Reading: The Shared and Non-Shared Environment PDF

Reading 31 October 2023 13:29 Source Notes Families promote emotional and behavioural resilience to bullying: evidence of an environmental effect Introduction (Bowes et al., 2010) The protective role of families Supportive families buffer children from the impact of stressful life events. Caring, se...

Reading 31 October 2023 13:29 Source Notes Families promote emotional and behavioural resilience to bullying: evidence of an environmental effect Introduction (Bowes et al., 2010) The protective role of families Supportive families buffer children from the impact of stressful life events. Caring, sensitive and safe home environments foster adjustment in children. Several aspects of the home environment may be particularly relevant for victims of bullying, promoting resilience to this st ressful experience. Parental warmth is linked to children’s social and emotional well-being. Bullied children who have warm relationships with their mothers might have more favourable adjustment outcomes. Sibling relationships play a role in child development. After experiencing stressful life events, children who have affectionate relationships with their siblings are less likely to develop emotional problems over time. Having a warm sibling relationship may have an effect on the association between bullying victimisation and adjustment proble ms. Siblings may help to buffer children from the negative outcomes of being bullied by providing an additional source of support. The overall atmosphere at home may also be a protective factor against bullied children developing adjustment difficulties. Home environments, in particular the level of routine and organisation, are associated with children’s behavioural adjustment over and above other parent relationship measures. Having a calm, well-structured and positive home environment may reduce overall stress levels in bullied children and increase their likelihood o f achieving positive adaptation. Processes explaining the association between protective family factors and children’s resilience to bullying Environmental mediation: Supportive families may buffer bullied children from developing adjustment difficulties by providing sources of support, alleviating stress or encouraging children to develop coping mechanisms to deal with bullying victimisation. Genetic influences: Parents who provide caring home environments for their children and who have good parenting skills may al so pass on to their children genes associated with resilience. Goals of the study: To test whether family factors were associated with children’s functioning in terms of emotional and behavioural resilience t o bullying victimisation. To test whether family factors were particularly important in promoting positive developmental outcomes in bullied children c ompared to non-bullied children. To test whether protective factors in the family had an environmentally mediated effect in promoting children’s positive adjustment following bullying victimisation. Method: Genetically sensitive monozygotic (MZ) twin differences design. Measures of resilience that encompassed adjustment over time following experience of bullying victimisation. Multiple informants to reduce shared method variance. Method Participants in the Environmental Risk (E-Risk) Longitudinal Twin Study: Study involved a birth cohort of 2,232 children. The ERisk sample was drawn from a 1994–1995 birth register of twins born in England and Wales. In 1999–2000, 1,116 families with same-sex twins participated in home-visit assessments when children were 5 years old. Details of sample construction were reported elsewhere (Moffitt & the E-Risk Study Team, 2002). Follow-up home visits occurred at ages 7, 10, and 12. Questionnaires were mailed to children's teachers at ages 7, 10, and 12. The sample included 56% monozygotic twin pairs, with an even distribution of sex within zygosity. Bullying Victimization in Primary School: Bullying victimization measured using mothers' and children's self-reports. Bullying defined as repeated harmful actions involving power differences. Mothers reported that 42.1% of children had ever been bullied by age 10. 8.3% of children reported frequent bullying during primary school. Valid information from both mothers and children adhered to the definition of bullying. A total of 1,022 children (44.7%) were reported by either source as having been bullied during primary school. Emotional and Behavioral Problems at Age 10 and 12: Assessed using the Child Behavior Checklist for mothers and the Teacher's Report Form for teachers. Reporting period was 6 months before the interview. Emotional Problems scale included items in the Withdrawn and Anxious/Depressed scales. The Behavioral Problems scale included items from the Delinquency and Aggression scales. High internal consistency reliability scores for both mothers and teachers. Scores were standardized, summed, and averaged across ages to represent children's emotional and behavioral problems over time. Family Factors Between 5 and 10 Years: Maternal warmth assessed using a 6-point scale, with high inter-rater reliability. Sibling warmth assessed using a series of questions with a 3-point scale. High internal consistency reliability scores for sibling warmth. Atmosphere at home measured using items from the Coder's Impression Inventory. Scores for atmosphere at home at age 7 and 10 showed a significant association. Covariates: Children's IQ assessed at age 5 using the Wechsler Preschool and Primary Scale of Intelligence-Revised. A composite index of socioeconomic disadvantage measured at age 5. Baseline emotional and behavioral problems assessed when children were aged 5 using Achenbach family of instruments. Results Does being bullied predict emotional and behavioral problems? Bullied children had greater levels of emotional problems at ages 10–12 years compared to non-bullied children, even after controlling for difficulties prior to being bullied. Bullied children also had higher levels of behavioral problems over time compared to non-bullied children, even after controlling for pre-existing behavioral problems. Are family factors associated with emotional and behavioral resilience among bullied children? Family factors, such as maternal warmth, sibling warmth, and atmosphere at home, were associated with children's emotional and behavioral resilience to bullying victimisation. These associations remained significant even after controlling for the effects of gender, IQ, SES, and pre-existing emotional and behavioral problems. Are family factors especially relevant for bullied children? Family factors were more strongly associated with fewer emotional and behavioral problems in bullied children compared to non-bullied children. This suggests that family factors may be especially important for bullied children in helping them to cope with the negative effects of bullying. Do family factors exert an environmentally-mediated effect on children's emotional and behavioral resilience to bullying victimisation? Maternal warmth exerted an environmental protective effect on bullied children's likelihood of developing behavioral problems. This suggests that maternal warmth may help to buffer bullied children from the negative effects of bullying on their behavio r. Discussion Key findings Family factors (maternal warmth, sibling warmth, and positive atmosphere at home) are uniquely associated with positive emotional and behavioural adaptation over a two-year period following bullying victimisation. The effects of family factors on emotional and behavioural development are significantly greater for bullied children compare d to non-bullied children. Maternal warmth protects against the development of adjustment difficulties for victims of bullying independent of other prot ective factors common to members of the family in which the bullied twins grew up, including genetic factors. Limitations The sample comprised twins, so it is uncertain whether the results generalise to singletons. Mother's reports were used for both bullying victimisation and children's adjustment outcomes, so results could be inflated by shared method variance. The measure of sibling warmth reflected warmth between twins in a pair, so it is possible that the protective effect may be d ifferent from siblings of a different age. The findings indicated a protective effect of family factors on children's adjustment at ages 10 –12 years. It is possible that other factors are important in older age groups as children begin to spend less time at home. Implications Findings highlight the importance of including families in school-based intervention programmes aimed at reducing difficulties experienced by bullied children. Understanding the mechanisms by which family factors help to buffer children from emotional and behavioural difficulties foll owing bullying victimisation is a particularly important aim for future work on resilience in bullied children and may repres ent a key area for clinical intervention. Meta-analysis of the heritability of human traits based on fifty years of twin studies Introduction Additive genetic variation is the primary source of observed variation in human traits 69% of traits have heritability estimates greater than 50%, indicating that additive genetic variation is the primary source of observed variation. This finding is consistent with recent results from large-scale genome-wide association studies (GWAS). (Polderman et al., 2015) Shared environment and non-additive genetic variation have little influence on observed variation in most traits Shared environment influences do not have a significant impact on most traits (less than 10% of traits have heritability esti mates less than 30%). Non-additive genetic influences (such as gene-gene interactions) also appear to have a relatively small impact on most traits. Heritability estimates cluster strongly within functional domains Heritability estimates are highly correlated within functional domains (e.g., cognitive traits, physical traits, and psychiat ric disorders). This suggests that common genetic factors influence the variation in traits within a functional domain. The reported heritability for all traits is 49% The average heritability estimate for all traits is 49%. This is higher than previous estimates, which may be due to the larger sample size and the inclusion of a wider range of trai ts in this study. Implications This study provides the most comprehensive analysis of the causes of individual differences in human traits thus far. The findings will guide future gene-mapping efforts by focusing on additive genetic variation as the primary source of observed variation. The MaTCH webtool can be used to visualize the results of this study. Findings Non-random Distribution of Studied Traits Skewed distribution of studied traits ○ 51% of twin studies focus on traits classified under the psychiatric, metabolic, and cognitive domains. ○ Traits classified under the developmental, connective tissue, and infection domains together account for less than 1% of all investigated traits. Most 10 investigated traits: ○ Temperament and personality functions PSYC0036 Genes and Behaviour Page 1 ○ Weight maintenance functions ○ General metabolic functions ○ Depressive episode ○ Higher-level cognitive functions ○ Conduct disorders ○ Mental and behavioral disorders due to use of alcohol ○ Anxiety disorders ○ Height ○ Mental and behavioral disorders due to use of tobacco Underrepresentation of twin studies in certain regions ○ Twin studies are underrepresented in South America, Africa, and Asia. Implications ○ The skewed distribution of studied traits in twin studies suggests that there is a need for more research on traits classifie d under the developmental, connective tissue, and infection domains. ○ The underrepresentation of twin studies in certain regions suggests that there is a need to expand twin research to these reg ions. Equal Contribution of Genes and Environment Key findings ○ There is no evidence of systematic publication bias in twin studies. ▪ no evidence that studies with larger sample sizes were more likely to be published than studies with smaller sample sizes ○ The weighted averages of correlations for monozygotic (rMZ) and dizygotic (rDZ) twins are 0.636 and 0.339, respectively. ▪ suggests that genes and environment contribute equally to the variation in most traits. ○ The reported heritability (h2) across all traits is 0.488, and the reported estimate of shared environmental effects (c2) is 0.174. ○ Heritability estimates cluster in functional domains, with the highest heritability estimates for traits classified under the ophthalmological, ear, nose and throat, dermatological, and skeletal domains. ▪. This suggests that there are common genetic factors that influence the variation in traits within the same functional domain ○ The lowest heritability estimates are for traits classified under the environment, reproduction, and social values domains. ▪ suggests that there is more variation in these traits due to environmental factors than genetic factors. ○ The largest influence of c2 is for traits classified under the cell, infection, hematological, endocrine, reproduction, socia l values, environment, and skeletal domains. ▪ suggests shared environmental effects are more important for traits that are more influenced by shared experiences More Causes of Variation in Human Traits No evidence of heterogeneity by sex ○ The weighted averages of twin correlations and reported h2 and c2 values do not show evidence of heterogeneity by sex. ○ This suggests that the genetic and environmental influences on trait variation are similar for males and females. Decrease in twin resemblance after adolescence ○ There is a decrease in monozygotic and dizygotic twin resemblance after adolescence and an accompanying decrease in the estim ates of both h2 and c2. ○ This suggests that environmental factors play a greater role in influencing trait variation in adulthood than in childhood. Discrepancy between estimated and reported h2 and c2 values ○ Applying Falconer's equations to the weighted averages of rMZ and rDZ yields an ĥ2 estimate of 0.593 and a ĉ2 estimate of 0.042, which are different from the weighted averages of reported h2 and c2 values. ○ This discrepancy is due to sampling bias in estimating h2 from the full model, which is caused by per-study choices in fitting ACE or ADE models based on the observed pattern of twin correlations. Twin correlations are consistent with a simple additive model ○ Across all traits, the vast majority of studies (84%) are consistent with the hypothesis that twin resemblance is solely due to additive genetic variation. ○ This suggests that a simple and parsimonious model of trait inheritance, in which trait variation is due to the independent effects of multiple genes, can explain the majority of the observed variation in human traits. Implications ○ The findings of this twin study provide strong evidence that additive genetic variation is the primary source of variation in human traits. ○ These findings suggest that future gene -mapping efforts should focus on identifying the genetic variants that contribute to additive genetic variation. Most specific traits follow an additive genetic model Twin correlations consistent with 2rDZ = rMZ ○ Most prominent in neurological, ear, nose and throat, cardiovascular and ophthalmological domains (99.5%, 97%, 95% and 87% of studies, respectively) ○ Least prominent in activities (35%), reproduction (44%) and dermatological (45%) domains Proportion of studies consistent with 2rDZ = rMZ for specific traits ○ 21 of 59 specific traits had a proportion less than 0.50 ○ 38 of 59 specific traits had a proportion greater than 0.50 Top 20 most investigated specific traits ○ 12 traits had a majority of studies consistent with a model where variance was solely due to additive genetic variance and no n-shared environmental variance ○ 8 traits had a pattern of monozygotic and dizygotic twin correlations inconsistent with this model ▪ Conduct disorders ▪ Height ▪ Higher-level cognitive functions ▪ Hyperkinetic disorders ▪ Mental and behavioral disorders due to the use of alcohol ▪ Mental and behavioral disorders due to the use of tobacco ▪ Other anxiety disorders ▪ Weight maintenance functions Discussion Heritability of all human traits ○ No trait had a weighted heritability estimate of zero Clustering of relative influences of genes and environment ○ Not randomly distributed across all traits ○ Cluster in functional domains Underestimation of true trait heritability ○ By reported estimates of variance components from model -fitting ○ When compared with heritability based on twin correlations Two-thirds of traits show a simple additive genetic model ○ Trait resemblance solely due to additive genetic variation ○ Causal genetic variants can be detected using a simple additive genetic model for the majority of complex traits One-third of traits do not follow a simple additive genetic model ○ A simple additive genetic model does not sufficiently describe the population variance for these traits ○ An incorrect assumption about narrow-sense heritability can lead to a mismatch between the results from gene -finding studies and previous expectations Gene-mapping studies ○ May yield disappointing results if the pattern of twin correlations is consistent with a substantial contribution from shared environmental factors ○ May be tempting to fit non-additive models if the cause of departure from a simple additive genetic model is the existence of non -additive genetic variation ○ Statistical power of such scans is extremely low owing to the many non -additive models that can be fitted and the penalty incurred by multiple testing Traits for which an additive model cannot be assumed ○ Dizygotic twin correlations are higher than half the monozygotic twin correlations, suggesting that shared environmental effe cts are causing the deviation from a simple additive genetic model Data from twin pairs only do not provide sufficient information ○ To resolve the actual causes of deviation from a simple additive genetic model More detailed studies ○ May identify the likely causes of such deviation ○ May as such uncover epidemiological or biological factors that drive family resemblance Additional data are required ○ To make stronger inferences about the causes underlying resemblance between relatives for traits that deviate from the additi ve genetic model ○ For example, from large population samples with extensive phenotypic and DNA sequence information, detailed measures of envir onmental exposures and larger pedigrees including non -twin relationships Inference based on twin studies published between 1958 and 2012 ○ Generally applies to complex traits but does not necessarily generalize to mendelian subtypes of traits Conclusion ○ results provide the most comprehensive empirical overview of the relative contributions of genes and environment to all human traits that have been studied in twins thus far ○ Can guide and serve as a reference for future gene -mapping efforts PSYC0036 Genes and Behaviour Page 2 Maternal Expressed Emotion Predicts Children’s Antisocial Behavior Problems: Using Monozygotic-Twin Differences to Identify Environmental Effects on Behavioral Development Introduction: (Caspi et al., 2004) Siblings in the same family often exhibit significant differences in their behavior. These differences may arise from various factors, including genetic makeup, age, and sex. Even monozygotic (MZ) twins can exhibit differences despite sharing identical genes, age, and sex. For psychiatric disorders, MZ twins raised in the same family can be discordant in over 50% of cases, indicating the influenc e of nonshared environmental factors. Behavioral genetics research has emphasized nonshared environmental experiences unique to each sibling growing up in the same family. Importance of Nonshared Environmental Experiences: Historically, nonshared environmental experiences have been recognized but not adequately measured. Psychosocial researchers need to measure nonshared experiences to determine their impact on behavioral differences between siblings. The present study focuses on mothers' expressed emotions toward their children and their role in early-emerging antisocial behavior problems in young children. Early-Onset Antisocial Behavior Problems: Early-onset antisocial behavior problems in children have long-lasting and significant consequences across various aspects of life. Parenting has been implicated in the origins of these individual differences, but the role of specific parenting attitudes an d behaviors is contested on empirical grounds. Twin and adoption studies have identified nonshared environmental factors influencing children's antisocial behavior problems. Emotional Attitudes of Mothers: Studies have shown that mothers of children with behavioral disorders express more criticism, fewer positive comments, and le ss warmth toward their children. These studies typically compare mother-child pairs from different families. Within-Family Designs: To address the limitations of between-families research, researchers have increasingly used within-family, 2-children-per-family designs. These designs aim to determine if nonshared maternal treatment is associated with behavioral differences between siblings growing up in the same family. Difference-score models and residualized-score models are often used to examine this relationship. Genetically Informative Designs: Genetically informative designs are necessary to distinguish environmental effects from genetic child effects. They help determine whether nonshared environmental experiences account for behavioral differences between siblings. MZ twins provide a unique opportunity to study nonshared environments, as they are genetically identical. Cross-Sectional Limitations: Cross-sectional studies, even using the MZ-difference method, have inferential limitations, as they do not rule out environmental child effects. A cross-sectional association suggests an environmental effect but does not exclude the possibility of behavioral differences driving differential maternal treatment. Single-Source Measurement: Using the same source for both environmental experience and behavioral outcome may inflate associations. Correlations between differential experiences and differential outcomes can drop when different sources are used. It's important to establish that nonshared family experiences predict independently ascertained behavioral differences. Study Design: The present study uses a genetically sensitive MZ-twin design, longitudinal data, and independent measurements of maternal expressed emotions and children's antisocial problem s. Qualitative interviews with mothers of discordant MZ twins are conducted to generate hypotheses for future research into why mothers may feel differently toward genetically identical twin children. Methods The Environmental Risk Study Sample: Participants are members of the Environmental Risk (E-Risk) Longitudinal Twin Study. Investigates how genetic and environmental factors shape children's development. Follows a sample of families with young twins interviewed at ages 5 and 7. E-Risk study focused on consecutive birth cohorts (1994 and 1995) of twins born in England and Wales. Excluded opposite-sex twin pairs and began with same-sex twins. Targeted a sample size of 1,100 families, allowing for attrition while maintaining statistical power. Used a high-risk stratification sampling frame, identifying high-risk families with young mothers. Final sample represents two-thirds of mothers in the general population and one-third of young mothers. Sample Details: Of the 1,203 eligible families, 1,116 (93%) participated in home-visit assessments at age 5. Data from teachers were obtained for 94% of the cohort children. Zygosity was determined using a questionnaire with 95% accuracy, and ambiguous cases were resolved with DNA testing. The sample consisted of 56% MZ and 44% DZ twin pairs, with an even distribution of sex within zygosity (49% male). A follow-up home visit was conducted at age 6.5 years on average (age 7 assessment), with data collected for 98% of the families. Teachers returned questionnaires for 91% of the twins in the follow-up. Maternal Expressed Emotion: Expressed emotion was measured using a 5-minute speech sample provided by mothers about each child. Trained interviewers encouraged mothers to describe their children freely, with minimal interruptions. Speech samples were audiotaped, and data were missing for 9% of the sample due to refusal or technical issues. Two trained raters coded audiotapes, considering elements such as positive comments, negative comments, negativity, and warmth. Positive comments were counted based on content and tone, while negative comments had to exhibit both negative tone and conte nt. Negativity was rated on a 6-point scale, describing the global level of negativity expressed in the interview about the child. Warmth was also rated on a 6-point scale, assessing the warmth of the respondent's personality expressed in the interview about the child. Children's Antisocial Behavior Problems: Antisocial behavior problems were assessed at ages 5 and 7 using the Achenbach family of instruments, including the Child Beh avior Checklist and Teacher Report Form. The externalizing syndrome in this article is the sum of items in the Delinquent Behavior and Aggressive Behavior scales. The parent and teacher reports of antisocial behavior problems had high internal consistency reliabilities of.90. Cross-informant (parent-teacher) correlations ranged from.31 to.43, and longitudinal correlations ranged from.54 to.68, indicating the consistenc y of antisocial behavior problems assessment. Results Is Maternal Expressed Emotion Associated With Children’s Antisocial Behavior Problems? A Comparison Between Children in Different Families: Maternal expressed emotion was significantly correlated with children's antisocial behavior problems, both cross -sectionally (age 5) and longitudinally (age 7), as reported by both mothers and teachers. Longitudinal regression analyses confirmed that maternal expressed emotion at age 5 accounted for variance in children's anti social behavior problems at age 7 beyond the influence of prior behavior problems, ruling out a child effect. Similarities and Differences in How MZ Twins Are Treated and in Their Behavior Problems: MZ twins were very similar in their antisocial behavior problems according to both parents and teachers. While MZ twins share identical genes, they were not phenotypically identical, with non -shared environmental factors accounting for approximately one quarter to one third of the variance in their behavior problems. Are Differences in Maternal Expressed Emotion Related to Behavioral Differences Between MZ Twins Reared in the Same Family? Differences in mothers' expressed emotion toward their 5-year-old MZ twins were significantly correlated with differences in the twins' behavior problems, both cross -sectionally (age 5) and longitudinally (age 7), regardless of whether mothers or teachers rated the children. Regression analyses confirmed that differences in maternal expressed emotion predicted behavioral differences between MZ twins at age 7 after controlling for age 5 behavioral differences within the twin pair. Why Do Some Mothers Feel Differently Toward Their Twins? A Qualitative Inquiry: The qualitative inquiry revealed several explanations for why mothers might feel differently toward their genetically identical twins, such as differential parenting due to illness in one twin, maternal folk beliefs about twin personalities, the identification of one twin as more like the mother, and a mother's negative feelings directed toward one twin due to an acrimonious relation ship with the twins' father. These findings suggest that maternal expressed emotion can be associated with differences in antisocial behavior problems in twins, and various factors contribute to differential treatment and emotional responses by mothers to their genetically identical twins. Discussion The study showed that maternal emotional attitudes are associated with children's antisocial behavior problems. The study is the first to support the conclusion that maternal expressed emotion is an environmentally mediated risk factor f or children's antisocial behavior problems. It ruled out biases in maternal reporting by showing that maternal expressed emotion correlated with teachers' ratings. It ruled out the child effect by demonstrating that maternal expressed emotion predicted changes in antisocial behavior even when controlling for children's behavior at age 5. It ruled out genetic mediation by revealing that differences in maternal expressed emotion predicted differences between genetically identical MZ twins. Some limitations include the possibility of unmeasured third variables, the lack of maternal expressed emotion data at age 7, and the need for further research in other populations and longer-term influences. The study has implications for socialization theory, emphasizing that maternal expressed emotion plays a causal role in creat ing behavioral differences between children. Researchers are encouraged to adopt the expressed emotion methodology for studying differential parenting and to explore the mechanisms by which maternal behavior influences children. Future research should delve into expressed emotion as an outcome variable, aiming to understand why mothers feel differently toward their twins, potentially due to factors like illness, folk beliefs, self-identification, or acrimonious relationships. Genetics affects choice of academic subjects as well as achievement (Rimfield et al., 2016) Introduction Heritability of educational achievement Educational achievement at age 18 is substantially heritable, with genetic factors accounting for 57% of the variation in achievement across multiple subjects. This suggests that genetic differences between children play a major role in explaining why some children perform better at s chool than others. Educational achievement is a strong predictor of many life outcomes. Shared environmental factors, such as home or school environment, are important in educational achievement. Previous research has shown that educational achievement is substantially heritable from the early school years until the end of compulsory education. This high heritability of educational achievement is explained by children's aptitude, or intelligence, but also by a constel lation of genetically related traits, such as self-efficacy, behavioral problems, and personality. Previous research demonstrates that genetic differences between children influence both their academic performance and how ea sy or enjoyable they find learning in general. Heritability of the decision to continue studying at A-level The decision to continue studying at A-level is also substantially heritable, with genetic factors accounting for 69% of the variation in this decision. PSYC0036 Genes and Behaviour Page 3 This suggests that genetic differences between children may also influence their decision to continue their education after compulsory education. We hypothesize that given a choice, children will select, modify and create their own educational experiences in part based o n their genetic propensities, a concept known as genotype-environment correlation. Children are not passive recipients of instruction, but instead are active participants in their path to knowledge. In a more personalized education system, children would choose educational subjects early allowing them to focus on their str engths and interests. Until the age of 16, students in England and Wales have little choice in subject choice. At age 16, after compulsory education, students are free to choose all of their A-level subjects from over 80 different options. Heritability of A-level subject choice Students' choice of A-level subjects is also heritable, with genetic factors accounting for 45% of the variation in subject choice. This suggests that genetic differences between children may also influence their preferences for different subjects. Role of shared environmental factors Shared environmental factors, such as school and family influences, play a relatively minor role in influencing educational achievement and subject choice, accounting for 2-5% of the variation. Role of non-shared environmental factors Non-shared environmental factors, such as child-specific school recommendations and parental advice, play a larger role in influencing educational achievement and subject choice, accounting for 37-48% of the variation. Current study The current study investigates the extent to which students’ choice to do A-levels and their choice of A-level subjects as well as subsequent achievement can be explained by genetic or environmental influences. The study uses a large UK-representative twin sample, the Twins Early Development Study (TEDS), to investigate the genetic and environmental contributi ons in choosing to do A-levels and subject choice at age 16, as well as achievement in the chosen subjects at age 18. Hypotheses The heritability of school achievement at age 18 will be substantial, and it will be substantial across the multiple subjects children study at school after compulsory education. The decision to continue studying at A-level and the students’ subject choice is made on the basis of their genetic propensities. Shared environmental factors that reflect shared school and family influences and non-shared environment such as child-specific school recommendations and parental advice will also influence subject choice. Method Participants: The sample was derived from the Twins Early Developmental Study (TEDS), representing twins born in England and Wales between 1994 and 1996. Over 10,000 twin pairs from the original 16,000 recruited remained actively involved in TEDS. Participants with severe medical or psychiatric issues and those with mothers experiencing severe medical complications during pregnancy were excluded. Zygosity (whether twins are identical or non-identical) was determined through a parent-reported questionnaire and confirmed by DNA testing if necessary. The final sample for analysis included 13,226 individuals, organized into 6584 twin pairs. Measures: Compulsory education in England and Wales ends with the General Certificate of Secondary Education (GCSE) typically taken at age 16. Post-GCSE, students can choose to leave formal education or continue for further education, including A-levels, in various subjects. A-levels are two-year courses covering over 80 subjects, with students typically selecting three to four subjects. Students' grades on A-levels are converted into a points-based system for university admissions. Composite variables were created for STEM (science, technology, engineering, and mathematics), English, second language, and humanities subjects. A-level mean grade represents the average grade across all subjects. Analyses: Data were analysed using ANOVA to explore sex and zygosity differences in A-level grades. The achievement scores were corrected for age and sex differences using the regression method. Twin analyses were conducted using structural equation modelling to estimate the genetic (A), shared environmental (C), and u nique environmental (E) components. The data were corrected for normality using the van der Waerden transformation. Power calculations ensured adequate power for subject choice and achievement variables. A sex-limitation model examined genetic and environmental differences across sexes. A liability threshold model assessed the presence or absence of subject choice using concordances between twins and tetrachoric correlations to model the liability threshold. Results Results - Descriptive Statistics: Approximately 50% of the participants (6613 students) in the study continued their studies at A -level. There were significant differences between girls and boys in choosing to do A-levels, with 57% of females and 43% of males. Girls and boys chose STEM subjects in roughly equal proportions, but they had preferences within STEM (e.g., biology for girls, physics for boys). Girls more often chose humanities subjects, such as English, second language, and psychology. Results - A-level Exam Results: Girls and boys did not differ significantly in their A-level exam results at age 18, except for overall A-level grade, humanities composite, and psychology. Sex and zygosity explained less than 1% of the variance in A-level results, except for psychology, where they explained 5% of the variance. The data were corrected for small mean sex and zygosity differences for subsequent analyses. Results - Twin Analyses: Quantitative sex differences were investigated using the full sex-limitation model, but no significant qualitative sex differences emerged. Some significant quantitative sex differences emerged for A-level grade, mathematics, chemistry, history, and humanities, but the differences were small. For example, for A-level mean grade, heritability was 52% for girls and 57% for boys. The full sample was used, combining males and females, to increase statistical power. The liability threshold model was used to calculate ACE estimates for choosing to study at A -level and A-level subject choice. Results - Heritability and Shared Environment: Choosing to do A-levels was moderately heritable (44%), and shared environment had a substantial influence (47%). A-level subject choice was more heritable (50-80%) and less influenced by shared environment (0-23%). A-level mean performance was highly heritable (59%) with only a small proportion of the variance explained by shared environmen tal factors (7%). Heritability was non-significantly lower for the humanities composite (49%) compared to STEM (65%). Differences in heritabilities across subjects (ranging from 35% for history to 76% for chemistry) could not be definitively d etermined due to small sample sizes. Discussion Key points: Genetic factors influence both academic choice and achievement in 16-year-olds. The influence of genetic factors is stronger for subject choice than for A-level grades. Shared environment has a substantial influence on the choice of whether or not to do A-levels. Possible explanations for the influence of genetic factors on academic choice: Previous achievement and ability: Students may make A-level choices based on their previous educational achievement, which is substantially heritable. General intelligence: General intelligence, which is also substantially heritable, may contribute to these choices independently from previous achievement. Aptitudes: Students may choose subjects that they enjoy, and this could be a cause rather than just an effect of their previous achievem ent. Implications for education: Personalized learning environments: The findings of the study suggest that children's educational potential could be maximized if environments were more personal ized and suited to their specific needs. Choice in the curriculum: Giving children a more active choice in their curricula would allow them to become more active participants in their educatio n rather than passive receivers of instruction. Future research: Identifying the specific DNA sequences responsible for heritability. Developing polygenic scores that can predict academic choice and achievement at A-levels. Investigating the role of genotype-environment correlation in academic choice and achievement. PSYC0036 Genes and Behaviour Page 4