Cognitive Aging Research Paper

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Abstract

Interest in cognitive aging has grown substantially during the past 25 years. For instance, the divisions of the American Psychological Association (APA) expanding most rapidly during this period have been those with a strong interest in aging such as aging and neuropsychology, a field that examines cognitive impairments associated with aging (e.g., Alzheimer’s disease). Responding to the growing interest in Alzheimer’s disease and other conditions afflicting numbers of older people, the U.S. Congress designated the 1990s as the ‘‘Decade of the Brain.’’ It might be said that that this interest applies especially to ‘‘older’’ brains. Funds are being invested at record high levels to increase the understanding and amelioration of the effects of age on intellectual vigor as well as on physical health. These efforts may be more important today than ever before. The reasons for this are demographic, legislative, physical, and economic.

Outline

  1. Introduction
  2. Cognitive Changes across the Life Span
  3. Age-Related Variability
  4. Evidence for Optimal Cognitive Aging
  5. Correlates of Optimal Cognitive Aging
  6. Looking Ahead

1. Introduction

1.1. Demographic Trends

America is graying. At the start of the new millennium, one of every seven U.S. citizens was over 65 years of age. By 2025, this proportion will be one of every five. The group of those age 85 years or over, currently numbering in excess of 3 million, is the fastest-growing segment of the population. This increase in the numbers of elders is not a uniquely American phenomenon. By 2025, those age 65 years or over in Japan will double. The People’s Republic of China, Korea, and Malaysia anticipate a tripling of this age group. There is little benefit in a longer lifetime if the quality of health and mental acuity are greatly diminished during these added years. The budget of the National Institute on Aging has tripled during the past decade. Substantial portions of that agency’s funds are earmarked for research to reduce the incidence of Alzheimer’s disease and other forms of cognitive impairment and to enhance intellectual vitality during the later years.

1.2. Legislative Changes

Compelling workers to retire due to age was banned in the United States by Public Law 99-592 as of January 1, 1994. With the exception of a small number of occupations, such as Federal Bureau of Investigation agents and airline pilots, this law eliminated age-based mandatory retirement for nearly everyone. A primary reason for passage of this law was that many studies had found that a large number of older individuals can match the physical and mental vigor of their younger colleagues. Because variability increases with age, it is necessary to differentiate between functional age and chronological age among seniors. Currently, organizations and professions are struggling with the implementation of objective and fair methods for retaining their older physically and cognitively vigorous employees while creating scenarios for encouraging the retirement of those whose abilities have declined to the point that their job performance is compromised.

1.3. Increased Physical and Cognitive Vigor

Despite the growing trend toward obesity in the United States, the physical and cognitive vigor of a large proportion of 60-, 70-, and even 80-year-olds today is superior to that of their parents and grandparents of the same age generations ago. Research confirms these observations. A 1997 report by the National Academy of Sciences showed a dramatic increase in the proportion of Americans over 65 years of age who are able to care for themselves. Reasons offered to account for these gains include reductions in drinking and smoking, better diets, weight loss, control of blood pressure, and use of aspirin to reduce heart attacks and strokes. Also, modern medicine has been chipping away at physical conditions that greatly affect cognition, including medications for diabetes, hypertension, and heart problems as well as advances in cardiac surgery and neurosurgery. Better physical health is strongly correlated with higher levels of intellectual functioning among older individuals.

1.4. Economic Needs

One unanticipated benefit of Public Law 99-592 is that the American economy will need its aging ‘‘baby-boomers’’—those born during the 1946–1964 era—to work well past what used to be the normal retirement age into the first quarter of the 21st century. The reason is that the labor pool is shrinking due to the ‘‘baby-bust’’ generation—those born during the 1965–1977 era— now entering the workforce. Because their yearly birth pools were much smaller than those during the previous 20 years of the baby boom, the labor force will experience a shortfall in those age groups that organizations have traditionally relied on to form the backbone of their workforces, that is, those 30 to 44 years of age.

By 2009, there will be 10.6% fewer men and women in that age group than there were a decade earlier. Census projections estimate that there will not be as many people in that age group as there were in 2000 until 2025. A source of workers that could fill this projected labor shortage are men and women in their 60s and early 70s. Fully 70% of the baby boomers, now at midlife, say that they want to stay on their jobs after reaching 65 years of age. A large proportion of these individuals are mentally and physically fit to continue working if opportunities are made available.

2. Cognitive Changes Across The Life Span

What happens to cognitive abilities over the life span? Which aptitudes are impaired most dramatically, and which are most likely to be spared? How much variability is there among people of a given age as they grow older? This section examines global changes in cognition through the life cycle and trace the age-associated pattern of decline among particular aptitudes, paying close attention to the degree to which some are impaired or spared. It also discusses evidence in support of increasing dedifferentiation of cognitive functions with advancing age.

2.1. Overall Cognitive Changes through the Life Span

Figure 1 shows the decline in Full Scale IQ from 30 to 75-plus years of age on an earlier version of the Wechsler Adult Intelligence Scale (WAIS). The curve is derived by comparing the average of the scaled scores for each older age group decade with the norms for 25to 34-year-olds. Overall, cognitive scores slope gently downward until 60 years of age. At that point, the level of intellectual functioning of the average 60-year-old is only 10% less than that of the average 30-year-old. But then the cognitive decline accelerates. During the next decade, the overall IQ drops 9%. The scores of those age 75 years or over are 11% lower than those of 70-year-olds.

A limitation of these data is that the WAIS respondents were not matched for characteristics (other than age) that affect cognitive changes over the life span. These other characteristics are educational level, social class background, and access to health care. Those who have more education, are wealthier, and are able to avail themselves of adequate medical services usually score higher on cognitive tests than do their less fortunate age mates. Studies that have rigorously matched age groups on these characteristics have found that the shape of the curves of overall cognitive decline is similar but that the test scores are higher at every age for those with more advantages.

2.2. Decline of Specific Aptitudes through the Life Span

Although overall intellectual functioning declines predictably from 30 years of age onward, the downward progression of individual aptitudes varies greatly. For instance, the various versions of the WAIS all have found that the Verbal IQ scores slope downward far more gradually than do the Performance IQ scores. For instance, scores on the Verbal IQ decline 10% from 30 to 70 years of age, whereas scores on the Performance IQ drop 25% during this same period.

FIGURE 1 Average WAIS Full Scale IQ scores for older age groups compared with 25to 34-year-olds. Adapted from Kaufman, A. S. (1990). Assessing adolescent and adult intelligence. Boston: Allyn & Bacon.

The types of abilities in the WAIS Verbal and Performance sections explain why there is so much difference in the rate of decline. The Verbal IQ score is based largely on crystallized abilities. In contrast, the Performance IQ subtests are composed of largely fluid aptitudes. Research by Salthouse and colleagues has demonstrated that fluid aptitudes, such as processing speed and working memory, are greatly impaired by aging. Tests involving processing speed typically require solving complex problems under time pressure. Being required to learn a number–symbol code and then to enter the proper number next to a list of symbols is an example. Working memory involves storing an important piece of information while working on another task. Backward number recall is an example.

Age differences in processing speed and working memory apply much more to complex tasks than to simpler ones. For instance, little difference occurs between younger and older adults on analogies of low and medium difficulty under time pressure. Where the performance of older test takers falls off, relative to that of young adults, is on the hardest of the analogies (e.g., ‘‘Fission is to splitting as fusion is to ’’) under stressful time limits. The differences are shown in Fig. 2. Research reports summarized by Heaton and colleagues in 1981 show other aptitudes whose scores decline earlier and more steeply with increasing age. Timed spatial recall, reasoning, and verbal memory after delay are examples. In contrast, attention, word knowledge, and calculation skills remain relatively stable and are largely spared by the aging process.

All age groups have more difficulty with tasks requiring dual-task or divided attention. The increased incidence of automobile accidents among drivers using cell phones is an example. As people age, their dual-task performance declines rapidly. Over the past three decades, scientific studies have consistently reported that younger adults outperform older adults on many different tests of dual task attention, for example, classifying a list of words appearing on a computer screen as verbs or nouns while simultaneously listening to a string of numbers and pushing a button when hearing two odd numbers in a row.

Although there is clear evidence of substantial disparity in the rate of decline of specific aptitudes, a number of studies have reported data showing dedifferentiation of cognitive functions with advancing age. That is, in normal older adults, the decline in specific aptitudes from decade to decade is embedded within a greater decline in global intellectual functioning. The evidence is stronger in cross-sectional data and among test scores based on accuracy alone. Longitudinal studies and test results combining speed with accuracy show weaker but similar patterns. Explanations for this phenomenon vary. One theory is that dedifferentiation is simply a symptom of cognitive decline. Another view, based on imaging studies, is that older adults compensate for diminished skills by drawing resources from other areas of the brain that are not normally activated during mental tasks.

2.3. Alzheimer’s Disease

If the 1990s was indeed the Decade of the Brain, it could also be said that the 1980s was the decade when Alzheimer’s disease (AD) and other forms of dementia began to attract public attention as potential threats to those entering the decades beyond middle age. The Alzheimer’s Disease and Related Disorders Association was founded in 1980. In that same year, according to Lexis/Nexis (an electronic database for media publications), major U.S. newspapers mentioned AD or dementia twice. In the year 2000, there were 250 separate pieces about AD or dementia.

FIGURE 2 Effect of time pressure on analogy scores by difficulty level. Adapted from Salthouse, T. A. (1992). Why adult age differences increase with task complexity. Developmental Psychology, 28, 905–919.

AD was first described by a German psychiatrist, Alois Alzheimer, in 1907. His first case was a 50-year-old woman whose memory and other cognitive functions deteriorated rapidly over a 5-year period before she died. An autopsy found abnormal brain structures that are referred to as neurofibrillary tangles. and neuritic plaques. As this case demonstrates, the relatively young onset differentiates AD from senile dementia. Today, health care specialists distinguish between presenile AD (prior to 65 years of age) and senile AD (age 65 years or over).

The criteria for AD include a gradual decline in at least two intellectual functions (e.g., attention, memory, language, reasoning, spatial ability) that are sufficient to significantly impair social relationships and/or performance at work. This decline cannot be explained by head trauma, neurological conditions, ill health, severe psychiatric symptoms, or drug/alcohol abuse. The cognitive deterioration also may be associated with depression, emotional outbursts, and/or apathy. It is not unusual to find AD occurring in individuals who otherwise are in good health.

At the start of the new millennium, there were an estimated 5 million people in the United States with AD or other forms of dementia. Prevalence estimates vary, however, and depend on the criteria used for making the diagnosis. For instance, a research team in England rated 100 elderly, community-dwelling volunteers using seven different sets of diagnostic criteria for AD. They found that between 3 and 63% of this population would be judged as ‘‘having’’ AD, depending on which standards were applied. A survey of the incidence of AD among older people in seven countries found proportions ranging from 1.9 to 52.7% of the population. One explanation for the disparate findings on the frequency of AD is the differences in the way in which the condition was assessed. Diagnoses that used tests that included measures of both crystallized and fluid abilities produced more consistent estimates. Applying these test-based standards, AD appears to afflict approximately 3% of 65to 69-year-olds, 6% of 70to 74-year-olds, and 11% of

75to 79-year-olds. Beyond 80 years of age, the proportion of AD rises sharply.

3. Age-Related Variability

Studies of age-related changes in cognitive functions have concentrated on what are called ‘‘measures of central tendency,’’ which are most often the mean or average scores. Figures 1 and 2 are illustrations of this approach. Typically, the mean scores of 30-year-olds are compared with the averages of groups of those in older decades. The downward slope of these age group means is then reported. What has been overlooked by focusing on averages alone is what happens to the variability of the individual scores with each advancing decade. The increasing variability with age found in the cross-sectional study of the cognitive aging of 1002 physicians using a computerized test, MicroCog, is an example.

Figure 3 shows the percentage of decline in MicroCog total score in each age group after 40 years. This is compared with the percentage growth of the variability for each decade during this same period. It can be seen that the standard deviations of the age groups rise much more rapidly than the mean scores decline. At 70 years of age, the average physician’s MicroCog total score was 13% lower than that of the typical 40-year-old. But the variability of the scores for these 70-year-olds was 57% greater than that for their younger colleagues.

Growing variability within advancing age groups is not specific to these data. Summaries of other studies of age-associated changes in cognition have reported that four of every five studies found that variance within each age group increased with advancing age. These findings occurred equally in both cross-sectional and longitudinal research.

The practical value of being aware of this growing age group variability is that it indicates that a number of older individuals continue to function as well as those in their prime. These older individuals might be called optimal cognitive agers (OCAs).

4. Evidence For Optimal Cognitive Aging

Newspapers and magazines often features stories of elders who have been productive and successful until very late in life. Novelists James Michener and Barbara Cartland were still writing into their 90s. Heart transplant pioneer Michael DeBakey, South African political leader Nelson Mandela, musician Lionel Hampton, and humanitarian Mother Teresa worked productively in their 80s. Grandma Moses did not begin painting until she was 78 years old and continued well beyond her 100th birthday.

FIGURE 3 Percentage changes in MicroCog total score and variability from 40 years of age: 1002 Physicians. Reprinted by permission of the publishers from Profiles in Cognitive Aging by Douglas H. Powell in collaboration with Dean Whitla, Cambridge, MA: Harvard University Press, Copyright # 1994 by the President and Fellows of Harvard College.

Social scientists are sometimes skeptical of such examples, wondering whether these people are merely statistical anomalies rather than representative of the vast majority of their age mates. However, empirical evidence now confirms the presence of large numbers of elders who continue to function cognitively at a level similar to those in midlife. This group of individuals, the OCAs, can be distinguished from their contemporaries by applying statistical standards.

Consider the following example. The MicroCog study described earlier obtained cognitive test scores on a large number of physicians from 25 to 92 years of age. Suppose that we wanted to know what proportion of older physicians were OCAs. We could use those doctors in their prime (say, 45–54 years of age) as a comparison group and then set a statistical threshold for optimal cognitive aging. For example, we might choose a cutting score of the 10th percentile, approximately –1.3 standard deviation, of those 45 to 54 years of age. In other words, for doctors to qualify as OCAs by this standard, their scores on MicroCog must be higher than the bottom 10% of those in midlife. The percentages of physicians age 65 years or over who meet this statistical standard are shown in Table I.

These data confirm what informal observation has told us: A large number of people continue to function at a high level cognitively well beyond 65 years of age. Nearly three-quarters of the 65to 69-year-old physicians, and half of the 70to 74-year-old physicians, scored as well on this cognitive test as did those in their prime. Onequarter (25%) of 75 to 79-year-old physicians, and slightly more than 10% of those beyond 80 years of age, performed as well as the reference group. These data are not specific to physicians. Similar proportions were found among nonphysician respondents in this study.

TABLE I Proportions of Older Physicians with MicoCog Scores above the 10th Percentile of 45 to 54-Year-Old Physicians

Although there are advantages to using respondents matched for education, social class, and access to health care for these calculations, nearly any cognitive test data set that reports individual test scores by age group through the life span can be analyzed to yield the percentage of older participants who are OCAs.

5. Correlates Of Optimal Cognitive Aging

What distinguishes these OCAs from their contemporaries whose cognitive decline follows the average downward trend for their age group? Are there behaviors within individuals’ control that are correlated with optimal cognitive aging? If so, identifying these factors may contribute to behavioral changes that can improve the quality of these later years for many people.

But first, another question must be asked: What are the relative contributions of heredity and environment to the quality of cognitive aging? Research finds that heredity does play a strong role in the acquisition, maintenance, and decline of most human qualities. It is also true that environmental forces exert a strong effect. Swedish scientists tested 80-year-old identical twins who had been separated at birth and raised in different home environments. The researchers estimated that approximately 60% of the variance (i.e., factors contributing to the similarity of cognitive ability) was genetic and that the rest was related to environmental influences. Reports from dozens of other twin studies have estimated that heredity accounts for 50 to 60% of what goes into mental ability. So, it seems that somewhere between 40 and 50% of the factors influencing the quality of cognitive aging is related to environmental influences, that is, factors that are partly within the control of each individual.

This section summarizes those behaviors that are correlated with optimal cognitive aging and that are within individuals’ control to varying degrees. These include activities that have been demonstrated to be directly related to higher levels of cognition in older adults. Also, this section describes a number of activities that indirectly benefit cognition because they are associated with better physical health. Finally, the section discusses selective optimization with compensation as a strategy for minimizing the inevitable negative effects of cognitive aging.

5.1. Activities That Directly Benefit Cognition

Activities that directly benefit cognition include regular exercise, mental enrichment, active social networks, and cognitive training. Of all the activities that could be recommended to maintain cognitive vitality, regular exercise has the greatest positive effect. This is because exercise strengthens the cardiovascular system, which maintains necessary blood flow to the brain. Cardiovascular disease is a major cause of cognitive impairment among individuals of any age. Meta-analyses of research over the past 40 years have found that younger and older individuals working out for 30 minutes or more every other day for at least 3 months perform at a higher level on tests of attention, memory, spatial ability, processing speed, and reasoning than do their sedentary neighbors. Of interest is that those individuals whose regimen combines strength/flexibility and aerobic training obtain slightly higher cognitive scores than do those who engage in aerobic or strength/flexibility exercise alone.

Physical and mental vigor can be improved until quite late in life. An illustration of the power of these programs was strength training for 90-year-olds at the Hebrew Rehabilitation Center for the Aged in Boston. After just 8 weeks of regular workouts, these nonagenarians increased their muscle strength by 174% and increased their walking speed by 48%. Although pre and post cognitive tests were not given, it is likely that improved intellectual vitality accompanied the physical gains. Baylor Medical School researchers found that physically active women and men in their late 60s had greater cerebral blood flow that resulted in higher cognitive test scores than those of their inactive contemporaries.

Mental enrichment stimulates cognitive functions. K. Warner Schaie, the director of the Seattle Longitudinal Study, and his coworkers identified factors that they believe are correlated with maintaining high levels of mental vigor well into later life. These include being open to new and stimulating experiences and having close relationships with individuals who have strong intellectual abilities. Scientific support for this thinking has come from the laboratory of Marian Diamond at the University of California, Berkeley. She was among the first to discover that laboratory animals that were raised in a more complex and challenging environment, along with other animals, developed a thicker frontal cortex than did those that lived in normal but unstimulating cages. She discovered that this occurred in both young and middle-aged animals. The increased thickness was because the existing brain cells in the cortex produced more connections (called dendrite branching) in response to outside stimulation. A research team at the University of California, Los Angeles, confirmed these findings with humans. The researchers looked at the brains of 20 adults at autopsy. Then, they correlated the size of the nerve cells in the brains’ cortexes with the activities reported by these individuals prior to death. They found that the cortexes of those older people who were more mentally and socially active were thicker than those of individuals who were not.

Social support has long been known to be correlated with physical health, but until recently little attention had been paid to its effect on cognition. Scientists from the MacArthur Studies of Successful Aging studied the impact of social networks on a battery of aptitude tests given to 70to 79-year-olds. They found that those who had more emotional support obtained higher test scores. At follow-up testing nearly 8 years later, higher retest aptitude scores were moderately correlated with having had greater social support. Other research has found that having larger and more diverse social networks and having more frequent contact with friends and family are related to less cognitive decline.

The question of whether age-related cognitive decline can be reversed through training has raised the interests of specialists in gerontology for the past quarter-century or so. Overall, it appears that most normally functioning individuals in the ‘‘young–old’’ years (approximately 60–75 years of age) and many of those who are older have the capacity to enhance their mental capabilities through practice. One example is the improvement made by participants in the Seattle Longitudinal Study who received 5 hours of training when they were 67, 74, and 81 years old. On average, the two younger groups improved their reasoning and spatial abilities to the levels of their test scores of 14 years earlier. Octogenarians were able to improve their performance to the level of 7 years earlier.

Follow-up studies of cognitive training have found that only those mental skills selected for remediation improved. Those not targeted for tutorial work remained the same as when the instruction began. Thus, if the goal of the program was to better remember a list of words, the participants did not wind up also exhibiting stronger calculation skills at the end of training.

Surveys of the published reports on cognitive training have found that many different methods produce positive results. Older participants at the Max Planck Institute in Berlin who spent 5 hours studying self-help books on improving fluid (spatial) abilities performed as well on tests as did those who had 5 hours of training. These gains were maintained on tests 6 months later. Similar results have been achieved with a wide range of other interventions, with some of them being quite indirect. For instance, members of groups that practiced transcendental meditation regularly improved their scores on cognitive tests far more than did those who did not.

So far, the effects of the training are largely untested in real life. After completing a course on memory improvement, is a woman better able to recall a list of errands she must run? After cognitive training, can a man more easily remember where he left his car in a supermarket parking lot?

5.2. Activities That Indirectly Benefit Cognition

Intellectual functions are indirectly influenced by a number of activities that enhance physical health. In an otherwise reasonably healthy aging population, these include behaviors that benefit cardiovascular functions and strengthen the immune system.

In addition to regular exercise, two crucial contributors to cardiovascular health are weight control and blood pressure management. Obesity is a growing problem in the United States. Depending on which criteria are applied, the proportion of overweight adults in the United States currently varies from 37 to 67%. By any standard, the percentage of obese adults has nearly doubled during the past 40 years. Excess weight is associated with greater risk for diabetes, hypertension, and cardiovascular disease—three conditions that adversely affect cognition. Obesity increases with age, partly because fewer calories are required to support normal activity with advancing years and partly because many older adults are physically inactive. In the year 2000, 35% of American older adults reported that they had engaged in no physical activity during the previous month.

Controlling blood pressure reduces the risk of cardiovascular disease and stroke. Participants in the Framingham Longitudinal Study with untreated hypertension scored lower on cognitive tests than did those with normal blood pressure. Increased diastolic blood pressure had particularly negative consequences for intelligence. The intellectual consequences of high blood pressure are far more serious for younger people. Hypertensives under 40 years of age had far lower scores on cognitive tests of attention, memory, mental flexibility, and reasoning than did age-matched normal individuals. Beginning to control high blood pressure early has substantial cognitive and physical advantages.

Physical vitality and cognitive vitality are greatly affected by the efficiency of the immune system. The immune system declines with age. Just as with age-related cognition, however, considerable variability occurs in immune system functions among older people. Until the past decade, it was assumed that the immune system functioned independently of psychosocial influences. Over the past 10 years, however, evidence has accumulated that the immune system is significantly influenced by mental states. This has led to increasing scientific interest in what is called psychoneuroimmunology. Of particular interest is the influence of stress on the suppression of the immune system given that this, in turn, can adversely affect health and cognition.

How much stress individuals confront, how well this stress is managed, and what other resources individuals can draw on to ameliorate the impact of negative events and bring comfort into their lives all are found to be correlated with health status. For example, more than 400 adult volunteers in Pittsburgh, Pennsylvania, were given nose drops containing a common cold virus. Not surprisingly, a large number of the volunteers developed severe colds soon afterward. But not everyone developed colds, and the severity levels of the colds varied widely. These scientists also measured the total amount of stress that these individuals had to deal with during the past year. Then, they compared these data with the susceptibility to, and the severity of, the colds. They found that individuals with more stress in their lives developed colds far more often, and with more severity, than did those whose stress scores were below average.

Elevated stress-related emotions of anxiety, depression, and anger correlate with lower scores on mental tests. This may be because high levels of stress diminish intellectual resources. An illustration is the finding that neuronal loss in the hippocampus area of the brain was moderately correlated with the number of months in combat in the war in Vietnam. The negative effect of stress emotions appears to be greatest on fluid abilities. For example, higher levels of anxiety have been demonstrated to be associated with lower scores on aptitudes such as analogies, picture memory, and block design.

5.3. Selective Optimization with Compensation

One of the most promising strategies for minimizing the impact of aging on cognitive performance is selective optimization with compensation. Developed by Baltes and coworkers, the essential ingredients in this approach are broken down into three steps. The first step is selection, that is, giving up some activities to concentrate the available mental energies on those remaining activities. The activities that continue to have priority are usually selected due to skills, motivations, and opportunities. An aging physician who wishes to remain active might be an example. In midlife, the physician has a busy practice and also teaches medical students. He simultaneously does clinical research, serves on professional committees and boards, and does consulting work. By his early 60s, the physician may begin to focus his mental energies on those patients and types of activities that he likes best, cutting back on those professional responsibilities in which his interest is waning. So, the physician keeps working at his practice but takes no new patients, and he continues his teaching and research but gives up committee work and consulting. At 70 years of age, the physician may limit his professional activities to teaching and research.

The next ingredient is optimization. This means doing everything possible to maximize one’s performance at those things that one chooses to do by anticipating the potential negative effects of cognitive aging. For example, the physician may begin to limit his practice to those patients who he believes he can treat most effectively, referring the others to colleagues. Keeping up with the recent developments in medicine and taking short courses to maintain and upgrade his medical skills become priority items. The physician may try to work ‘‘smarter,’’ that is, using computerized expert analyses and digital libraries more readily as opposed to trying to keep all of this information in his head. Optimization requires more time for preparation. For an older physician, this might entail carefully reviewing the chart of a patient in advance of an appointment rather than counting on his ability to get a picture of the medical history by a quick scan while seeing the patient. The aging physician also begins to dictate notes right after seeing the patient instead of waiting until the end of the day or later in the week to do so. In his 60s, the physician must accept the reality that far more time needs to be set aside to prepare lectures than was the case a decade earlier.

Compensation is doing everything that can be done to bolster fading abilities. Eyeglasses and hearing aids, to see and listen as well as possible, are examples from the physical standpoint. From the cognitive standpoint, compensation can include doing one task at a time and recognizing the effect of circadian rhythm (day– night cycle) and glucose/caffeine on cognition. The still working older physician compensates by avoiding dual-task activities such as making notes in a patient’s chart while talking about another patient on the telephone. Cognitive compensation might include putting to use an understanding of his personal circadian cycle. The average older person’s mental functions are stronger in the morning than later in the day, so the physician may schedule his most difficult patients in the morning and schedule less challenging professional activities in the afternoon. Finally, the physician may compensate for diminished mental acuity in the late afternoon with a cup of coffee and a cookie. For most healthy older individuals, moderate amounts of caffeine and glucose enhance attention and memory for a short time.

6. Looking Ahead

Judging from the remarkable progress and growth of interest in all aspects of aging during the past quarter century, there is little doubt that this will continue to be an area of expanding scientific and academic interest, as well as an area of considerable opportunity, during the decades ahead.

Several relatively recent developments make cognitive aging an especially interesting subspecialty within the field of aging. For instance, developments in neuroimaging technology over the past decade or so have enabled investigators to see in real time how the brain functions when carrying out specific intellectual tasks, to visualize the differences between the brain structures of younger individuals and those of older individuals, and to observe how the brain is compromised by conditions such as AD. Neuroimaging techniques have made possible a quantum leap in understanding the relationship between the brain and behavior. A new discipline, called cognitive neuroscience, draws deeply from this technology. At the time of this writing, the field is attracting the interest of the some of the most influential thinkers in the social sciences and medicine. Another important development has been the availability of findings from longitudinal studies of human development through much of the life span. Examples of these longitudinal studies include the Oakland/Berkeley Growth and Guidance Studies, the Terman Study of Children With High Ability, the Grant Study of Adult Development, the Seattle Longitudinal Study, and the Duke Longitudinal Studies. Some of these were begun during the 1920s and 1930s, whereas others started during the third quarter of the 20th century. Although many of these studies have limited generalizability because their participant pools are not representative of the U.S. population in terms of gender, education, social class, and race, they still provide an increased understanding of the aging human body and mind. As the participants from these investigations are moving into their later years, this research has begun to bear fruit. The numerous books and research papers published about these studies have contributed much to the understanding of cognitive aging.

But these publications do not nearly exhaust the opportunities to learn much more about cognitive aging. The raw data from many of these longitudinal studies—the actual responses from each participant every time he or she was examined—are currently archived and are available for analysis. For instance, the Henry A. Murray Research Center for the Study of Lives at Harvard University contains nearly 300 complete data sets from these longitudinal studies as well as other cross-sectional research that is better balanced for demographic variables. The rapid growth in data storage technology and computer memory and speed makes it possible today to access the raw data from these aging studies and to examine them using a computer in the privacy of a distant laboratory, professorial office, or student’s room. Today’s scholars can examine this vast storehouse of information, posing new questions, formulating new hypotheses, and looking for new answers in the responses of participants studied generations earlier.

The verity of any research finding is strengthened when it is demonstrated across studies, across generations, across geographical regions, and across investigators. Sophisticated statistical packages and advances in meta-analyses make it possible to compare findings from several studies at once. For instance, a student working on his or her thesis may want to know whether the findings from cross-sectional studies about the significant correlation between more social support and less cognitive decline also could be confirmed by looking at these same relationships in longitudinal studies of earlier epochs. The archived raw data can be easily loaded into the student’s computer for analysis of this new question.

Finally, because substantial scientific interest in cognitive aging is relatively new, much interesting work begs attention. Following are two examples. First, what are the characteristics of people who benefit most from cognitive training? What are the mediating effects of variables such as education, motivation, temperament, and degree of impairment? Do people with more education and higher levels of motivation, who are more extraverted and less intellectually impaired, benefit more from cognitive training? Or, is it just the opposite—do those people with less education and lower levels of motivation, and who are less extraverted and more intellectually impaired, make greater gains following training?

The second example is Public Law 99-592. Its passage solved one problem but exposed another. What standards will replace the arbitrary age limits of 55, 60, or 65 years to determine when someone is no longer able to do the job? Because of the currently shrinking labor pool, valid and fair procedures are urgently needed to determine whether an older person continues to have the skills necessary to perform competently in an occupation. So far, no techniques have been developed that have the necessary sensitivity to identify only those individuals with true cognitive impairment without falsely identifying others who, in fact, do not suffer from cognitive impairment.

Knowledge about cognitive aging has accrued rapidly during the past 25 years or so. More is on the way. As these new findings accumulate, they raise the probability that all individuals, through their behaviors in small increments, will be able to positively influence a significant portion of the cognitive quality of their later lives.

References:

  1. Baltes, P. B. (1997). On the incomplete architecture of human ontogeny: Selection, optimization, and compensation as a foundation of developmental theory. American Psychologist, 52, 366–380.
  2. Birren, J. E., & Schaie, K. W. (Eds.). (2001). Handbook of the psychology of aging (5th ed.). San Diego: Academic Press.
  3. Cohen, S. (1996). Psychological stress, immunity, and upper respiratory infections. Current Directions in Psychological Science, 5, 86–90.
  4. Craik, F. I. M., & Salthouse, T. A. (Eds.). The handbook of aging and cognition. Hillsdale, NJ: Lawrence Erlbaum.
  5. Damasio, A. R. (1994). Descartes’ error: Reason, emotion, and the human brain. New York: Avon Books.
  6. Diamond, M. C. (1988). Enriching heredity: The impact of the environment on the anatomy of the brain. New York: Free Press.
  7. Glaser, R., & Kiecolt-Glaser, J. (Eds.). (1994). Handbook of human stress and immunity. San Diego: Academic Press.
  8. Heaton, R. K., Grant, I., & Damasio, A. R. (1981). Normative observations on neuropsychological test performances in old age. In I. Grant, & K. Adams (Eds.), Neuropsychological assessment of neuropsychiatric disorders (pp. 100–120). New York: Oxford University Press.
  9. Kosslyn, S. M., & Koenig, O. (1992). Wet mind: The new cognitive neuroscience. New York: Free Press.
  10. Lexak, M. D. (1983). Neuropsychological assessment. New York: Oxford University Press.
  11. McClearn, G. E., Johansson, B., Berg, S., Pedersen, N. L., Ahern, F., Petrill, S. A., & Plomin, R. (1997). Substantial genetic influence on cognitive abilities in twins eighty or more years old. Science, 276, 1560–1563.
  12. Poon, L. W., Rubin, D. C., & Wilson, B. A. (Eds.). (1989). Everyday cognition in adulthood and later life. New York: Cambridge University Press.
  13. Rowe, J. W., & Kahn, R. L. (1987). Human aging: Usual and successful. Science, 237, 143–149.
  14. Salthouse, T. A. (1991). Theoretical perspectives on cognitive aging. Hillsdale, NJ: Lawrence Erlbaum.
  15. Salthouse, T. A. (1992). Mechanisms of age–cognition relations in adulthood. Hillsdale, NJ: Lawrence Erlbaum.

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