Cognitive Development in Adulthood Research Paper

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The area of developmental research focusing on the study of cognitive changes in adulthood is often referred to as the field of cognitive aging. The orienting question for this field is, How does cognition change with aging? Three components of this question may be highlighted initially. First, the term cognition is used broadly and inclusively in this research paper to accommodate multiple aspects, dimensions, theories, and measures of a variety of mental activities executed by the brain. These include, but are not limited to, classes of activities known as intelligence, memory, attention, reasoning, problem solving, and wisdom. Second, the term change is used broadly and inclusively to accommodate several theories, phenomena, directions, and research designs. Thus, the present approach permits consideration of structural, stage-like, or incremental cognitive changes with aging, as investigated with any of numerous legitimate research designs. No assumptions are made about the nature of cognitive developmental change with aging. Third, the term aging is used broadly and inclusively to reflect processes occurring throughout adulthood. It is a neutral term tantamount to “changes with age that occur during adulthood” regardless of the direction or quality of the changes.

Cognitive aging (the field) is a particularly active and vibrant domain of research, one that is at the crossroads of both classic questions and novel trends. Several brief examples of each of the paths leading to this crossroads may be useful. First, classic questions about cognitive aging revolve around core developmental issues such as directionality (i.e., whether adult cognitive changes are gains, losses, or maintenance), universality (i.e., the extent to which there are individual differences in profiles of changes throughout adulthood), and reversibility (i.e., whether experience or intervention may promote recovery or improvement in functioning). For more than a century scholars have wondered about whether the lengthening adult life span would be ineluctably accompanied by diminishing cognitive resources (Dixon, Kramer, & Baltes, 1985). Moreover, because contemporary adulthood represents about 75% of the normal expected life span, few adults would fail to have a vested interest in the cognitive changes they might expect as they grow through their middle and into their later years. Second, novel trends reflect influences that are as easily incorporated into cognitive aging research as into any other developmental area. Recent trends include methodological advances, such as the means of analyzing structure, change, and variability (e.g., Hertzog & Dixon, 1996; Salthouse, 2000). Other novel trends in cognitive aging are often adapted from neighboring disciplines and given new clothing in the context of understanding long-term change. Among recent developments are such new topics as metamemory and memory self-efficacy (e.g., Cavanaugh, 1996, 2000), social cognition (Hess & Blanchard-Fields, 1999), practical cognition (e.g., Berg & Klaczynski, 1996; Park, 2000), collaborative cognition (e.g., Dixon, 1999), and brain and cognition (e.g., Raz, 2000; Woodruff-Pak, 1997). How cognition changes with aging is seen as a developmental question, and one that reflects classic developmental issues and relates to numerous neighboring developmental processes.

Issues considered in the study of cognitive aging go to the heart of our view of both the human life course, in general, and of individual aging adults, in particular. Personal expectations about aging are based in part on personal perceptions of cognitive skills—how adaptive they are and how they are believed to change during the adult years (e.g., Cavanaugh, 1996; Hertzog & Hultsch, 2000). Similarly, one of the prominent themes in societal stereotypes of aging is that of cognitive decline (e.g., Hummert, Garstka, Shaner, & Strahm, 1994). Notably, however, some stereotypes of aging include processes believed to improve or grow into and throughout late life (e.g., Heckhausen & Krueger, 1993). Some of these potential growth-like processes have substantial cognitive components (e.g., wisdom). Overall, whether cognitive aging should be characterized as consisting of gains or losses (or both) has been the topic of much debate for many decades (Baltes, 1987; Dixon, 2000; Uttal & Perlmutter, 1989).

Although it may be used in different ways and to accomplish different goals, cognition is no less important in late adulthood than in early adulthood. Not only is it a basis of one’s achievements and competence, but it contributes to—or detracts from—one’s sense of self-efficacy and the efficiency with which one engages in life planning and life management and pursues life goals. Therefore, it is instructive to compare the basic stories told about cognitive development during the first 20 or so years of life, on the one hand, and during the remaining 40 or 50 (or more) years of life, on the other. Obviously, the stories told of infant, child, adolescent, and even early adult cognitive development are generally optimistic. Cognition during these years is progressing and growing, and cognitive potential is being realized. For normally developing individuals there are some differences in level of performance attained and in the rate at which growth occurs, but virtually no differences in the direction of change. Cognition improves from early infancy.

Around early adulthood, however, the story of cognitive development evidently changes.The word “evidently” is used because there is some controversy about the range and causes of aging-related changes in cognition. There is, however, little remaining controversy regarding the fact that there is substantial and necessary cognitive decline (see, e.g., Craik & Salthouse, 2000). Nevertheless, an important theme in cognitive aging is one of individual differences in profiles, rates, and causes of change. Increasingly, researchers are attending to questions concerning such issues as whether people differ in when they start to decline, whether processes differ in rate of decline, what processes are maintained and for how long, how normal decline differs from that associated with various brain-related diseases (e.g., Alzheimer’s disease), and the extent to which this decline affects individuals’ everyday lives. Acommon proposal is that individual differences in cognitive development are greater in late life than in early life. Research in cognitive aging is ideally suited to investigating why such individual differences in change patterns occur.

In this research paper we summarize selected aspects of the field of cognitive aging. Reflecting the breadth of the field, we have elected to focus on several clusters or processes of cognitive functioning. Naturally, this results in numerous unattended  processes; interested readers may turn to several recent volumes of collected works in which scholars have reviewed a variety of processes of cognitive aging (e.g., Craik & Salthouse, 2000; Park & Schwartz, 2000). A long-standing area of study in cognitive aging is intelligence; we begin by reviewing scholarship in this area. Perhaps the most commonly researched domain in cognitive aging is memory. Accordingly, we review basic systems and results in this field and indicate several novel directions of research. More recently, numerous researchers have attended to issues of potential or resilience in cognitive aging. Included in this domain are such topics as plasticity and susceptibility to effects of experience, mechanisms of compensating for cognitive impairments, and such intriguing cognitive processes as wisdom and creativity.

Intelligence

Cognition can be viewed from several related perspectives. From one such perspective, the focus is on cognition as intelligence as an intellectual ability. There is a long tradition of research on intelligence and a surprisingly long history of research on intellectual aging. Research on the aging of intellectual abilities typically uses procedures adapted from research on psychometric intelligence. This means that intelligence is measured by one or more tests. These tests may be composed of more than one scale, or subtest. Each subtest measures a relatively unique aspect of intelligence. There are a variety of statistical means through which the uniqueness of the subtests can be evaluated. In addition, however, the subtests typically should be linked both conceptually and empirically.

Contemporary psychometric approaches to adult intellectual development employ multidimensional theories of intelligence. Therefore, they also use intelligence tests in which performance on multiple scales or dimensions may be tested. Using multiple scales of intelligence allows the investigator to examine the extent to which dimensions of intelligence change similarly or differently across adulthood. The psychometric approach to intellectual aging has a long and illustrious history.

Patterns of Intellectual Aging

A typical expectation about intellectual aging is that intelligence increases until early adulthood and then declines through late adulthood. This results in an inverted-U-shaped curve. Botwinick (1977) referred to this curve as a classic pattern, partly because it was so frequently supported in the literature. Interestingly, however, even the earliest theories and research did not lead to the unequivocal conclusion that intelligence inevitably and universally declined after early adulthood. Contemporary research has confirmed the prescient early theorists, who operated without the benefit of modern technology, contemporary theories, or even much research data. Several examples illustrate this point.

Issues of age fairness and late life potential and plasticity were identified early. Kirkpatrick (1903) noted that age-fair intelligence tests were crucial to identifying patterns of intellectual aging. Almost a century ago he also speculated that adults could be trained to perform better on intelligence tests; recently, several researchers (e.g., Schaie, 1996) reported that this was indeed possible. Another important issue raised almost 100 years ago is the potentially close connection between the aging body and the aging mind. For example, Sanford (1902) noted that intellectual decline was likely associated with the inevitable physical decline that accompanies late life. Thus, Sanford anticipated some aspects of contemporary theories focusing on the roles of physiological, neurological, and sensory factors (e.g., Baltes & Lindenberger, 1997). Could older adults overcome such inevitable changes? Sanford speculated that some maintenance of performance levels is possible if aging adults made an effort to maintain them by, for example, continuing challenging activities. This idea, too, has recently been the target of considerable research (e.g., Gold et al., 1995; Hultsch, Hertzog, Small, & Dixon, 1999). Still in the first half of the century, Weisenburg, Roe, and McBride (1936) attended to the questions of whether all adults developed in the same pattern and whether all intellectual abilities changed in the same way. They reported a wide range of ages in adulthood at which performance on intelligence tests peaked. This implies that individuals may differ in peak age, rate of growth and decline, overall degree of decline, and perhaps even final performance level. If some individuals decline relatively early in adulthood, and if their decline is sharply downward, others may decline relatively late and quite gradually, and perhaps not even noticeably. This prediction, too, proved to be uncannily accurate.

One final similarity between early and recent research on intellectual development may be noted: The study of intellectual aging has long been viewed as a research topic with important and immediate practical implications. That is, how well society understands the characteristics of intellectual aging may have a direct impact on the welfare of individuals and of the society. For example, in the early 1920s, R. M. Yerkes set out to enhance the recruitment and training of excellent military officers. Shortly after World War I it was clear that each side in a war would want people in charge who were intellectually competent, if not intellectually superior. How would the best people be selected and promoted to sensitive and influential positions? How could the best officers be identified and retained? Were older officers less competent than younger officers? Yerkes found that older officers performed worse on an intelligence test than did younger adults. Nevertheless, he argued that many older officers had accumulated valuable experience and had command of specific relevant domains of knowledge. It could take years for younger officers to acquire similar levels of knowledge. Yerkes believed that this actually put older adults at an advantage in the intellectually demanding role of planning and executing war. Thus, even when a great deal is at stake, some observers opted for (older) adults possessing age-related experience and a seasoned mind over (younger) adults who might be able to learn novel information more quickly.

In sum, many early researchers identified remarkably contemporary concerns in the study of intelligence and aging. Moreover, several early leaders commented on the implications of intellectual development for continued cognitive potential throughout life.

Crystallized and Fluid Intelligence

Beginning in the 1960s John Horn and Raymond Cattell began developing an alternative view of the classic aging pattern. Horn and Cattell collected a variety of intelligence-test data from adults of varying ages. Rather than interpreting the scores from each of the tests, or even collapsing across categories of tests (such as Verbal and Performance), Horn and Cattell conducted complicated statistical analyses. In these analyses they sought to assess empirically whether there was indeed more than one category (or factor) of intelligence. If so, this would support the notion that intelligence in adulthood was multidimensional. Empirical support for this fact would then allow Horn and Cattell to investigate three major issues. First, how many and what were the dimensions of intelligence? Second, what were the age-related patterns of performance on these dimensions? Third, to what explanatory processes could these empirically derived dimensions be linked?

In their research, Horn and Cattell (1966; Horn, 1982) identified two major dimensions of intelligence. These dimensions of intellectual abilities were called fluid intelligence (Gf) and crystallized intelligence (Gc). Fluid intelligence reflected the level of intellectual competence associated with casual learning processes. This learning is assessed by performance on novel, usually nonverbal tests. Crystallized intelligence, on the other hand, reflects intellectual competence associated with intentional learning processes. This variety of learning is assessed by measures of knowledge and skills acquired during school and other cultural learning experiences. Most verbal tests tap processes thought to underlie crystallized intelligence.

How is this perspective an alternative to the classic aging pattern? Because crystallized intelligence indexes life-long accumulation of cultural knowledge, it should show a pattern of maintenance or increase during the adult years. According to the theory, fluid intelligence is more dependent on physiological functioning, including the neurological system. The physiological and neurological base declines with advancing age (e.g., Medina, 1996; Raz, 2000). If this neurological base is impaired, the ability to perform associated intellectual skills is undermined. Horn and Cattell have therefore provided the classic aging pattern with two contributions. First, they provided a firmer empirical basis for the common verbal-performance distinction. Roughly speaking, crystallized intelligence corresponds to verbal intelligence scales, and fluid intelligence corresponds to performance intelligence scales. Second, they have provided potential explanations for the common observation of differential decline across the two dimensions.

Seattle Longitudinal Study

Longitudinal research in intellectual aging has been carried out in a number of locations (Schaie, 1983).Although longitudinal investigations have the advantage of examining age changes rather than simply age differences, they have their associated limitations as well (see Hultsch, Hertzog, Dixon, & Small, 1998; Schaie, 1983). For example, selective sampling and selective attrition factors plague longitudinal designs but are now manageable with contemporary design features and statisticaltechniques(e.g.,Hultschetal.,1998;Schaie,1996). Individuals who volunteer to participate in longitudinal studies are committing considerable time and effort over a period of many years. The sample of people who would volunteer for such a long-term commitment are generally positively selected on anumber of dimensions that may be relevant to intellectual performance. As well, those who continue in such studies are also positively selected. Indeed, these participants often perform initially on the intelligence tests at a higher level than those who drop out. In this way, a volunteer longitudinal sample is somewhat selective at the outset, and the continuers are more positively selected than the dropouts. Because of this bias, simple longitudinal designs may underestimate the extent of age-related declines.

In 1956 K. Warner Schaie began a carefully designed and exhaustive longitudinal and cohort-sequential study of intelligence in adulthood. Schaie administered the Primary Mental Abilities (PMA) test and additional measures related to intelligence. His initial sample was approximately 500 adults living in the community. This sample was carefully constructed to be representative, and participants ranged in age from 20 to 70 years. Testing was done at seven-year intervals beginning in 1956. At each occasion new participants were added and then followed in subsequent occasions. Thus, there was a sequence of longitudinal studies. Because of the location of all the testing, Schaie’s study has become known as the Seattle Longitudinal Study (Schaie, 1996).

Schaie applied special techniques for comparing longitudinal samples to new cross-sectional samples. In doing so, he was able to estimate that until the age of 50 a substantial portion of the age differences observed in cross-sectional studies were not due exclusively to aging-related decline. Instead, much of the observed age differences in cross-sectional studies were due to cohort effects. That is, observed age differences may be related to cultural and historical changes. Indeed, Schaie (1990) reported such a phenomenon when he noted that historical analyses indicate that successive generations have performed at higher levels on intelligence tests. Notably, the patterns suggest that the historical increases may be greater for older than for younger cohorts. If so, future studies may find reduced age differences between younger and older participants. Such a trend can only provide more pressure to utilize the productive potential of older adults.

Throughout his career Schaie (1994, 1996) has emphasized that there are considerable individual differences in degree of decline and age at onset of decline. Indeed, up to age 70 some individuals do not decline at all. Some of these individuals even show modest gains for all of the intellectual abilities that he evaluates. Nevertheless, a prominent conclusion is that the age at which each ability peaks and the patterns of decline thereafter are quite different. For example, those abilities associated with fluid intelligence have earlier peaks and longer declines than those abilities associated with crystallized intelligence. He also pointed out that the patterns vary for women and men. For example, one finding was that women generally decline earlier on fluid intelligence, whereas men generally decline earlier on crystallized intelligence. There is diversity not only in how dimensions of intelligence develop, but also in how men and women develop in different dimensions. Because of this diversity, Schaie (1994, 1996) underscored the warning that an overall index of ability such as the IQ score should not be used in research on intellectual development in adulthood.

Schaie also examined issues of intervention or application. As the Seattle Longitudinal Study progressed, he realized that he could address a unique question with profound implications for both theory and application. The issue is the age at which substantial cognitive decline actually begins. Whether substantial decline begins earlier or later in life could have a profound influence on social policy problems such as mandatory retirement (e.g., Perlmutter, 1990; Schaie, 1994). Schaie’s studies suggested that such decline is not observed on average for all dimensions of intelligence until about the late 60s (Schaie, 1996). These results may be surprising to even the most optimistic theorist and practitioner, for they imply that the overall profile of intellectual aging is one of maintenance. In fact, in one analysis Schaie (1990) reported that over 70% of 60-year-olds and over 50% of 81-year-olds declined on only one ability over the previous seven years. Thus, intellectual declines occur with aging, but not appreciably until quite late in life, and then not uniformly across dimensions of intelligence.

Schaie discovered some tentative answers to frequently asked questions about risk and protection factors. Everyone would like to know what they can do to increase the probability that their cognitive aging will by characterized by maintenance and growth and to minimize the probability that it will instead be characterized by decline and decay. By analyzing the differences among individuals in decline versus growth patterns, Schaie (1996) cited several factors that may lead to reducing the risk of cognitive decline in late life. These protective factors include (a) avoiding chronic illnesses, especially cardiovascular disease, or lifestyles that lead to these diseases; (b) pursuing high levels of education and having professions that involve high complexity and higher-thanaverageincomes;(c)continuingtobeactiveinreading,travel, culture, and further education; (d) being married to a spouse withhighandsimilarcognitiveskills;and(e)feelinggenerally satisfiedwithlife(Schaie,1996).Ofcourse,thesefactorswere not linked causally or directly to maintenance of intellectual functioning, so the above list should not be interpreted too literally. Therefore, it is not yet a list of dos and don’ts for maintaining high levels of cognitive performance into late adulthood. Nevertheless, such hypotheses highlight the close link between research on cognitive aging and questions of application to real life. Overall, it can safely be said that the previous factors cannot hurt one’s chances of maintaining intellectual functioning; in fact, they may help.

Memory

If research on intellectual aging is characterized principally by psychometric assumptions and procedures, research on memory and aging is typically conducted by implementing one or more of a wide range of experimental tasks and techniques in the service of answering a broad range of specific questions. To be sure, all prominent developmental research designs— that is, those that compare age groups (cross-sectionally) or those that follow samples across time (longitudinally)—may be enacted for either psychometric or experimental research. In the case of memory, the bulk of extant research has been cross-sectional and experimental in nature, but there are a growing number of examples of change-oriented, longitudinal studies populating the scholarly literature. Thus, at the most general level the motivating issues of memory and aging research are similar to those propelling scholarship in intelligence and aging. These include (a) whether aging-related changes may be characterized as gains, losses, or both and (b) what accounts for differences in performance as observed across time, age, task, and individuals.

Overall, research on memory and aging is focused on processes through which individuals may recall previously experienced events or information, the extent to which these processes change with advancing age, and the conditions, correlates, or predictors of such changes. Reflecting the sheer volume of research in this field, numerous reviews of memory and aging have been published in recent decades (e.g., Bäckman, Small, Wahlin, & Larsson, 2000; Craik, 2000; Craik & Jennings, 1992; Hultsch & Dixon, 1990; Kausler, 1994; Light, 1992;A. D. Smith & Earles, 1996). Of all aspects of cognitive aging, memory may be the one that has most captivated general human interest and academic attention. Nearly all reviewers begin by noting that (a) memory is viewed as a functional, if not essential, tool of successful development; (b) memory is one of the most frequently mentioned complaints of older adults; (c) memory loss is one of the most feared signs and implications of aging; and (d) many adults believe that, whereas memory abilities improve through childhood, they decline with aging. For these and other reasons, researchers and lay adults are profoundly interested in whether and when their and others’ memory abilities change (decline) throughout adulthood (Dixon, 2000).

Systems of Memory

Over the last several decades, research on memory and aging reveals provocative patterns of results. Whereas some tasks are associated with robust findings of age-related deficits, other tasks are associated with less pronounced losses or even equivalent performance by younger and older adults. Tasks typically associated with losses include remembering lists of information, expository texts, picture characteristics, spatial locations, and those that tap the limits of online memory processing. Tasks often associated with relatively unimpaired performance include implicit memory, facts and knowledge, and those that reflect familiar situations with substantial environmental or human support. Although others are available, one well-developed theoretical treatment of memory per se has proven helpful in organizing these disparate results. Specifically, the memory systems perspective has been especially influential in research on memory and aging (Bäckman et al., 1999; Craik, 2000; Dixon, 2000; Schacter & Tulving, 1994).

Positing that there are up to five systems of memory, a central goal of this perspective is to explicate the organization of the systems. A memory system is defined as a set of related processes, linked by common brain mechanisms, information processes, and operational principles (Schacter & Tulving, 1994). We define four of the systems briefly and summarize some principal findings with respect to aging. We begin with the two most commonly encountered forms of memory, those to which most people refer when they express their beliefs and fears about the effects of aging on memory functioning (Ryan, 1992).

Episodic Memory

This form refers to memory for personally experienced events or information. Everyday examples are bountiful: trying to remember the names of people one has met at a party, where one parked the car, a conversation or joke one heard, the locationofanobjectinaspatialarrangement,ananecdoteoneread in a newspaper, or an unwritten list of items to purchase at a store. It is thought to be the latest developing memory system, and some reviewers have suggested that it is correspondingly among the first to begin showing signs of aging-related decline. Indeed, cross-sectional research using a variety of episodic memory tasks (e.g., memory for digits, words, texts, pictures, objects, faces) and procedures (e.g., free recall, cued recall, recognition) has observed that older adults commonly perform worse than younger adults. Much recent research has targeted potential moderating factors, such as health, lifestyle activities, education, environmental support, collaborative condition, and ecological relevance of the task (e.g., Bäckman et al., 2000; Hultsch et al., 1998). Although no evidence has been marshaled to dispute persuasively the conclusion that episodic memory performance generally declines with advancing age, some cross-sectional (e.g., Nilsson et al., 1997) and longitudinal (Dixon, Wahlin, Maitland, Hertzog, & Bäckman, in press) research has indicated that the magnitude of aging-related change may be more gradual than precipitous for normally aging adults, at least until the mid-70s (Bäckman et al., 2000).

Semantic Memory

This system of memory is expressed through the acquisition and retention of generic facts, knowledge, and beliefs. In research, it is evaluated by administering tests of general world knowledge, facts, words, concepts, and associations.As such, it is similar to the domain represented by crystallized intelligence. The typical finding for semantic memory is that older adults may remember as much information of this sort as do younger adults. For example, normal older adults, through extended cultural and educational experiences, may possess knowledge bases regarding world facts (sports, celebrities, geographical information, political lore) that are superior to those of younger adults. A typical finding in cognitive aging literature is that the vocabulary performance of older adults is similar to or better than that of younger adults. Thus, older adults display similar knowledge structures or associative networks. Nevertheless, some studies have suggested that older adults may access such information more slowly and with more frequent blockages than do younger adults. In a large cross-sectional study, only small differences were observed across the ages of 35 to 80 years (Bäckman & Nilsson, 1996). Moreover, a recent longitudinal study observed modest changes over a 12-year period for adults originally aged 55 to 85 years (Hazlitt, 2000).

Procedural Memory

This form of memory is reflected in the gradual learning (through practice) of a wide variety of cognitive and behavioral skills. Naturally, as one learns a skill, one may acquire information or actions intentionally, deliberately, explicitly, and with awareness. However, other phases and aspects of learning the skill may be accomplished more automatically, implicitly, and without specific awareness. This latter aspect of memory is the one reflected in this system. It is involved in the identification of words, objects, or movements that have been experienced by an individual but about which that individual may have little direct awareness—little episodic memory of having previously encountered the word or object. Memory thus used has been said to be automatic or implicit, as contrasted with intentional or explicit (Howard, 1996). A common expectation is that procedural memory, as evaluated through priming techniques (e.g.,Howard, 1996), is relatively unaffected by aging, as long as the involvement of explicit memory is minimized (Craik, 2000; Craik & Jennings, 1992). Although this seems to indicate a beneficial aspect of memory functioning in late life, it may lead unintentionally to a greater propensity to generate and remember false information (see Schacter, Koutsaal, & Norman, 1997).

Primary Memory

Although differing in some respects, this system is also known popularly as working memory and, in some restricted instances, as short-term memory. The terms are selected to convey the fact that some expressions of memory are brief, temporary, not yet (or ever) stored, or still in consciousness. Distinguishing between primary and working memory has proven useful for aging research (Craik, 2000). Specifically, primary memory is observed in conditions in which individuals must repeat minimal information presented immediately prior to the task. For example, primary memory is tapped when an individual must repeat a short list of letters or digits immediately after it is read. For such brief and passive tasks, older adults perform as well as younger adults, or at least not as poorly as in tasks requiring further manipulation of more complex information over a longer duration. Performing working memory tasks requires more active processing and manipulation of incoming information. As such, older adults are typically at a disadvantage as compared to younger adults in performing such tasks. As Craik (2000) noted, this divergent pattern within a memory system implies that aging processes do not adversely affect some everyday memory demands (e.g., copying addresses and numbers as they are read), but it does negatively affect more active aspects of online memory processing.

Emerging Memory Topics

As can be inferred from the preceding summary, memory, like intelligence, is a multidimensional construct. As with other multidimensional constructs of interest in developmental psychology, differentiable dimensions may reveal distinct developmental patterns. Researchers continue to explore with increasing ingenuity each of the clusters of memory phenomena. In addition, many researchers push the boundaries of these memory systems as they apply to aging by considering ever-broader ranges of memory phenomena, as well as correlates and predictors. In this section we briefly note a few trends in memory and aging research, selecting for somewhat more discussion two of these domains.

Biological to the Social

Among the promising new trends in memory and aging research is the ever-increasing attention that biological influences are receiving. This is an entirely logical development, if only because the brain is a crucial site of activation that is representative of memory and other cognitive processing. Structural and functional changes in the brain are related to, if not predictive of, cognitive performance in adults (e.g., Cabeza & Nyberg, 2000; Raz, 2000; Reuter-Lorenz, 2000). Also within a biological level, much current research in memory and aging has focused on the extent to which physiological, sensory, and physical health changes may have an effect on cognitive functioning in late life (e.g., Baltes & Lindenberger, 1997; Waldstein, 2000).

Shifting to a cognitive level of analysis, recent efforts have been made to identify other cognitive factors that influence target cognitive functions. For example, working memory has been identified as a relevant influence on episodic and semantic memory functioning (e.g., Hultsch et al., 1998). Theoretical constructs such as processing resources, inhibitory control, and information-processing speed have, in empirical applications, accounted for age-related variance in memory performance (see Craik, 2000; Salthouse, 1991). At still another level of analysis, recent progress in examining the role of background characteristics such as gender, education, and lifestyle activities on cognitive aging have been made (e.g., Herlitz, Nilsson, & Bäckman, 1997; Hultsch et al., 1999). Finally, social and cultural aspects of memory and aging have been explored with much promise (e.g., Hess & BlanchardFields, 1999; Park, Nisbett, & Hedden, 1999). In sum, the goal of understanding memory changes with aging suggests a complex web of changing relationships—among systems of memory, other cognitive influences, and correlates ranging from the neurological to the social-cultural.

Metamemory

Adults of all ages often wonder about their memory—how it works or does not work, why one remembers some things but notothers,andwhethermemoryskillswillchangeoverthelife course. The term metamemory refers to such cognitions about memory—thinking about how, why, and whether memory works.Specific aspects of metamemory include knowledge of memory functioning, insight into memory changes or impairment, awareness of current memory processes, beliefs about and interpretations of memory skills and demands, and even memory-related affect. This research paper features an overview of the concept of metamemory and how it applies to aging. The view of metamemory presented here is useful when considering both basic (e.g., how memory and metamemory change and relate to one another in aging) and applied (e.g., the role metamemory may play in compensating for memory impairments and decline) research questions.

Overall, research and theory in metamemory in adulthood incorporate many of the issues raised in the neighboring domains of metamemory research. It does so in part through implementation of an inclusive and multidimensional concept of metamemory (e.g., Dixon, 1989; Hertzog & Hultsch, 2000). Four principal characteristics of this are that (a) it includes a wide variety of behaviors (knowledge, beliefs, evaluations, and estimates), indicating the level, degree, or extent of an individual’s metamemory performance or skill; (b) it features a multidimensional concept, in that the multiple facets or behaviors are viewed as separable but linked dimensions of a coherent construct of metamemory; (c) it assumes that multiple operations and dimensions would converge on a higher order construct of metamemory and that metamemory can be discriminated from related constructs; and (d) metamemory is a construct of intrinsic interest in the study of normal cognitive aging, but one that may also have substantial implications for understanding impairments of memory in late life.

Metamemory represents one’s knowledge, awareness, and beliefs about the functioning, development, and capacities of one’s own memory and of human memory in general (Dixon, 1989). As such, metamemory includes three principal categories (Hertzog & Dixon, 1994). First, declarative knowledge about how memory functions includes knowledge of how the characteristics of memory tasks have an impact on memory performance, whether strategies are required, and which strategies may be usefully applied to particular situations. Second, self-referent beliefs about one’s capability to use memory effectively in memory-demanding situations define memory self-efficacy and controllability (e.g., Cavanaugh, 1996, 2000). One’s beliefs about one’s ability to remember may determine (a) the extent to which one places oneself in memory-demanding situations, (b) the degree of effort one applies to perform the memory task, (c) one’s expectation regarding level of memory performance, and (d) one’s actual memory performance. Certain aspects of affect regarding memory (in general) or one’s memory performance and change (in particular) may also play a role (e.g., motivation to do well, fear of memory-demanding situations).

Third, awareness of the current, general, and expected state of one’s memory performance includes processes of memory insight and memory monitoring. Effective rememberers are able to monitor actively and accurately their performance vis-à-vis the demands of the memory task. A high degree of accuracy in predictions of performance, evaluations of encoding demands, and on-line judgments of learning may indicate an effective and accomplished rememberer (e.g., Hertzog & Hultsch, 2000; Moulin, Perfect, & Jones, 2000). In clinical situations, an awareness of a deficit may be an important precursor to memory compensation (e.g., Dixon & Bäckman, 1995, 1999; Wilson & Watson, 1996).

In aging research, these categories of metamemory have been related to one another theoretically and empirically (see Hertzog & Dixon, 1994; Hertzog & Hultsch, 2000). In principle, for older adults, high performance on given memory tasks should be promoted by the following metamemory profile: (a) a well-structured declarative knowledge base about how memory functions in given tasks, (b) refined knowledge of one’s own memory skills, (c) accurate and high memory self-efficacy, and (d) skill at the monitoring and control activities during acquisition, retention, and retrieval. In addition, it could be useful to have (e) stable or low memory-related affect, such that the potential deleterious effects of memoryrelated anxiety or depression could be avoided. In contrast, some older adults with poorer—and perhaps impaired— performance could be experiencing some components of the following profile: (a) and (b) an ill-structured, incomplete, or erroneous knowledge base pertaining to general memory functioning or one’s own memory skills; (c) inaccurate or low memory self-efficacy; (d) an inability to monitor and control the requisite activities of effective remembering; and (e) fluctuant, uncontrolled, or excessive memory-related anxiety or depression. These profiles define two hypothetical ends of a continuum.

Two practical implications of these hypothetical profiles in older adults are evident. First, some aging-related memory disorders or impairments may be remedied through clinical intervention designed to assess and improve selected categories of metamemory. Second, the diagnosis and remediationofsomeorganicmemorydisorders(e.g.,theresultof injuries or disease) may be enhanced through the use of metamemory or awareness information. Research on these provocative issues is advancing on a variety of fronts, including cognitive neurorehabilitation (e.g., Prigatano, 2000; Wilson & Watson, 1996), memory compensation in late life (e.g., Dixon, de Frias, & Bäckman, 2001), awareness and insight neuropsychological conditions (e.g., Lovelace, 1990; Markova & Berrios, 2000; Schacter, 1990), memory complaints and their origins and implications (e.g., Gilewski & Zelinski, 1986; Grut et al., 1993; G. E. Smith, Petersen, Ivnik, Malec, & Tangalos, 1996), and potential effects of metamemory training on memory (e.g., Lachman, Weaver, Bandura, Elliott, & Lewkowicz, 1992; Verhaeghen, Marcoen, & Goosens, 1992).

Memory in Interactive Situations

For several decades researchers in a surprising variety of fields have addressed aspects of everyday memory activity that appear to operate in the influential context of other individuals. Many observers have noted the frequency with which everyday adult cognitive activity occurs in interactive contexts (e.g., Clancey, 1997; Greeno, 1998). Acollaborative context frequently envelops cognitive performance in modern life. Everyday examples of collaborative cognition include (a) family groups or lineages reconstructing stories from their shared past; (b) spouses enlisted to help remember important appointments, duties, or dates; and (c) strangers in unknown cities consulted in order to solve way-finding or map-reading problems (Dixon, 1999; see also Strough & Margrett, 2002). Lurking behind this observation is the contention that collaboration may lead to functional performance outcomes, practical solutions, and improved performance. Of particular importance in cognitive aging research is the possibility that the strategic deployment or use of human cognitive aids (other individuals) may be a means of compensating for individual-level aging-related losses or deficits.

In other literatures the phenomenon has been also called collective (e.g., Middleton & Edwards, 1990), situated (e.g., Greeno, 1998), group (e.g., Clark & Stephenson, 1989), socially shared (e.g., Resnick, Levine, & Teasley, 1991), or interactive (e.g., Baltes & Staudinger, 1996) cognition. In the case of collaborative memory, an assumption is made that two or more individuals attend to the same set of learning or memory tasks and are working cooperatively (although not necessarily effectively) to achieve a recall-related goal. Notably, the members of the collaborating group can be variously passive listeners, conversational interactants, productive collaborators, seasoned tutors, counterproductive or even disruptive influences, or optimally effective partners. Therefore, according to a neutral definition of collaborative memory espoused in this research paper, no a priori assumptions are made about the effectiveness or logical priority of the memoryrelated interaction. It has long been clear that group processes can vary in their effectiveness and thus that group products can vary in their accuracy and completeness (e.g., Steiner, 1972).

The issue of the extent to which collaborative memory is effective has been evaluated from numerous perspectives for several decades. Indeed, much research has focused on this contentious issue (e.g., Dixon, 1999; Hill, 1982), and several key factors appear to play roles in the observations and inferences. These factors include (a) whether the participants are collaborative-interactive experts (e.g., friends or couples), (b) the type of outcome measure observed (i.e., a simple product such as total items recalled or a variety of recall-related products such as elaborations and inferences), (c) the extent to which the actual processes (e.g., strategic negotiations) and byproducts (e.g., affect and sharing) of the collaborative communication are investigated, and (d) the comparison or baseline by which the effectiveness of collaborative performance is evaluated. In general, little extra benefit is observed under conditions in which researchers reduce the dimensionality of the tasks, the familiarity of the interactants, the variety of the memory-related products measured, and the richness of the collaborative communication (e.g., Meudell, Hitch, & Kirby, 1992). In contrast, evidence for notable collaborative benefit may be observed when researchers attend to collaborative expertise, multidimensional outcomes, measurement of actual collaborative processes, and comparisons accommodated to memory-impaired or vulnerable groups (e.g., Dixon & Gould, 1998). In particular, evidence has accumulated that expert older collaborators (long-term married couples) may be able to solve complicated memory problems at levels not otherwise expected for such individuals through cooperative mechanisms that resemble compensatory devices (Dixon, 1999, for review). This is a growing and promising area of both basic and applied research in memory and aging.

Memory for Future Events

The classical sense of memory—and all the examples just noted—refer to remembering events that have occurred in the past. There is, however, a common class of memory activities that refer to future events. Among the plethora of everyday memory experiences are those in which one must remember to carry out an action in the future, such as remembering to take medication, keep an appointment, give a message to a colleague, pick up a loaf of bread on the return trip home, or perform an errand such as mailing a letter. This class of memory has become known as prospective memory. Accordingly, it is contrasted with the sizable set of memory activities for past events, which, from this perspective, may be classified as retrospective memory. Thus, retrospective memory includes the principal memory systems, such as episodic and semantic memory. Although memory and aging research has been predominantly interested in retrospective memory phenomena, in recent years prospective memory has become a salient research topic (Einstein, McDaniel, Richardson, & Guynn, 1995).

Like retrospective memory, prospective memory and aging have been studied with both naturalistic and experimental procedures. The two classes of memory share also a considerable amount of research examining age-related patterns of performance. In a groundbreaking naturalistic study, Moscovitch (1982) instructed younger and older adults to call an experimenter at prearranged times throughout a period of several days. The intriguing results indicated that older adults’ prospective memory performance was actually better than that of the younger adults. Further investigation revealed an unexpected potential explanation; namely, older adults were motivated to perform such tasks and were more likely to use reminders (e.g., written notes) as a way of remembering the intention of phoning the experimenter. Thus, this early study suggested the possibility that older adults may have identified a potential everyday memory deficit as well as an effective compensatory mechanism (see also Dixon, de Frias, et al., 2001).

To investigate such issues further, experimental researchers developed procedures for controlling the strategies that participants might use (e.g., Einstein & McDaniel, 1990). Such laboratory experiments have revealed divergent findings. For example, Dobbs and Rule (1987) asked younger and older adults at the beginning of an experiment to remind the experimenter to give them a red pen at a particular later point in the session. Thus, participants had to monitor this intention over a period of time, without the benefit of external memory aids, while performing other demanding or primary tasks. In this study older adults performed significantly worse than did their younger counterparts.

Einstein et al. (1995) proposed a subdivision of prospective memory tasks. From this analysis, one subset of prospective memory tasks is event-based, as represented in those situations in which an external event acts as a trigger for some previously encoded intention. Theoretically, the occurrence of the event prompts a memory search that will eventually result in the retrieval of the intention. For example, an event could be the sudden meeting of a friend that triggers the memory that one has a message to deliver. In contrast, timebased prospective memory reflects the situation in which the appropriateness of an action or intention is determined by the passage of time. Accordingly, one must remember to take a pill in two hours; in order to do this with no external event, one must monitor time while performing other (distracting) actions. The provocative hypothesis was that time-based tasks would produce more negative aging-related effects than would event-based tasks because the former require more self-initiated processing (Einstein et al., 1995). The key to older adults’successful performance may be the ability to implement compensatory procedures such as strategic use of environmental cues. Although this idea remains controversial (e.g., Park, Hertzog, Kidder, & Morrell, 1997), the ideas of decomposing this class of memory actions and relating performances to other factors is advancing our understanding of how aging might affect memory for future events.

Cognitive Potential in Adulthood

Taken together, the bodies of research on intellectual and memory aging reveal that despite robust evidence of gradual decline in performance, there may be some room for slightly optimistic interpretations. To be sure, among the multidimensional constructs and processes considered to be the mechanics of cognitive aging (Park, 2000), intelligence and memory may offer the greatest opportunity to observe even this extent of mixed aging-related patterns. Recent reviews of other more basic processes (e.g., attention, perception) and those more closely linked to biological aging (e.g., those heavily involving sensory, physiological, and neurological functioning) evaluate almost exclusively the magnitude and rate of decline, as well as the extent to which such changes affect other cognitive performances, with little space devoted to maintenance or growth (see Dixon, Bäckman, & Nilsson, in press). Nevertheless, the overall balance between the gains and losses of cognitive aging continues to be an issue of vigorous and compelling debate (e.g., Baltes, 1987; Dixon, 2000; Park, 2000; Salthouse, 1991; Schaie, 1996; Uttal & Perlmutter, 1989). Why is this the case? Perhaps the most compelling reason has been identified by Salthouse (1990), who noted that one of the most vexatious challenges facing cognitive aging researchers is to reconcile what we have learned about cognitive decline from laboratory and psychometric research with the common observation that many older adults are quite competent in cognitively demanding everyday leisure and professional activities into very late life. How can older adults—all of whom will have experienced at least detectable decline in a variety of fundamental cognitive processes—still perform well as world political leaders, CEOs of large corporations, scientists, novelists and poets, expert bridge and chess players, composers and painters, and a variety of other roles? In brief, there must be some aspects or processes of cognitive aging that are not definitively represented or determined by commonly researched domains. In this section we review briefly some of the possible scenarios for observing or optimizing cognitive potential in adulthood, midlife, and beyond.

Concept of Cognitive Gains

With most empirically investigated psychological processes, aging-related changes may follow multiple directions. This is the case, despite the fact that many biologically based processes are in decline for much of middle and late adulthood. In fact, Baltes (1987, p. 613) referred to this idea as one of the principal theoretical propositions of life-span developmental psychology: “Considerable diversity . . . is found in the directionality of changes that constitute ontogenesis, even within the same domain . . . [and] during the same developmental periods.” An important implication of this is that the concept of psychological development contains both gains (growth, increases) and losses (decline, decrements). From this perspective, life-span psychological development is not simply or exclusively characterized by incremental growth or structural advances. Instead, development is a concept that contains multiple possible directions—as widely varied as these directions can be (i.e., that between gains and losses). Moreover, as Baltes noted, multiple directions of change can occur within a single multidimensional construct.

Memory is an excellent example. Recall that multiple systems have been posited and that these systems may undergo somewhat different developmental changes with aging (Craik, 2000; Craik & Jennings, 1992). This example is of multiple directions of change across dimensions of a multidimensional construct (e.g., intelligence, personality, memory). It may, as Baltes noted, also apply within a single dimension but across individuals in a single developmental period. That is, a diverse group of adults in their 60s may be at different points, following different trajectories, in the developmental paths of any single psychological process.

Thus, gains and losses have become a key organizing feature of psychological aging (Baltes, 1987; Dixon, 2000). Among the principal challenges for psychologists is not only to describe the cognitive losses that occur with aging and to articulate the mechanisms accounting for those losses. A great deal of evidence pertains to both these descriptive and explanatory undertakings (e.g., Park, 2000). Instead, an important challenge is to articulate classes of examples of gains with psychological aging. In what manner and by what means may there be improvement in psychological functioning with advancing age? Accordingly, several such classes of examples have been identified (e.g., Dixon, 2000).

Specifically, one model proposes that given substantial and unavoidable losses in basic biological and cognitive functioning with aging (Park, 2000), three main categories of gains may still be articulated. These are (a) gains qua gains, or the possibility that some gains may emerge and continue independent of the constraints provided by surrounding aging-related losses; (b) gains as losses of a lesser magnitude, or the idea that some consolation or adjustment may be made given that some psychological losses occur later than expected (personally or in stereotypes) or to an extent not as devastating as had been feared; and (c) gains as a function of losses, or the evident possibility that some psychological gains are linked to specific losses, occasioned by those losses, and that may even compensate partially for such losses, mitigating their detrimental effects (see Dixon, 2000). Interestingly, the latter category includes many examples that operate principally at a basic or neurological level of analysis. In sum, at many levels cognitive aging appears to be multidirectional; this is the case even though much overall loss (decline) occurs with aging.

Plasticity and Experience

Under what circumstances can older adults experience gains in cognitive performance? Whereas early twentieth century researchers only speculated about this matter, recent researchers have produced useful empirical information. Some evidence regarding potential is revealed in intervention research, such as training older adults to perform better on challenging cognitive tasks. For example, this literature supports four principal theses. First, many normal older adults can improve their performance on intelligence tests simply by having the opportunity for some self-directed practice (e.g., Baltes & Willis, 1982). Second, healthy older adults can benefit from specific training on how to perform cognitive tasks (e.g., Verhaeghen, Marcoen, & Goosens, 1992). Third, selected older adults who have experienced severe or pathological decline can benefit from specific and aggressive interventions (e.g., Camp & McKitrick, 1992). Fourth, there may be some conditions in which training higher levels of performance on intelligence tests can lead to better performance in some cognitive tasks of everyday life (e.g., Neely & Bäckman, 1995; Willis, Jay, Diehl, & Marsiske, 1992).

Overall, some interventions work to improve performance or even reverse losses associated with aging. Theoretically, this implies that some degree of normally observed decline in intellectual aging may be due to disuse. Older adults decline partly because they no longer have the experience or the social and cultural context that will help them maintain some intellectual abilities. Recall that several very early observers had produced prescient speculations remarkably consistent with this empirical generalization. The implication is not, however, that there is no real decline, or that simply providing mental exercises or social support will overcome observed decline. Intellectual decline is real, but there is some degree of plasticity available to many older adults. This conclusion supports the contention that the potential for improvement may be present into late life.

The “potential for potential” in late life is of interest not only to theorists and researchers interested in cognitive aging. It is of interest—or should be of interest—also to politicians, policy makers, aging workers, and just about everyone who knows someone who is nearing the retirement years or who plans to reach old age themselves. Why should so many people be interested in the fact that aging individuals retain the potential for cognitive maintenance and growth? One reason is that our population is increasingly an aging one. More people are getting older; more people are reaching retirement age and beyond; and more people may be feeling that they are being closed off from making useful contributions at an age in which they feel quite competent and potentially useful. Many recent books have addressed precisely this issue and its many implications, as the titles of several of them indicate: Late Life Potential (Perlmutter, 1990), Successful Aging (Baltes & Baltes, 1990), Promoting Successful and Productive Aging (Bond, Cutler, & Grams, 1995), and Compensating for Psychological Deficits and Declines: Managing Losses and Promoting Gains (Dixon & Bäckman, 1995). These and similar recent contributions explore the possibility that there is considerable cognitive potential in late life, as well as how such potential can be actuated or preserved.

Some authors have focused also on the social policy implications of late life potential. For example,Achenbaum (1990) suggested that North American society may have to place a greater emphasis on adult education. In particular, training and retraining programs may have to be instituted so that potentially competent workers are not placed on the sidelines simply because of their age. A critical issue, however, is how and who will fund such training and retraining programs. Numerous other policy issues can be specified, but most have the same fundamental theme: How do we take advantage of increasing numbers of adults who getting older but not substantially less competent? If this challenge is not addressed soon, the number of individuals who are prematurely discarded or discounted—whose skills and potential contributions will be forever lost—will grow.

Wisdom

The study of wisdom is as old as the study of human thought or philosophy. Although philosophers have struggled with the concept of wisdom for centuries, psychologists and other researchers in human development have addressed it only more recently. In the field of gerontology wisdom is naturally of considerable interest. There are relatively few processes that are generally thought to improve substantially with advancing age. Wisdom is one such process.

Many provocative questions have been addressed. What is wisdom, and how does one know if someone is wise? What are the signs of wisdom, and how might it be recognized? Until the late 1980s only a few researchers had attempted to study the aging of wisdom (e.g., Baltes & Smith, 1990; Baltes & Staudinger, 1993; Clayton & Birren, 1980; Sternberg, 1990). One early psychologist, G. Stanley Hall (1922), thought that wisdom was one of the desirable characteristics of late adulthood. For Hall, wisdom included taking perspective, synthesizing significant factors of life, and moving toward higher levels. Other observers have portrayed wisdom as good or sound judgment regarding the conduct of life. Good judgment about a life problem would probably involve consideration of a variety of aspects of the situation: personal strengths and weaknesses, talents and emotions, health and physical abilities, as well as social and cultural considerations.

Recent investigators have explored empirically whether wisdom does indeed develop in late life and, if so, whether it is in fact an important aspect of successful aging. The first step is to define wisdom in a way that allows for empirical study. It is clear from common conceptions of wisdom that it involves good judgment about life problems. As pointed out by Kekes (1983), the life problems that bring out wisdom are those for which there may be multiple considerations and even multiple solutions, each with a variety of repercussions. For example, it is likely to require some wisdom to deal with a life problem such as deciding whether to leave college and get a job or whether to marry or divorce somebody. These are everyday problems with many uncertainties associated with them—this is what makes them complex and difficult. Solving such problems well (or wisely) is important because of the significant implications for the individual’s (and family’s) future.

Wise decisions would therefore involve several ingredients (Baltes & Staudinger, 1993). First, there would be some analysis of the problem. This would include knowledge about (a)theindividualandhisorhertalentsandweaknesses,(b)the situation or problem with which they are faced, (c) the context of this problem, especially with respect to the individual’s life-span development. In cognitive psychology this kind of knowledge—knowledge about something—is known as declarative knowledge. Second, wisdom would involve some knowledge about how to solve the problem. This would include strategies and procedures that typically work for a particular kind of problem. In cognitive psychology this kind of knowledge—knowledge about how to do something—is known as procedural knowledge. Third, wisdom would involve good judgment about what to do in particular situations. In this way, the declarative knowledge would be combined with the procedural knowledge and decisions or suggestions wouldresult.Becauseoftheuncertaintyassociatedwithmany life problems, it is likely that even these judgments would be qualified. That is, good judgments may be characterized less by absolute recommendations than by qualified suggestions. Such tentative suggestions would be dependent on new developments in the life course, new information obtained, or other changing aspects of the context.

Is wise advice therefore inherently indeterminate? Probably not, for the wisest way to solve some life problems could be known with certainty. Solving a problematic life situation by turning to addictive drugs is not a wise decision. A wise person would be unlikely to give a feeble answer to someone seeking advice about whether to begin taking heroin as an escape from a given set of life problems. This fact makes the measurement of wisdom difficult.

How can wisdom be measured? Some researchers have presented a variety of life problems in the form of personal vignettes to adults of all ages (J. Smith & Baltes, 1990). They then asked them to indicate how they would go about giving advice to the character in the vignette. Wisdom is measured by analyzing the responses given to these problems. Two kinds of problems have been used. J. Smith and Baltes (1990) used life-planning problems. In these problems individuals learn about a problem in the life of a character and are asked to indicate what the character should do and consider in planning the future. Staudinger, Smith, and Baltes (1992) used life-review problems. In these problems a similar vignette is presented in which a character experiences a life event that causes the person to look back over his or her life. The individual solving the problem is asked to describe the aspects of life that the character might remember, as well as how the character might explain or evaluate his or her life.

Would older adults do better at these tasks than younger adults? Or would wise (but not unwise) older adults do better than younger adults? These questions are critical in evaluating the results of the life-planning and life-review wisdom studies. Results from both studies indicate a substantial similarity between young, middle-aged, and older adults in how they respond to these problems. Obviously, an initial expectation would have been that if wisdom is associated with aging, then older adults would do better than younger adults. That this was not found may reflect on (a) the adequacy of the measures of wisdom and (b) the definition of wisdom being used. Future research will further refine the measures and theories of wisdom and aging (e.g., Simonton, 1990; Sternberg, 1990). One avenue to explore is whether the development of wisdom occurs only for a select few older adults. If this is true, it would be unlikely that a group of normal older adults would perform at a particularly high level. Some results from these studies appear to be promising. For example, middle-aged and older adults who were selected to be tested on the basis of having been nominated by a peer performed slightly better than did comparison groups on some indicators related to wisdom (Baltes & Staudinger, 1993). Wisdom, like intelligence, may require some training and effort to maintain.

Creativity

Creativity is the “ability to innovate, to change the environment rather than merely adjust to it in a more passive sense” (Simonton, 1990, p. 320). If the popular stereotype about wisdom is that it grows with age, the stereotype about creativity may be that it declines during adulthood. Are people more creative in their 20s than in their 60s?Think about all the creative people whom you know—scientists, poets, artists, novelists, actors, musicians, and so forth.Are younger individuals typically better than older individuals in the same field? Are their most creative products generated during their early years in the field? Or are creative people always creative, regardless of their age? Many researchers have investigated these issues. For example, some samples believe that aging is accompanied by an increase in conservatism and cautiousness and a decrease in creative achievement and productivity (e.g., Heckhausen, Dixon, & Baltes, 1989; Hummert et al., 1994). Unlike research on wisdom, there are clear results about the development of creativity during adulthood.

In 1953 Lehman published an influential but controversial volume titled Age and Achievement, in which he plotted creative productivity as a function of age.After examining the historical records in numerous domains of productivity, he found that there was an increase in creative output in early adulthood, followed by a decline. Although there were numerous criticisms of his methods and interpretations (e.g., Dennis, 1954, 1956; Lehman, 1956), recent reviewers argue that Lehman’s basic results are correct. More recently, Simonton (1990, 1994) noted that across a wide range of studies a robust age-related function can be observed but that there are some important qualifications. For example, in some cases the lifespan trajectories have two peaks, one in early adulthood and one in late adulthood. The latter can be thought of as the second-wind phenomenon. That is, in some cases there may be a general decline in creative output until a second wind hits about retirement age.

A second important qualification to Lehman’s model is that both the age at peak performance and the steepness of the decline in creative productivity vary according to domain. This means that peak creativity in some domains may occur much earlier in life than in other domains. For example, in fields such as pure mathematics, lyric poetry, and theoretical physics, the peaks are in the late 20s or early 30s. In contrast, in fields such as history, philosophy, novel writing, and general scholarship, the peaks are in the 40s or 50s, and the declines are not very steep. For a number of fields—including psychology—the peak of creative output is in the late 30s or early 40s (see Lehman, 1956; Simonton, 1990, 1994).

What about the argument that creativity should not be measured simply by amount of creative output—a quantitative measure? Instead, it should be measured by quality of output—a focus on the truly creative part of productivity. Would this shift in emphasis result in a different profile across the life span? As Simonton (1994) elegantly showed, the answer to this intriguing question is no. Separating the truly creative productions from the less inspired pieces results in virtually identical patterns across the life course. This implies that the quantity of creative output is highly related to the quality of that output. This relationship holds throughout the life course, or the career of an individual. Specifically, those who begin their careers with a great deal of productive output can continue this output throughout their careers. People who are less precocious may also have careers characterized by a stable quality-to-quantity ratio of productivity.

There are several reasons that some careers can be curtailed or become substantially less productive. As Simonton (1990, 1994) noted, these include declining physical health, increasing family responsibilities, and accumulating administrative activities. Declining physical health can, of course, make concentrated effort more laborious or even less frequent. Both increasing family responsibilities and administrative duties can reduce the amount of time available for productive and creative work. Few administrators in universities, for example, are able to maintain full and energetic scholarship programs. However, with seniority some compensatory mechanisms may be available. For example, highly accomplished senior researchers may be called upon to perform full-time administrative duties (e.g., chair of a department at a university), but they may be able to employ several highly qualified and ambitious postdoctoral fellows, as well as numerous graduate students, to carry on their scholarly programs. These younger collaborators become, in this way, human compensatory mechanisms for senior creative scholars.

Overall, Simonton’s (1990, 1994) research has generated three general statements about the life course of creativity. First, there is age-related decline in creativity in the late years of life. However, this decline is rarely so substantial as to turn a creative person into a noncreative person. Most creative individuals’lives end before their potential for creative production is exhausted. Second, how creative or productive older adults are depends more on their early-life creativity than on their age. Simonton argued that people who are exceptionally creative in early adulthood are often quite prolific throughout their careers. Indeed, they may continue to produce excellent creative products into very late life. Third, there is no evidence to suggest that the decline in creative output occurs because of a corresponding decline in cognitive skills. Even individuals who enter new arenas of interest in middle or late life have the opportunity to have productive new careers. Creativity, then, may be one area in which potential in late life may be actuated. At the least, it is possible to contend that creative people may continue to be creative across their careers.

Compensation

Compensation is a promising new concept in the field of cognitive aging. It refers to a set of mechanisms through which an individual may continue to perform difficult or complex skills although they are experiencing some loss in relevant abilities required to perform a particular task. As noted earlier, aging involves decline in fundamental sensory, motor, neurological, and cognitive abilities. Many of these abilities are components of higher level skills. Some of these skills may be maintained into late life. One mechanism through which such maintenance can occur is compensation.Adults may be able to compensate for declines that they experience in even very basic components; they may continue to perform even complex skills (composing, writingnovels, driving) at competent, if not creative, levels.

Several forms of compensation have been identified (Bäckman & Dixon, 1992; Dixon & Bäckman, 1995, 1999; Salthouse, 1995). For older adults all forms of compensation begin with the experience of a mismatch between their available abilities and the requirements they either place upon themselves (as personal expectations) or accept as given by the community in which they operate. The term community can refer to a wide range of environmental demands, such as those accruing as a function of professional requirements, social and interactive obligations, familial responsibilities, sensory and physical contexts, and so forth. The important point is that by using one or more of the forms of compensation, the gap between their ability and their expected level of performance can be closed. In this way, a satisfactory level of performance for a given skill can be attained, and an individual’s potential can be maximized. Compensation can occur in normal aging, but also as a form of recovery from brain injury or other pathogenic neurological conditions (e.g., Dixon & Bäckman, 1999; Wilson & Watson, 1996). Compensation is also a viable concept in recovery from a wide range of social and personal deficits and losses, many of which are quite pertinent to the study of cognitive aging (see Dixon & Bäckman, 1995).

What are the forms of compensation applicable to aging in general, and to cognitive aging in particular? Scholars offer somewhat different perspectives on these forms (e.g., Marsiske, Lang, Baltes, & Baltes, 1995; Salthouse, 1995), but the convergence and overlap are impressive (Dixon & Bäckman, 1995). Four forms appear to cover most of the situations in which compensation might occur in late life. The first form is perhaps the simplest. It reflects investing time and effort when there is a deficit in learning or performing a target skill. For example, an individual whose work environment is becoming ever-more computerized, and whose understanding of hardware and specific applications is lagging behind, may compensate for the gap between her environmental demands and skill level by putting more time and effort into acquiring the requisite skills. This deliberate and effortful upgrading of her skill level such that it matches the requirements of her community can result in successful compensation.

The second form of compensation, substitution, originates in a deficit that is the result of important components of skills declining with age, and therefore contributing ineffectively to overall skill performance (e.g., Salthouse, 1995). Compensation as substitution occurs when other components of the skill are correspondingly improved, such that the overall skill performance level is maintained. That is, the global skill is supported by new, emerging components after the original components decline. One well-known example concerns aging typists who can no longer tap their fingers as fast as they might have as younger adults, and who can no longer respond to visual stimuli (e.g., to-be-typed characters) as quickly as they might have in earlier years (Salthouse, 1995). Finger tapping and reaction time are components of the global skill of typing, in that speeded typing cannot be accomplished without some contribution from these abilities. As Salthouse observed, however, some successful older typists compensated for these decrements by possibly developing a substitutable mechanism, namely, eye-hand coordination. That is, they compensated for slower speeds of reaction and tapping by looking further ahead in the to-be-typed text so that their fingers had more time to prepare for the upcoming characters. In this way, their overall performance (typing rate) could be maintained into late life.

A third compensatory process, selection and optimization, involves optimizing one’s development overall by selecting different paths or goals when the original one is blocked or unattainable (Marsiske et al., 1995). If the deficit is too great to overcome through investment of time and effort, and if no substitutable components are available, then this form of compensation might be invoked. Essentially, the deficit in the global skill is accepted, and alternative skills and performance domains are emphasized. For example, an aging typist for whom substitution is unavailable might become an office manager, combining “people” or supervisory skills with declarative and procedural knowledge about the office and business. In this way, one has selectively optimized one’s development by choosing an alternative path, after the original trajectory was blocked.

A fourth category reflects processes in which one adjusts goals and criteria of success. Specifically, individuals may accommodate deficits by modifying their goals (e.g., Brandtstädter & Wentura, 1995) or lowering their criteria of what constitutes successful performance (Dixon & Bäckman, 1995). For example, older adults may modify their goals or personal expectations of performance such that it is no longer necessary to perform at quite the same level or with quite the same speed as they did when they were younger. Given no other available form of compensation, an older typist might decide that her personally required typing rate can be adjusted downward, focusing perhaps instead on maintaining accuracy. A complication, of course, is that employers or senior colleagues may not concur with the lowered performance goals. For some everyday, social, and life skills, however, such changing expectations may indeed be a viable form of compensating for increasing limitations and performance decrements (Brandtstädter & Wentura, 1995). Managing one’s changing resources efficiently may involve devaluing and disengaging from some blocked goals while selecting new and feasible goals. Some aging-related losses may be compensated by rearranging priorities or constructing palliative meanings (i.e., selecting positive interpretations; Baltes, Staudinger, & Lindenberger, 1997; Brandtstädter & Wentura, 1995).

Compensation may be an important mechanism of successful aging, a means of realizing and maintaining cognitive potential into late life (Baltes & Baltes, 1990; Dixon, 1995). It is perhaps not an achievement that will garner awards from historians or critics (as would the creative products of a renowned composer), and it may not be a success that brings the respect accorded to the wise sage. It is, however, a practical and functional process associated with both elite levels of technical and artistic performance and everyday life skills such as driving, working, and leisure activities (Dixon, 1995).

Conclusions

Cognitive aging is a vibrant field of developmental psychology. The field of cognitive aging has become one of increasing theoretical complexity, methodological sophistication, and practical utility.Theoretical attention is given to diversity, directionality, multidimensionality, context, and (of course) changes with age. Also notable is the fact that the researchable contexts of cognitive aging extend from the biological (especially neurological) to the social (especially interactional) and even to the historical and cultural.This may be one reason that so many large-scale longitudinal studies of cognitive aging are being undertaken in many corners of the globe. These include the Seattle Longitudinal Study, as described in this research paper, as well as the Victoria Longitudinal Study (e.g., Dixon, Wahlin, et al., in press), the Swedish Betula Project (e.g., Nilsson et al., 1997), and the Berlin Aging Study (e.g., Baltes & Smith, 1997).

Because cognitive aging is a complex set of developmental phenomena intrinsically involving processes at many levels of analysis, with methods and techniques originating in disparate disciplines, it is profitably studied from select and complementary perspectives. In this research paper we illustrated some of the main domains of research in cognitive aging, as well as selected emerging trends.Although numerous handbooks and primers are available covering a broader range with more detail, we trust that this brief overview represents principal facets of this growing area of developmental science.

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