DBAS. A higher DBAS score was associated with more insomnia symptoms. Overall DBAS showed a mainly non-shared environmental influence (86%). The genetic correlation between overall DBAS and insomnia symptoms was large but not significant, the shared environmental correlation was very small, negative and not significant, whereas a moderate, significant overlap in the non-shared environmental influences was evident (non-shared environmental correlation = 0.32). For the association between the subscales of DBAS and insomnia symptoms no significant overlap for genetic (weak to strong associations) or shared environmental factors (very weak negative to strong associations) was indicated. Most of the non-shared environmental influences on the four variables were significantly moderately correlated (non-shared environmental correlation = 0.24-0.46). These findings help to deepen our understanding of cognitive theories of insomnia by dissecting one of its crucial elements and illuminating the factors involved in its association with insomnia symptoms.

GENES AND GINI: WHAT INEQUALITY MEANS FOR HERITABILITY.

Research has established that genetic differences among people explain a greater or smaller proportion of the variation in life outcomes in different environmental conditions. This review evaluates the results of recent educationally relevant behavioural genetic studies and meta-analyses in the context of recent trends in income and wealth distribution. The pattern of results suggests that inequality and social policies can have profound effects on the heritability of educational attainment and achievement in a population (Gene-Gini interplay). For example, heritability is generally higher at greater equality levels, suggesting that inequality stifles the expression of educationally relevant genetic propensities. The review concludes with a discussion of the mechanisms of Gene-Gini interplay and what the findings mean for efforts to optimize education for all people.

Persistent Genetic and Family-Wide Environmental Contributions to Early Number Knowledge and Later Achievement in Mathematics.

This study investigated the stable and transient genetic and environmental contributions to individual differences in number knowledge in the transition from preschool (age 5) to Grade 1 (age 7) and to the predictive association between early number knowledge and later math achievement (age 10-12). We conducted genetic simplex modeling across these three time points. Genetic variance was transmitted from preschool number knowledge to late-elementary math achievement; in addition, significant genetic innovation (i.e., new influence) occurred at ages 10 through 12 years. The shared and nonshared environmental contributions decreased during the transition from preschool to school entry, but shared and nonshared environment contributed to the continuity across time from preschool number knowledge to subsequent number knowledge and math achievement. There was no new environmental contribution at time points subsequent to preschool. Results are discussed in light of their practical implications for children who have difficulties with mathematics, as well as for preventive intervention.

The high heritability of educational achievement reflects many genetically influenced traits, not just intelligence.

Because educational achievement at the end of compulsory schooling represents a major tipping point in life, understanding its causes and correlates is important for individual children, their families, and society. Here we identify the general ingredients of educational achievement using a multivariate design that goes beyond intelligence to consider a wide range of predictors, such as self-efficacy, personality, and behavior problems, to assess their independent and joint contributions to educational achievement. We use a genetically sensitive design to address the question of why educational achievement is so highly heritable. We focus on the results of a United Kingdom-wide examination, the General Certificate of Secondary Education (GCSE), which is administered at the end of compulsory education at age 16. GCSE scores were obtained for 13,306 twins at age 16, whom we also assessed contemporaneously on 83 scales that were condensed to nine broad psychological domains, including intelligence, self-efficacy, personality, well-being, and behavior problems. The mean of GCSE core subjects (English, mathematics, science) is more heritable (62%) than the nine predictor domains (35-58%). Each of the domains correlates significantly with GCSE results, and these correlations are largely mediated genetically. The main finding is that, although intelligence accounts for more of the heritability of GCSE than any other single domain, the other domains collectively account for about as much GCSE heritability as intelligence. Together with intelligence, these domains account for 75% of the heritability of GCSE. We conclude that the high heritability of educational achievement reflects many genetically influenced traits, not just intelligence.

Preschool Drawing and School Mathematics: The Nature of the Association.

The study examined the etiology of individual differences in early drawing and of its longitudinal association with school mathematics. Participants (N = 14,760), members of the Twins Early Development Study, were assessed on their ability to draw a human figure, including number of features, symmetry, and proportionality. Human figure drawing was moderately stable across 6 months (average r = .40). Individual differences in drawing at age 4½ were influenced by genetic (.21), shared environmental (.30), and nonshared environmental (.49) factors. Drawing was related to later (age 12) mathematical ability (average r = .24). This association was explained by genetic and shared environmental factors that also influenced general intelligence. Some genetic factors, unrelated to intelligence, also contributed to individual differences in drawing.

Intrinsic Motivation and Achievement in Mathematics in Elementary School: A Longitudinal Investigation of Their Association.

This study examined the associations between intrinsic motivation and achievement in mathematics in a sample of 1,478 Canadian school-age children followed from Grades 1 to 4 (ages 7-10). Children self-reported their intrinsic motivation toward mathematics, whereas achievement was measured through direct assessment of mathematics abilities. Cross-lagged models showed that achievement predicted intrinsic motivation from Grades 1 to 2, and from Grades 2 to 4. However, intrinsic motivation did not predict achievement at any time. This developmental pattern of association was gender invariant. Contrary to the hypothesis that motivation and achievement are reciprocally associated over time, our results point to a directional association from prior achievement to subsequent intrinsic motivation. Results are discussed in light of their theoretical and practical implications.

A latent profile analysis of math achievement, numerosity, and math anxiety in twins.

Underperformance in math is a problem with increasing prevalence, complex etiology, and severe repercussions. This study examined the etiological heterogeneity of math performance in a sample of 264 pairs of 12-year-old twins assessed on measures of math achievement, numerosity and math anxiety. Latent profile analysis indicated five groupings of individuals representing different patterns of math achievement, numerosity and math anxiety, coupled with differing degrees of familial transmission. These results suggest that there may be distinct profiles of math achievement, numerosity and anxiety; particularly for students who struggle in math.

From classroom environment to mathematics achievement: The mediating role of self-perceived ability and subject interest.

Drawing on Bandura's triadic reciprocal causation model, perceived classroom environment and three intrapersonal factors (mathematics self-efficacy, maths interest and academic self-concept) were considered as predictors of test performance in two correlated mathematics assessments: a public examination (GCSE) and an on-line test, both taken by UK pupils at age 16 (n = 6689). Intrapersonal factors were significantly associated with both test scores, even when the alternative score was taken into account. Classroom environment did not correlate with mathematics achievement once intrapersonal factors and alternative test performance were included in the model, but was associated with subject interest and academic self-concept. Perceptions of classroom environment may exercise an indirect influence on achievement by boosting interest and self-concept. In turn, these intrapersonal factors have direct relationships with achievement and were found to mediate the relationship between perceived classroom environment and maths performance. Findings and their implications for mathematics education are discussed.

Is Math Anxiety Always Bad for Math Learning? The Role of Math Motivation.

The linear relations between math anxiety and math cognition have been frequently studied. However, the relations between anxiety and performance on complex cognitive tasks have been repeatedly demonstrated to follow a curvilinear fashion. In the current studies, we aimed to address the lack of attention given to the possibility of such complex interplay between emotion and cognition in the math-learning literature by exploring the relations among math anxiety, math motivation, and math cognition. In two samples-young adolescent twins and adult college students-results showed inverted-U relations between math anxiety and math performance in participants with high intrinsic math motivation and modest negative associations between math anxiety and math performance in participants with low intrinsic math motivation. However, this pattern was not observed in tasks assessing participants' nonsymbolic and symbolic number-estimation ability. These findings may help advance the understanding of mathematics-learning processes and provide important insights for treatment programs that target improving mathematics-learning experiences and mathematical skills.

Cross-cultural investigation into cognitive underpinnings of individual differences in early arithmetic.

The present study evaluated 626 5-7-year-old children in the UK, China, Russia, and Kyrgyzstan on a cognitive test battery measuring: (1) general skills; (2) non-symbolic number sense; (3) symbolic number understanding; (4) simple arithmetic - operating with numbers; and (5) familiarity with numbers. Although most inter-population differences were small, 13% of the variance in arithmetic skills could be explained by the sample, replicating the pattern, previously found with older children in PISA. Furthermore, the same cognitive skills were related to early arithmetic in these diverse populations. Only understanding of symbolic number explained variation in mathematical performance in all samples. We discuss the results in terms of potential influences of socio-demographic, linguistic and genetic factors on individual differences in mathematics.

Why children differ in motivation to learn: Insights from over 13,000 twins from 6 countries.

Little is known about why people differ in their levels of academic motivation. This study explored the etiology of individual differences in enjoyment and self-perceived ability for several school subjects in nearly 13,000 twins aged 9-16 from 6 countries. The results showed a striking consistency across ages, school subjects, and cultures. Contrary to common belief, enjoyment of learning and children's perceptions of their competence were no less heritable than cognitive ability. Genetic factors explained approximately 40% of the variance and all of the observed twins' similarity in academic motivation. Shared environmental factors, such as home or classroom, did not contribute to the twin's similarity in academic motivation. Environmental influences stemmed entirely from individual specific experiences.

Evidence for shared genetic risk between ADHD symptoms and reduced mathematics ability: a twin study.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) symptoms and mathematics ability are associated, but little is known about the genetic and environmental influences underlying this association. METHODS: Data came from more than 6,000 twelve-year-old twin pairs from the UK population-representative Twins Early Development Study. Parents rated each twin's behaviour using a DSM-IV-based 18-item questionnaire of inattentive and hyperactive-impulsive ADHD symptoms. Mathematics tests based on the UK National Curriculum were completed by each twin. The twins also completed standardised tests of reading and general cognitive ability. Multivariate twin model fitting was applied. RESULTS: Inattentive and hyperactive-impulsive ADHD symptoms were highly heritable (67% and 73% respectively). Mathematics ability was moderately heritable (46%). Mathematics ability and inattentiveness showed a significantly greater phenotypic correlation (r(p) = -.26) and genetic correlation (r(A) = -.41) than mathematics ability and hyperactivity-impulsivity (r(p) = -.18; r(A) = -.22). The genetic correlation between inattentiveness and mathematics ability was largely independent from hyperactivity-impulsivity, and was only partially accounted for by genetic influences related to reading and general cognitive ability. CONCLUSIONS: Results revealed the novel finding that mathematics ability shows significantly stronger phenotypic and genetic associations with inattentiveness than with hyperactivity-impulsivity. Genetic associations between inattentiveness and mathematics ability could only partially be accounted for by hyperactivity-impulsivity, reading and general cognitive ability. Results suggest that mathematics ability is associated with ADHD symptoms largely because it shares genetic risk factors with inattentiveness, and provide further evidence for considering inattentiveness and hyperactivity-impulsivity separately. DNA markers for ADHD symptoms (especially inattentiveness) may also be candidate risk factors for mathematics ability and vice versa.

Who is afraid of math? Two sources of genetic variance for mathematical anxiety.

BACKGROUND: Emerging work suggests that academic achievement may be influenced by the management of affect as well as through efficient information processing of task demands. In particular, mathematical anxiety has attracted recent attention because of its damaging psychological effects and potential associations with mathematical problem solving and achievement. This study investigated the genetic and environmental factors contributing to the observed differences in the anxiety people feel when confronted with mathematical tasks. In addition, the genetic and environmental mechanisms that link mathematical anxiety with math cognition and general anxiety were also explored. METHODS: Univariate and multivariate quantitative genetic models were conducted in a sample of 514 12-year-old twin siblings. RESULTS: Genetic factors accounted for roughly 40% of the variation in mathematical anxiety, with the remaining being accounted for by child-specific environmental factors. Multivariate genetic analyses suggested that mathematical anxiety was influenced by the genetic and nonfamilial environmental risk factors associated with general anxiety and additional independent genetic influences associated with math-based problem solving. CONCLUSIONS: The development of mathematical anxiety may involve not only exposure to negative experiences with mathematics, but also likely involves genetic risks related to both anxiety and math cognition. These results suggest that integrating cognitive and affective domains may be particularly important for mathematics and may extend to other areas of academic achievement.

Why do spatial abilities predict mathematical performance?

Spatial ability predicts performance in mathematics and eventual expertise in science, technology and engineering. Spatial skills have also been shown to rely on neuronal networks partially shared with mathematics. Understanding the nature of this association can inform educational practices and intervention for mathematical underperformance. Using data on two aspects of spatial ability and three domains of mathematical ability from 4174 pairs of 12-year-old twins, we examined the relative genetic and environmental contributions to variation in spatial ability and to its relationship with different aspects of mathematics. Environmental effects explained most of the variation in spatial ability (~70%) and in mathematical ability (~60%) at this age, and the effects were the same for boys and girls. Genetic factors explained about 60% of the observed relationship between spatial ability and mathematics, with a substantial portion of the relationship explained by common environmental influences (26% and 14% by shared and non-shared environments respectively). These findings call for further research aimed at identifying specific environmental mediators of the spatial-mathematics relationship.

Etiological Distinction of Working Memory Components in Relation to Mathematics.

Working memory has been consistently associated with mathematics achievement, although the etiology of these relations remains poorly understood. The present study examined the genetic and environmental underpinnings of math story problem solving, timed calculation, and untimed calculation alongside working memory components in 12-year-old monozygotic (n = 105) and same-sex dizygotic (n = 143) twin pairs. Results indicated significant phenotypic correlation between each working memory component and all mathematics outcomes (r = 0.18 - 0.33). Additive genetic influences shared between the visuo-spatial sketchpad and mathematics achievement was significant, accounting for roughly 89% of the observed correlation. In addition, genetic covariance was found between the phonological loop and math story problem solving. In contrast, despite there being a significant observed relationship between phonological loop and timed and untimed calculation, there was no significant genetic or environmental covariance between the phonological loop and timed or untimed calculation skills. Further analyses indicated that genetic overlap between the visuo-spatial sketchpad and math story problem solving and math fluency was distinct from general genetic factors, whereas g, phonological loop, and mathematics shared generalist genes. Thus, although each working memory component was related to mathematics, the etiology of their relationships may be distinct.

AI can see you: Machiavellianism and extraversion are reflected in eye-movements.

INTRODUCTION: Recent studies showed an association between personality traits and individual patterns of visual behaviour in laboratory and other settings. The current study extends previous research by measuring multiple personality traits in natural settings; and by comparing accuracy of prediction of multiple machine learning algorithms. METHODS: Adolescent participants (N = 35) completed personality questionnaires (Big Five Inventory and Short Dark Triad Questionnaire) and visited an interactive museum while their eye movements were recorded with head-mounted eye tracking. To predict personality traits the eye-movement data was analysed using eight machine-learning methods: Random Forest, Adaboost, Naive Bayes, Support Vector Machine, Logistic Regression, k Nearest Neighbours, Decision Tree and a three-layer Perceptron. RESULTS AND DISCUSSION: Extracted eye movement features introduced to machine learning algorithms predicted personality traits with above 33% chance accuracy (34%-48%). This result is comparable to previous ecologically valid studies, but lower than in laboratory-based research. Better prediction was achieved for Machiavellianism and Extraversion compared to other traits (10 and 9 predictions above the chance level by different algorithms from different parts of the recording). Conscientiousness, Narcissism and Psychopathy were not reliably predicted from eye movements. These differences in predictability across traits might be explained by differential activation of different traits in different situations, such as new vs. familiar, exciting vs. boring, and complex vs. simple settings. In turn, different machine learning approaches seem to be better at capturing specific gaze patterns (e.g. saccades), associated with specific traits evoked by the situation. Further research is needed to gain better insights into trait-situation-algorithm interactions.