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Intelligence, Information Processing, & Aging Article List
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Papers:
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.
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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.
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Jopp, D., & Hertzog, C. (2009). Assessing Adult Leisure Activities: An Extension of a Self- Report Activity Questionnaire.
Unpublished manuscrpipt
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.
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Hertzog, C. (2008). Theoretical approaches to the study of
cognitive aging: An individual differnces perspective. In S. M. Hofer &
Alwin (Eds.),
Handbook of Cognitive Aging (pp 34-49). Thousand Oaks, CA:
Sage Publications
Abstract

Our understanding of aging and its
effects on cognition has improved considerably over the last 50 years,
as can be seen in a number of reviews (e.g., Craik & Salthouse, 200;
Hoyer & Verhaeghen 2006). This improvement has occurred despite the fact
that it is anything but easy to conduct research on cognitive
development.
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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.
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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.
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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.
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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).
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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.
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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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