The implications of unintended pregnancies for mental health in later life

Despite decades of research on unintended pregnancies, we know little about the health implications for the women who experience them. Moreover, no study has examined the implications for women whose pregnancies occurred before Roe v. Wade was decided—nor whether the mental health consequences of these unintended pregnancies continue into later life. Using the Wisconsin Longitudinal Study, a 60-year ongoing survey, we examined associations between unwanted and mistimed pregnancies and mental health in later life, controlling for factors such as early life socioeconomic conditions, adolescent IQ, and personality. We found that in this cohort of mostly married and White women, who completed their pregnancies before the legalization of abortion, unwanted pregnancies were strongly associated with poorer mental health outcomes in later life.Publisher PDFPeer reviewe

The implications of unintended pregnancies for mental health in later life

Despite decades of research on unintended pregnancies, we know little about the health implications for the women who experience them. Moreover, no study has examined the implications for women whose pregnancies occurred before Roe v. Wade was decided—nor whether the mental health consequences of these unintended pregnancies continue into later life. Using the Wisconsin Longitudinal Study, a 60-year ongoing survey, we examined associations between unwanted and mistimed pregnancies and mental health in later life, controlling for factors such as early life socioeconomic conditions, adolescent IQ, and personality. We found that in this cohort of mostly married and White women, who completed their pregnancies before the legalization of abortion, unwanted pregnancies were strongly associated with poorer mental health outcomes in later life.Publisher PDFPeer reviewe

SCAN: Learning Hierarchical Compositional Visual Concepts

The seemingly infinite diversity of the natural world arises from a relatively small set of coherent rules, such as the laws of physics or chemistry. We conjecture that these rules give rise to regularities that can be discovered through primarily unsupervised experiences and represented as abstract concepts. If such representations are compositional and hierarchical, they can be recombined into an exponentially large set of new concepts. This paper describes SCAN (Symbol-Concept Association Network), a new framework for learning such abstractions in the visual domain. SCAN learns concepts through fast symbol association, grounding them in disentangled visual primitives that are discovered in an unsupervised manner. Unlike state of the art multimodal generative model baselines, our approach requires very few pairings between symbols and images and makes no assumptions about the form of symbol representations. Once trained, SCAN is capable of multimodal bi-directional inference, generating a diverse set of image samples from symbolic descriptions and vice versa. It also allows for traversal and manipulation of the implicit hierarchy of visual concepts through symbolic instructions and learnt logical recombination operations. Such manipulations enable SCAN to break away from its training data distribution and imagine novel visual concepts through symbolically instructed recombination of previously learnt concepts