Genetic and Environmental Influences on Stressful Life Events and their Associations with Executive Functions in Young Adulthood: A Longitudinal Twin Analysis.

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Title: Genetic and Environmental Influences on Stressful Life Events and their Associations with Executive Functions in Young Adulthood: A Longitudinal Twin Analysis.
Authors: Morrison, Claire L. (AUTHOR), Rhee, Soo Hyun (AUTHOR), Smolker, Harry R. (AUTHOR), Corley, Robin P. (AUTHOR), Hewitt, John K. (AUTHOR), Friedman, Naomi P. (AUTHOR)
Source: Behavior Genetics. 2021, Vol. 51 Issue 1, p30-44. 15p.
Subjects: Life change events, Young adults, Executive function, Action theory (Psychology), Genetic correlations
Abstract: Although stress is frequently considered an environmental factor, dependent stressful life events (SLEs)––stressors that result from one's actions or behaviors––may in fact be evoked by a genetic liability. It has been suggested that dependent SLEs may be partially caused by poor executive function (EFs), higher-level cognitive abilities that enable individuals to implement goal-directed behavior. We investigated the possibility of genetic and environmental overlap between SLEs and EFs in a longitudinal twin study. We found high genetic stability in the number of dependent SLEs from age 23 to age 29, suggesting that the number of dependent stressors show persistence across time due to their genetic etiology. In addition, there was a nominally significant negative genetic correlation between a Common EF latent factor and dependent SLEs at age 23. The genetic stability of dependent SLEs and association with Common EF provides insight into how some behaviors may lead to persistent stress. [ABSTRACT FROM AUTHOR]
Copyright of Behavior Genetics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="DE" term="%22Life+change+events%22">Life change events</searchLink><br /><searchLink fieldCode="DE" term="%22Young+adults%22">Young adults</searchLink><br /><searchLink fieldCode="DE" term="%22Executive+function%22">Executive function</searchLink><br /><searchLink fieldCode="DE" term="%22Action+theory+%28Psychology%29%22">Action theory (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+correlations%22">Genetic correlations</searchLink>
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  Data: Although stress is frequently considered an environmental factor, dependent stressful life events (SLEs)––stressors that result from one's actions or behaviors––may in fact be evoked by a genetic liability. It has been suggested that dependent SLEs may be partially caused by poor executive function (EFs), higher-level cognitive abilities that enable individuals to implement goal-directed behavior. We investigated the possibility of genetic and environmental overlap between SLEs and EFs in a longitudinal twin study. We found high genetic stability in the number of dependent SLEs from age 23 to age 29, suggesting that the number of dependent stressors show persistence across time due to their genetic etiology. In addition, there was a nominally significant negative genetic correlation between a Common EF latent factor and dependent SLEs at age 23. The genetic stability of dependent SLEs and association with Common EF provides insight into how some behaviors may lead to persistent stress. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Behavior Genetics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10519-020-10017-9
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