Moderators of Intellectual Change
Based on the research we have considered thus far, two different developmental trends emerge: We see gains in experience-based processes but losses in information-processing abilities. The continued growth in some areas is viewed as a product of lifelong learning. The losses are viewed as an inevitable result of the decline of physiological processes with age.
A number of researchers, though, emphasize individual differences in the rate of change in intellectual aging (Arbuckle et al., 1998; Baltes et al., 2006; MacDonald et al., 2004; Schaie, 1996; Wilson et al., 2002). These researchers do not deny that some adults show intellectual decline. Based on large individual differences in intellectual performance over time, they simply suggest that these decrements may not happen to everyone to the same extent. They argue that many reasons besides age explain performance differences. In this section, we will explore some of the social and physiological factors that have been proposed as modifiers of intellectual development. These include cohort differences, educational level, social variables, personality, health and lifestyle, and relevancy and appropriateness of tasks.
Cohort Differences. Do the differences in intellectual performance obtained in some situations reflect true age-related change or mainly cohort, or generational, differences? This question gets right to the heart of the debate over interpreting developmental research on intelligence. On the one hand, dozens of cross-sectional studies document significant differences in intellectual performance with age. On the other hand, several longitudinal investigations show either no decrement or even an increase in performance (Hertzog, Dixon et al., 2003; Schaie, 2005, 2008; Zelinski, Kennison, Watts, & Lewis, 2009).
The way to resolve the discrepancy between the two approaches involves comparing data collected over long periods of time from several samples and analyzed simultaneously in both cross-sectional and longitudinal designs as we discussed in Chapter 1. When this has been done, the results indicate that part of the apparent decline with age in performance on intelligence tests is due to generational differences rather than age differences (Schaie, 1996, 2005).
Marked generational changes in levels of performance on tests of primary abilities have been
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1889 1896 1903 1910 1917 1924 1931 1938 1945 1952 1959 1966
Figure 7.5 Cohort gradients showing cumulative cohort differences on five primary mental abilities for cohorts born from 1889 to 1966.
Source: Schaie, K. W. (1994). The course of adult intellectual development. American Psychologist, 49, 304-313. Copyright (c) 1994, American Psychological Society. Reprinted with Permission.
noted in the Seattle Longitudinal Study (Schaie, 1996, 2005). As you can see in Figure 7.5, more
recent cohorts generally score better than earlier cohorts on verbal meaning, spatial orientation, and inductive reasoning. These trends reflect better educational opportunities (e. g., in the past, compulsory education varied widely by state, in contrast to today), better lifestyles, better nutrition, and improved health care. Note that cohort differences on number ability show gradual declines over the middle 20th century and that word fluency is gradually increasing after showing declines earlier in the 20th century.
The complex pattern of cohort differences indicates that interpreting data from cross-sectional studies is difficult. Recall from Chapter 1 that crosssectional studies confound age and cohort; because there are both age – and cohort-related changes in intellectual abilities, drawing any meaningful
conclusions is nearly impossible. Schaie (1996, 2005) argues that the trends indicate a leveling off of cohort differences, which may come to a halt in the early part of the 21st century. This conclusion is supported by a study of 531 adult parent-offspring pairs that indicated that generational (cohort) improvements were becoming smaller for more recently born pairs (Schaie et al., 1992).
What about one’s generation affects rate of intellectual change? The importance of education for intellectual development during adulthood may partially account for cohort differences. People who are more highly educated tend to adopt lifestyles that foster the maintenance of cognitive abilities. Highly educated older adults are also the exception in their generation; opportunities to go to college were not as prevalent 50 years ago as they are now.
Thus one source of the cohort effect may be differences in the type and amount of education.
The evidence points to the maintenance of intellectual abilities in well-educated adults at least into old age (Schaie, 1990, 1996, 2005). As better-educated cohorts grow old, education may also provide an explanation of why cohort differences on many measures are not increasing at the same rates as they did in the 20th century (Schaie, 2008). In sum, cohort differences provide important evidence about changes in intellectual abilities in adulthood. However, we must be careful not to read too much into these trends and to recognize that they may not be sustained into the 21st century.
Information Processing. A number of researchers suggest that general processing constraints that occur with aging may help identify mechanisms that underlie decline in mechanic and fluid intelligence abilities with age (Baltes et al., 2006; Salthouse, 1997; Zimprich & Martin, 2002, 2009). For example, evidence suggests that perceptual speed accounts for the lion’s share of age-related decline in both fluid and crystallized mental abilities. Similarly, working memory decline with increasing age accounts for poor performance on the part of older adults when the tasks involve coordinating both new incoming information and stored information such as those found in the fluid and/or mechanic component of intelligence (Mayr & Kliegl, 2003; Salthouse,
1991) . Finally, evidence suggests that the inability to inhibit actions and thoughts or to avoid interference typically found in older adults may also account for efficient functioning in fluid and/or mechanic abilities (Brainerd, 1995; Stoltzfus et al.,
Overall, processing rate, working memory, and ability to inhibit tend to show decline during later adulthood and old age and are linked to physiological decline. However, studies in this area are still inconclusive in that it is difficult to make a clear – cut distinction between these three informationprocessing mechanisms. For example, proneness to interference when performing a task is highly correlated with perceptual speed (Hasher et al., 2002; Lustig et al., 2009; Salthouse & Meinz, 1995). As indicated earlier, it may be the case that future developments in cognitive neuroscience are likely
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to shed more light on the determinants of mental abilities involved in intellectual functioning (Baltes et al., 2006; Gazzaniga, 1995; Reuter-Lorenz, 2002).
Social and Lifestyle Variables. Numerous social demographic variables have been identified as important correlates of intellectual functioning. Think for a minute about the kind of job you currently have or would like to get. What kinds of intellectual skills does it demand? What similarities or differences are there between your chosen job (e. g., school counselor) and a different one (say, accountant)? An interesting line of research concerns how the differences in cognitive skills needed in different occupations makes a difference in intellectual development (Bosma et al., 2003; Schooler et al., 1999). To the extent that a job requires you to use certain cognitive abilities a great deal, you may be less likely to show declines in them as you age.
Support for this hypothesis comes from a study that examined both psychometric intelligence and practical intelligence as defined by Sternberg, discussed earlier. Practical intelligence, in this case in bank managers, is tacit knowledge (generic knowledge about a particular area) and expertise (Colonia- Willner, 1998). As expected, age was associated with decreases in psychometric test performance. However, decline was not found in more practical intelligence areas such as tacit knowledge and managerial skills.
Support for this hypothesis also comes from a longitudinal study showing that as adults grow
More and more women are employed in demanding occupations.
older, the level of complexity of their occupation continues to affect the level of their intellectual functioning as it did when they were 20 to 30 years younger (Schooler et al., 1999). This finding held for both men and women. It appears that occupations that require complex thought and independent judgment raise the level of people’s intellectual functioning, whereas occupations that do not require such complex processes decrease their level of intellectual functioning. Interestingly, the positive effect of job complexity is greater for older than for younger workers (Schooler & Caplan, 2009; Schooler et al., 1999).
Other social demographic variables implicated in slower rates of intellectual decline include a higher education and socioeconomic status (Cagney & Lauderdale, 2002; Turrell et al., 2002; Schaie, 2008), exposure to stimulating environments, the utilization of cultural and educational resources throughout adulthood (Schaie, 2008), and strong social engagement (Zunzunegui et al., 2003). For example, recent work examining social engagement suggests that loneliness is associated with more rapid cognitive decline (Tilvis et al., 2004; Wilson, Krueger et al., 2007). Social engagement has also been studied in dementia patients yielding similar results. High levels of social activity have been associated with a reduced risk in developing dementia (Fabrigoule et al., 1995; Wang et al., 2002; Wilson, Kreuger et al., 2007). Overall, there is growing evidence that higher levels of social interaction and engagement are related to reduced risk of cognitive decline and dementia in old age.
Finally, although some researchers suggest that a cognitively engaging lifestyle is a predictor of intellectual functioning (Arbuckle et al., 1998), it is still a matter of considerable debate (Hertzog et al., 2009). We examine this debate in the Current Controversies feature.
Personality. Several aspects of personality have been proposed as important for understanding intellectual change. Similar to research we examined in Chapter 6 on memory, one of these aspects concerns self-efficacy (Lachman et al., 1995). High initial levels of fluid abilities and a high sense of internal control led to positive changes in people’s perceptions of their abilities; low initial levels led to decreases in perceptions of ability and behavior (Lachman et al., 1995; Lachman & Andreoletti, 2006). A related personality aspect concerns people’s perceptions of changes in their intellectual performance (Schaie et al., 1994; Schaie, 1996). By comparing people’s perceptions to actual test performance, Schaie and colleagues classified people as realists (people who accurately estimated changes in performance), optimists (people who overestimated positive change), and pessimists (people who overestimate negative change). Most people were classified as realists, although women were more likely than men to be pessimists on spatial abilities, and older people were more likely than younger people to be pessimists on verbal meaning and inductive reasoning.
Neuroticism and chronic psychological distress have been implicated in rapid cognitive decline (Wilson, Arnold et al., 2006; Wilson, Bennett et al.,
2005) . This makes sense given that neuroticism is strongly associated with frequency of negative emotions. Negative emotions and psychological distress go hand-in-hand. Furthermore, neurobiological research suggests that chronic psychological distress may cause deteriorative changes in the limbic system of the brain that helps regulate emotion and cognition (Dwivedi et al., 2003; Webster et al.,
2002) . These deteriorative changes could cause cognitive impairment. However, this area is still in its infancy and further research is needed.
On a more positive note, positive beliefs and attitudes also have important indirect effects on cognitive enrichment. This indirect effect is reflected in the influence of these beliefs and attitudes on desirable behaviors such as exercise and mental stimulation that are known to be associated with enrichment effects on intelligence (Hertzog et al., 2009). For example, research indicates that people who have flexible attitudes at midlife tend to experience less decline in intellectual competence than people who are more rigid in middle age (Lachman, 2004; Schaie, 1996; Willis & Boron, 2008). Similarly, motor-cognitive flexibility in one’s 60s is highly predictive of numerical and verbal abilities in late life (O’Hanlon, 1993).
Health. One of the most difficult problems in any study of aging is the separation of normal processes from abnormal ones. So far our discussion of