Intelligence, Information Processing, & Aging Article List

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Papers:

 

Ennis, G. E., Moffat, S. D., & Hertzog, C. (2016). The cortisol awakening response and cognition across the adult lifespan. Brain and Cognition, 105, 66-77.

ABSTRACT: Although the hippocampus is thought to play a central role in the regulation of the cortisol awakening response (CAR), results from past studies examining the relationship between the CAR and hippocampal-mediated memory and cognition have been mixed. Inconsistent findings may be due to the use of cortisol samples collected on only 1–2 days since reduced sampling can permit unstable situational factors to bias results. We used cortisol assessments from 10 consecutive days to test the relationship of the CAR to episodic memory, working memory, and processing speed in a sample of healthy young, middle-aged, and older adults (age range: 23–79 years; N = 56). We tested if the relationship between the CAR and cognition would depend upon age and also tested if other cortisol measures, specifically waking cortisol, diurnal cortisol output (i.e., area under the curve) and diurnal cortisol slope (linear and quadratic), would be related to cognition. We found that a more positive CAR slope was related to better episodic memory and that this relationship did not depend upon age. The CAR was not significantly related to working memory. The relationship of the CAR to processing speed was not significant when using a CAR measure that corrected for non-compliant cortisol sampling. We also found that higher waking cortisol was significantly related to better working memory, but not episodic memory or processing speed. Neither diurnal cortisol output nor diurnal linear cortisol slope was significantly related to cognitive functioning. Future work should investigate the mechanisms underpinning the relationship of the cortisol awakening process to cognitive functioning.

External link: doi:10.1016/j.bandc.2016.04.001

 

Hertzog, C. (2011). Intelligence in later adulthood. In R. J. Sternberg and S. B. Kaufman (Eds.), The Cambridge Handbook of Intelligence (3rd Ed.; pp. 174-190). Cambridge: Cambridge University Press.

ABSTRACT: The field of gerontology – the scientific study of aging – emerged as a major scientific discipline in the 20th century (e.g., Birren, 1964). Research on intelligence and intellectual development played a major role in shaping the field of psychological gerontology (e.g., Botwinick, 1977). This chapter reviews what is known and not yet known about adult intellectual development after decades of research on the topic. Most of the information we have available concerns aspects of what Sternberg (1985) has defined as academic intelligence (based on traditional psychometric tests of human abilities). This chapter focuses on what is known about these types of human abilities and their correlates, although I also briefly treat other aspects of intellect, such as practical intelligence and tacit knowledge.

 

Jopp, D., & Hertzog, C. (2010). Assessing adult leisure activities: An extension of a self-report activity questionnaire. Psychological Assessment, 22, 108-120.

ABSTRACT: Everyday leisure activities in adulthood and old age have been investigated with respect to constructs such as successful aging, an engaged lifestyle, and prevention of age-related cognitive decline. In the present study, we sought to augment the Victoria Longitudinal Study activity questionnaire by adding items on physical and social activities, and to validate a shortened version of the questionnaire. Our proposed leisure activity model included 11 activity categories: three types of social activities (i.e., activities with close social partners, group-centered public activity, religious activities), physical, developmental, and experiential activities, crafts, game playing, TV watching, travel, and technology use. Confirmatory factor analyses validated the proposed factor structure in two independent samples. A higher-order model with a general activity factor fitted the activity factor correlations with relatively little loss of fit. Convergent and discriminant validity for the activity scales were supported by patterns of their correlations with education, health, depression, cognition, and personality. The questionnaire has good reliability and validity, and is suitable to assess leisure activities in young, middle-aged, and older individuals.

External link: doi: 10.1037/a0017662

 

Hertzog, C. (2009). Use it or lose it: An old hypothesis, new evidence, and an ongoing controversy. In H. Bosworth & Hertzog (Eds.), Cognition and Aging: Research and Methodologies and Empirical Advances (pp. 161 – 179) Washington, D. C.: American Psychological Association.

ABSTRACT:One of the more interesting and difficult questions regarding aging is the extent of malleability or plasticity in cognitive development over the adult life span. Few scientists question that there is a casual relation between biological aging mechanisms, as they affect the central nervous system, and some aspects of cognitive function.  What are at stake, however, are two important issues. First, to what extent do observed age differences and age changes in cognitive tasks reflect the effects of neurobiological aging as opposed to other influences such as environmental context (e.g., Hertzog, 2008; Hess, 2005)? Second do people’s behaviors influence the course of their own cognitive development? Sine-Morrow (2007) posed this question in terms of how people’s life choices influence their cognitive development in adulthood.

External link: doi: 10.1037/11882-008

 

Hertzog, C., Kramer, A.F., Wilson, R.S., & Lindenberger, U. (2009). Enrichment effects on adult cognitive development: Can the functional capacity of older adults be preserved and enhanced? Psychological Science in the Public Interest (Supplement to Psychological Science). Washington, D. C.: Association for Psychological Science.

ABSTRACT: In this monograph, we ask whether various kinds of intellectual, physical, and social activities produce cognitive enrichment effects—that is, whether they improve cognitive performance at different points of the adult life span, with a particular emphasis on old age. We begin with a theoretical framework that emphasizes the potential of behavior to influence levels of cognitive functioning. According to this framework, the undeniable presence of age-related decline in cognition does not invalidate the view that behavior can enhance cognitive functioning. Instead, the course of normal aging shapes a zone of possible functioning, which reflects person-specific endowments and age-related constraints. Individuals influence whether they function in the higher or lower ranges of this zone by engaging in or refraining from beneficial intellectual, physical, and social activities. From this point of view, the potential for positive change, or plasticity, is maintained in adult cognition. It is an argument that is supported by newer research in neuroscience showing neural plasticity in various aspects of central nervous system functioning, neurochemistry, and architecture. This view of human potential contrasts with static conceptions of cognition in old age, according to which decline in abilities is fixed and individuals cannot slow its course. Furthermore, any understanding of cognition as it occurs in everyday life must make a distinction between basic cognitive mechanisms and skills (such as working-memory capacity) and the functional use of cognition to achieve goals in specific situations. In practice, knowledge and expertise are critical for effective functioning, and the available evidence suggests that older adults effectively employ specific knowledge and expertise and can gain new knowledge when it is required.

External Link: doi: 10.1111/j.1539-6053.2009.01034.x

 

Hertzog, C. (2008). Theoretical approaches to the study of cognitive aging: An individual differences perspective. In S. M. Hofer & Alwin (Eds.), Handbook of Cognitive Aging (pp 34-49).Thousand Oaks, CA: Sage Publications

ABSTRACT: This chapter evaluates the hypothesis that life style and intellectually engaging activities have a positive effect on adult intellectual development. Life style can influence cognition by multiple pathways, including effects of practicing cognitive operations, the build-up and benefits of knowledge for cognition in everyday life, and the effects of physical exercise on brain physiology. A recent critique of evidence for cognitive enrichment by life style by Salthouse (2006) is acknowledged but also critiqued. Although more evidence, and more definitive evidence of life style effects on cognition is needed, evidence is mounting that behaviors do influence the neural substrates for cognition, and cognition itself.

External Link: doi: http://dx.doi.org/10.4135/9781412976589.n2

 

 

Jopp, D., & Hertzog, C. (2007). Activities, self-referent memory beliefs, and cognitive performance: Evidence for direct and mediated relations. Psychology and Aging, 22(4), 811-825.

ABSTRACT: In this study, the authors investigated the role of activities and self-referent memory beliefs for cognitive performance in a life-span sample. A factor analysis identified 8 activity factors, including Developmental Activities, Experiential Activities, Social Activities, Physical Activities, Technology Use, Watching Television, Games, and Crafts. A second-order general activity factor was significantly related to a general factor of cognitive function as defined by ability tests. Structural regression models suggested that prediction of cognition by activity level was partially mediated by memory beliefs, controlling for age, education, health, and depressive affect. Models adding paths from general and specific activities to aspects of crystallized intelligence suggested additional unique predictive effects for some activities. In alternative models, nonsignificant effects of beliefs on activities were detected when cognition predicted both variables, consistent with the hypothesis that beliefs derive from monitoring cognition and have no influence on activity patterns.

External link: doi: 10.1037/0882-7974.22.4.811

 

Hertzog, C., & Robinson, A. E.  (2005).  Metacognition and intelligence.  In O. Wilhelm & R. W. Engle (Eds.) Understanding and measuring intelligence. London: Sage, 101-123.

ABSTRACT: The construct of metacognition, broadly defined as cognition about cognition, has played an increasingly prominent role in cognitive psychologists’ thinking about cognition (e.g., Hacker, Dunlosky, & Graesser, 1998; Metcalfe & Shimamura, 1994; Nelson & Narens, 1990). Metacognition has also been an important focus in domains of developmental psychology (e.g., Hertzog & Hultsch, 2000; Schneider & Pressley, 1997), social psychology (Ehrlinger & Dunning, 2003), educational psychology (Thiede, 1999; Schraw & Nietfeld, 1998; Winne, 1998), and applied cognitive psychology (Perfect & Schwartz, 2002). Metacognition, framed as a class of components of the architecture of executive functioning, has also been featured in at least some theories of intelligence (e.g., Naglieri, 1997; Sternberg, 1985). Given the importance of cognitive control for concepts of fluid intelligence, and the evidence for frontal lobe involvement in processes of achieving cognitive control (see Heitz, Unsworth, & Engle, this volume; Kane, this volume), the potential importance of metacognition as part of the architecture supporting intelligence and cognition should be apparent. It is reinforced by evidence that frontal damage impairs metacognition (Shimamura, 1994). However, with some important exceptions (e.g., Metcalfe & Wiebe, 1987; Stankov, 2000), the bulk of recent research on metacognition has been in the domain of learning and memory (e.g., Schwartz, 1994), and the methodological advances represented in this work have had little impact on theorizing about intelligence or studies of metacognition-intelligence relationships. Our chapter reviews some critical features and findings of recent empirical research on metacognition in these areas, and identifies relevant linkages to research on intelligence.

External Link: doi: 10.4135/9781452233529.n7

 

Hertzog, C., & Bleckley, M .K. (2001).  Age differences in the structure of intelligence: Influences of information processing speed.  Intelligence, 29, 191-217.

ABSTRACT: A battery of widely-studied psychometric ability tests, measuring 7 primary abilities, was administered to undergraduate students and a cross-sectional sample, ranging in age from 43 to 78. The battery included measures of how rapidly individuals could mark answer sheets when provided with booklets containing correct answers to test questions. Confirmatory factor analyses showed that the ability factors could be identified in all age groups, but that the factor structure did not show (metric) invariance of factor loadings across age groups. Factor correlations increased with age, as did the ability tests’ communalities, indicating a type of dedifferentiation of the primary ability factor structure. Thurstone’s Primary Mental Abilities Verbal Meaning test was shown to have a strong relationship to answer-marking speed, independent of Verbal Ability, and this relationship was higher for older adults. Several ability factors had high correlations with a factor measuring answer sheet speed, and controlling for speed by removing the answer sheet-related variance attenuated the pattern of higher factor correlations for older adults. Findings were consistent with the view that speed of information processing can be both an important correlate of individual differences in rates of intellectual aging and a performance-specific confound that distorts estimates of age-related change in psychometric ability tests.

External Link: doi:10.1016/S0160-2896(00)00050-7

 

Hertzog, C. (1991).  Aging, information processing speed, and intelligence. In K. W. Schaie (Ed.), Annual review of Gerontology and Geriatrics, 11, 55-79. New York: Springer.

ABSTRACT: One of the most widely demonstrated findings in gerontology is the slowing of the information processing speed in adulthood (Birren, 1965, 1974; Birren, Woods, & Williams, 1980; Salthouse, 1985a, 1985b; Welford, 1977) Age-related slowing has been found in a large number of cross-sectional studies comparing young and old adults in performance on a wide variety of experimental tasks, including simple and choice reaction time (RT). Performance on virtually every information processing task measuring cognitive or perceptual mechanisms is slowed, on average, in old age, and gerontologists have concluded that the speed of execution of almost all psychological processes, including such constructs as pattern recognition, memory scanning, perceptual synthesis, and mental rotation, are affected. A number of studies conducted in the 1950s and 1960s indicate that there may be slowing of peripheral nerve conduction. The literature also indicates, however, that age differences in RT tasks probably reflect slowing in the central nervous system and its functioning and cannot be attributed merely to slowed perceptual or peripheral motor tasks (Birren, 1965). Moreover, accentuated age-related slowing is observed when tasks require cognitive transformations of stimuli in terms of meaning or implications for response behavior (Brinley, 1965).

External Link:

 

Hertzog, C. (1989).  The influence of cognitive slowing on age differences in intelligence.  Developmental Psychology, 25, 636-651. 

ABSTRACT: A large cross-sectional sample took a battery of psychometric tests measuring multiple primary abilities, including the Primary Mental Abilities (PMA) test used in Schaie’s (1983) longitudinal studies. The battery also included measures in perceptual speed and speed in working with the PMA answer sheets. There were large age differences for several abilities. Regression analysis showed that (a) these differences were dramatically attenuated by partialing speed and (b) a substantial proportion of age-related variance is shared in common with speed. The PMA vocabulary test showed an age-related increase in its correlation with answer sheet speed, suggesting an age-related performance bias due to slowing. Substantial speed/intelligence relationships require renewed attention to the role of information-processing speed in age changes on psychometric test performance.

External Link:

 

Berg, C., Hertzog, C., & Hunt, E. (1982). Age differences in the speed of mental rotation. Developmental Psychology, 18(1), 95-107.

ABSTRACT: 66 Ss in 4 age groups (mean ages 20.9, 32.4, 50.9, and 63.3 yrs) participated in a mental rotation task for 4 consecutive days. ANOVAs revealed significant age differences in the linear function relating median RT to degrees of rotation: Older Ss had higher intercepts and higher slopes. There were no significant age differences in error rates. Practice reduced slopes and intercepts for all groups, but it neither eliminated nor systematically reduced age differences in mental rotation performance. Mental rotation slopes and intercepts were significantly correlated with performance on the Figures subtest of the Primary Mental Abilities Test but not the Vocabulary subtest of the Nelson-Denny Reading Test. Results point toward age changes in the speed of spatial information processing that may contribute to age changes in performance on tests of spatial ability.

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