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      Cognitive reserve in the healthy elderly: cognitive and psychological factors

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          Abstract

          Cognitive reserve (CR) helps explain the mismatch between expected cognitive decline and observed maintenance of cognitive functioning in older age. Factors such as education, literacy, lifestyle, and social networking are usually considered to be proxies of CR and its variability between individuals. A more direct approach to examine CR is through the assessment of capacity to gain from practice in a standardized challenging cognitive task that demands activation of cognitive resources. In this study, we applied a testing-the-limits paradigm to a group of 136 healthy elderly subjects (60–75 years) and additionally examined the possible contribution of complex mental activities and quality of sleep to cognitive performance gain. We found a significant but variable gain and identified verbal memory, cognitive flexibility, and problem-solving as significant factors. This outcome is in line with our earlier study on CR in healthy mental aging. Interestingly and contrary to expectations, our analysis revealed that complex mental activities and sleep quality do not significantly influence CR. Contrasting “high” and “low” cognitive performers revealed significant differences in verbal memory and cognitive flexibility; again, complex mental activities and sleep quality did not contribute to this measure of CR. In conclusion, the results of this study support and extend previous findings on CR in older age; further, they underline the need for improvements in existing protocols for assessing CR in a dynamic manner.

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          Most cited references 27

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          How much does schooling influence general intelligence and its cognitive components? A reassessment of the evidence.

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            Use of the extreme groups approach: a critical reexamination and new recommendations.

            Analysis of continuous variables sometimes proceeds by selecting individuals on the basis of extreme scores of a sample distribution and submitting only those extreme scores to further analysis. This sampling method is known as the extreme groups approach (EGA). EGA is often used to achieve greater statistical power in subsequent hypothesis tests. However, there are several largely unrecognized costs associated with EGA that must be considered. The authors illustrate the effects EGA can have on power, standardized effect size, reliability, model specification, and the interpretability of results. Finally, the authors discuss alternative procedures, as well as possible legitimate uses of EGA. The authors urge researchers, editors, reviewers, and consumers to carefully assess the extent to which EGA is an appropriate tool in their own research and in that of others.
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              Intelligence.

               Ian Deary (2011)
              Individual differences in human intelligence are of interest to a wide range of psychologists and to many people outside the discipline. This overview of contributions to intelligence research covers the first decade of the twenty-first century. There is a survey of some of the major books that appeared since 2000, at different levels of expertise and from different points of view. Contributions to the phenotype of intelligence differences are discussed, as well as some contributions to causes and consequences of intelligence differences. The major causal issues covered concern the environment and genetics, and how intelligence differences are being mapped to brain differences. The major outcomes discussed are health, education, and socioeconomic status. Aging and intelligence are discussed, as are sex differences in intelligence and whether twins and singletons differ in intelligence. More generally, the degree to which intelligence has become a part of broader research in neuroscience, health, and social science is discussed.
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                Author and article information

                Contributors
                Journal
                SOR-SOCSCI
                ScienceOpen Research
                ScienceOpen
                2199-1006
                29 September 2014
                : 0 (ID: e50e7fe1-ecda-4667-8c48-f60c85c57da0 )
                : 0
                : 1-8
                Affiliations
                [1 ]Department Psychology, Neuropsychology, Lud1wig-Maximilians-Universität München, Munich, Germany
                [2 ]Max Planck Institute of Psychiatry, Munich, Germany
                [3 ]Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Braga, Portugal, and ICVS/3B's, PT Government Associate Laboratory, 4710-057 Braga/Guimarães, Portugal
                Author notes
                [* ]Corresponding author's e-mail address: zihl@ 123456psy.lmu.de
                Article
                1851:XE
                10.14293/S2199-1006.1.SOR-SOCSCI.ADKHNX.v1
                © 2014 Zihl et al.

                This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

                Page count
                Figures: 1, Tables: 2, References: 48, Pages: 8
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