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Ann S. Masten
Researcher at University of Minnesota
Publications - 273
Citations - 49518
Ann S. Masten is an academic researcher from University of Minnesota. The author has contributed to research in topics: Resilience (network) & Developmental psychopathology. The author has an hindex of 88, co-authored 264 publications receiving 44645 citations. Previous affiliations of Ann S. Masten include Duke University & University of California, Los Angeles.
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Ordinary magic. Resilience processes in development.
TL;DR: An examination of converging findings from variable-focused and person-focused investigations of resilience suggests that resilience is common and that it usually arises from the normative functions of human adaptational systems, with the greatest threats to human development being those that compromise these protective systems.
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The development of competence in favorable and unfavorable environments. Lessons from research on successful children
TL;DR: Signals are drawn from studies of naturally occurring resilience among children at risk because of disadvantage or trauma and also from efforts to deliberately alter the course of competence through early childhood education and preventive interventions.
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Resilience and development: Contributions from the study of children who overcome adversity
TL;DR: This paper reviewed the research on resilience in order to delineate its significance and potential for understanding normal development and concluded that children who experience chronic adversity fare better or recover more successfully when they have a positive relationship with a competent adult, they are good learners and problem-solvers, engaging to other people, and they have areas of competence and perceived efficacy valued by self or society.
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The study of stress and competence in children: a building block for developmental psychopathology
TL;DR: In this article, the authors present a 3-model approach to stress resistance in a multivariate regression framework: the compensatory, challenge, and protective factor models, illustrated by selected data.