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It is unknown how much variation in adult mental health problems is associated with differences between societal/cultural groups, over and above differences between individuals.
To test these relative contributions, a consortium of indigenous researchers collected Adult Self-Report (ASR) ratings from 16 906 18- to 59-year-olds in 28 societies that represented seven culture clusters identified in the Global Leadership and Organizational Behavioral Effectiveness study (e.g. Confucian, Anglo). The ASR is scored on 17 problem scales, plus a personal strengths scale. Hierarchical linear modeling estimated variance accounted for by individual differences (including measurement error), society, and culture cluster. Multi-level analyses of covariance tested age and gender effects.
Across the 17 problem scales, the variance accounted for by individual differences ranged from 80.3% for DSM-oriented anxiety problems to 95.2% for DSM-oriented avoidant personality (mean = 90.7%); by society: 3.2% for DSM-oriented somatic problems to 8.0% for DSM-oriented anxiety problems (mean = 6.3%); and by culture cluster: 0.0% for DSM-oriented avoidant personality to 11.6% for DSM-oriented anxiety problems (mean = 3.0%). For strengths, individual differences accounted for 80.8% of variance, societal differences 10.5%, and cultural differences 8.7%. Age and gender had very small effects.
Overall, adults' self-ratings of mental health problems and strengths were associated much more with individual differences than societal/cultural differences, although this varied across scales. These findings support cross-cultural use of standardized measures to assess mental health problems, but urge caution in assessment of personal strengths.
The study focused on the extent to which the general factor of intelligence g and heritability coefficients of the subtests of an IQ battery correlate. Modest to strong positive correlations were found in five studies from Western countries and six studies from a Japanese meta-analysis. The results for Russian twins were compared with those of the Western and Japanese studies. Data from 402 twins aged 13 and 296 twins aged 16 showed correlations of r=−0.45 and r=−0.60, respectively. It is concluded that the two data points are clearly not in line with established findings. It may be that the link between g loadings and heritabilities is more complex than previously thought.
The Russian School Twin Registry (RSTR) was established in 2012, supported by a grant from the Government of the Russian Federation. The main aim of the registry is to contribute to Progress in Education through Gene-Environment Studies (PROGRESS). The formation of the registry is ongoing and it is expected that most schools in the Russian Federation (approximately 50,000 schools) will contribute data to the registry. With a total of 13.7 million students in Grades 1–11 (ages 7–18), the potential number of twin pairs exceeds 100,000. Apart from the large sample size and its representative nature, the RSTR has one unique feature: in collaboration with the International Advisory Committee to the Registry, genetically sensitive cross-cultural investigations are planned, aided by the use of the common assessment instruments. Other strengths of the registry include the assessment of a large sample of non-twin school children, including those studying in the same classes as the twins in the registry. It is hoped that the RSTR will provide an important research platform for national and international educationally relevant research.
Using a longitudinal twin study of Moscow children, we have studied the development of psychometric intelligence during the transition from preschool (age 6) to school (age 7). Children were tested using the Wechsler Intelligence Scale for Children (WISC). Simplex models were applied to explore the relationship of different sources of phenotypic variance. The following sources of variation were considered: genetic effects, common or shared family environment and unique environment. At age 6, genetic influences were much greater than those of shared environment but the magnitude of genetic influences decreased and the magnitude of shared environment influences increased substantially by age 7.
A mathematical model based on queuing theory is used to study the dynamics of environmental influence on twin pairs. The model takes into consideration genetic factors and effects of non-shared environment. Histograms are exploited as base analysed characteristics, with the method of minimum chi-square yielding estimated characteristics. The proposed technique was applied to analysis of longitudinal data for MZ and DZ twins. It was shown that the same environment impact may yield different contributions to final variances of the IQ parameters under investigation. Magnitudes of these contributions depend on the genetic factor represented by distributions of an analysed parameter at the point of birth. Twin Research (2000) 3, 92–98.
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