Developing a Research Agenda to Combat Ageism

By Sarah Raposo and Laura L. Carstensen

As the United States undergoes a transformation from a young to an old society, it is essential we address the problems individuals face as they age, and prepare for the opportunities longer lives afford. In light of the speed with which the world is aging, we are moving too slowly on both fronts. We argue that ageism is largely the crux of the problem. Widespread pessimism about the inevitability of age-related decline held by individuals, policy makers, and even the scientific community divert attention away from potentially solvable problems and reduce the likelihood that longer lives lived will improve quality of life at all ages.

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Below we outline a research agenda that addresses three issues deserving serious attention that often are overlooked in the traditional literature on ageism. They include the following: the pressing need to understand the role ageism plays in workforce participation and performance; the ways in which ageism may limit the effectiveness of interventions to improve health in older populations; and, failure in much scientific research to differentiate between pathological and normal aging, thus producing overly negative conclusions about the effects of aging.

Explicating the Third “-ism”

The clarion call to fight ageism was initiated by Robert Butler, inaugural director of the National Institute on Aging, who maintained that its perniciousness must be addressed if older people were to function fully in society. As he eloquently articulated in his Pulitzer Prize–winning book, Why Survive? Being Old in America, ageism is ubiquitous and hurts society as a whole, as well as older people (Butler, 1975).

Ageism continues today. Portrayals of incompetent older people abound in film and the arts, in fiction and nonfiction storylines. Popular periodicals and media outlets regularly publish articles about “grey tsunamis” that forecast dire economic slowdowns based purely on population aging. Entire industries have been built around products that promise to slow or reverse aging, implying that old age is something to avoid at all costs. There is little doubt ageist beliefs are widespread, involving many myths about the aging process and older people (Palmore, 1977, 2005). Even “positive” views of older adults often depict them as warm but incompetent, leading others to pity them (Fiske et al., 2002).

Research also has shown that awareness of negative stereotypes undermines cognitive performance (Chasteen et al., 2006), and that holding negative beliefs about aging is associated with relatively shorter life expectancies and poorer health over time (Levy, 2003). Aside from these important findings, however, relatively little is known about the ways ageism manifests in everyday life. Compared with the immense amount of literature on racism and sexism, surprisingly little empirical research has been conducted on the ramifications of ageism.

Ageism has been termed the third “-ism,” similar in many ways to racism and sexism. Research suggests that the strength of effect sizes for biases against the old are comparable—or even larger—than those observed in other forms of discrimination (Nosek, Banaji, and Greenwald, 2002). Ageism, nonetheless, is distinct from racism and sexism. For one, the discriminated group is one that (with a little luck) we all eventually join, and, in contrast to the long legacies of racism and sexism, ageism is relatively new (Achenbaum and Stearns, 1978).

In agricultural societies, when the family was the unit of production, those exceptional relatives who made it to old age were well-known loved ones and less likely to be mischaracterized on the basis of stereotypes. Also, unlike racism and sexism, where presumptions about inferiorities are unsubstantiated, ageism has roots in genuine age-related limitations in functional capacity and disease risk. Dementia, atherosclerosis, and bone diseases, for example, are common in old age and do affect function.

Consequently, ageism is more difficult to isolate. Findings that older medical patients are less likely than younger patients to receive aggressive and potentially life-saving medical care may, at times, reflect ageism, and at other times may reflect appropriate care for individuals with physiological vulnerabilities and multiple comorbidities. Thus, it is not always straightforward to interpret the meaning of age differences in treatment and access.

We argue that ageism entails overgeneralizations and exaggerations, such as generalizing incompetence based on physical disabilities, or applying broad stereotypes about cognitive ineptitudes of older people based on a minority of people who suffer from serious brain disease. It includes conflating the status of people in the years just before their deaths with the more than thirty-year period we call “old age.” Ageism is reflected in the tacit acceptance of age-related problems as inevitable consequences of advancing age, as opposed to problems in search of solutions. For these reasons, ageism is often (though not always) more subtle and more insidious than racism and sexism. It is why, ironically, even advocates for older adults sometimes play a role in perpetuating ageism by portraying older people as overly needy and frail.

The direct effects of ageism deserve more empirical investigation. This article focuses on three arguably more subtle areas where research is needed. We need to uncover the ways ageism impedes individuals and societies from benefitting from the engagement of older people in society. We need to understand how ageism limits the effectiveness of interventions to optimize aging; and we need to understand how ageism in science may limit progress in finding solutions to the real problems that aging entails. Below we consider ageism in work, health interventions, and science.

Does Ageism Affect Workforce Participation and Performance?

Longer lives will demand longer working lives for most Americans, as the vast majority cannot save enough during forty years of work to support thirty (or more) years in retirement. Even beyond the financial need to work, workforce participation holds benefits for physical and psychological well-being, along with anchoring individuals within the broader society (Berkman, Börsch-Supan, and Avendano, 2015). Since 2000, a decades-long trend toward ever-earlier retirements reversed and there has been a steady increase in retirement age over the last decade. Baby boomers say they plan to work past traditional retirement age and empirical evidence suggests that such statements are good indicators of future workforce participation (Hurd and Rohwedder, 2014).

It has yet to be seen, however, whether employers are interested in recruiting and retaining older workers. Labor economists regularly voice concerns about slowing productivity associated with an older workforce. The belief that older workers take jobs from younger workers remains widespread, despite compelling evidence that older people’s workforce participation is associated with less (not more) unemployment among younger workers (Munnell and Wu, 2012). Although the Age Discrimination in Employment Act (ADEA) was passed in 1967, this legislation has been relatively ineffective. Wrongful termination is the most common complaint under the ADEA, and many suspect that the legislation reduced employers’ inclinations to hire older workers due to fears of potential litigation (Lahey, 2006).

Rather than age-blind approaches, we maintain there is an important role for research to identify the relative strengths and weaknesses of older and younger workers, and to identify working conditions and roles that optimize performance at all ages.

One area where research is sorely needed concerns age differences in productivity. As noted, claims that older workers are less productive than younger workers are made on a regular basis, using cognitive slowing and physical decline as justification. There is very little evidence, however, that age-related changes in laboratory-documented cognitive performance are associated with reductions in work performance (Salthouse, 2004). On the contrary, performance in knowledge-based jobs appears to benefit from experience, thereby advantaging older workers (Avolio, Waldman, and McDaniel, 1990). In exceptional cases where there are observed reductions in performance, it is important not to assume simply that age-related decline is the cause. One historical analysis of scientific productivity among researchers revealed steady declines in publication rates and grant support as professors aged. Yet after mandatory retirement was eliminated, productivity and funding became positively associated with age (Stroebe, 2010). In other words, perceptions of remaining time, not age, impacted productivity.

In jobs that are physically demanding, such as nursing, mail delivery, or construction work, aging may well affect performance. In these cases, research is needed to develop technological solutions and ergonomic accommodations that reduce injuries and benefit productivity. There is little doubt that changes made to improve the safety of older workers will benefit younger workers as well.

Employers also are affected by time horizons, often not investing in employee training by mid-career and creating vicious cycles where perceptions about outdated skills are reified by workplace practices (Stanford Center on Longevity, 2014); for example, emphasizing the acquisition of new skills and efficiency in reviews of younger workers, while ignoring skills that develop over time and often contribute to greater cohesion of work groups, such as expertise and generativity (Carstensen, Beals, and Deevy, 2015).

To date, research on older workers’ strengths is nearly non-existent. Yet, there is evidence of improvement in a range of qualities that likely benefit work performance. Relative to younger adults, for example, older adults are more emotionally stable, less likely to experience anger or fear, and more likely to be interested in making meaningful contributions. In addition to having more knowledge and expertise, older people generate wiser responses to emotionally charged interpersonal problems and solutions for intergroup conflicts (Carstensen, 2014). Such qualities hold great potential for workplace productivity and cohesion, yet the ways in which they operate in work settings remain largely unrecognized or studied.

Workforces are not only aging, they are becoming more age-diversified than ever in history. In light of ubiquitous age segregation in the United States, the workplace presents a tremendous opportunity to combat ageism through intergenerational interactions. One reasonable hypothesis is that knowing and working with a diverse group of people reduces stereotyping. Another is that mixed-age teams can reveal the idiomatic strengths of young and older co-workers. It also is important to study optimal conditions for encouraging creative exchanges across generations, conditions where these exchanges suffer, and to identify potential difficulties associated with intergenerational workplaces, as well as ways to address them.

Some employers voice concerns about the discomfort young managers may experience when supervising older workers (Cappelli and Novelli, 2010), reminiscent of concerns expressed in the 1970s, when gender integration became widespread, that men may be uncomfortable having a female supervisor. Understanding the stages and processes involved in age integration will allow employers to anticipate and address potential problems. Research on gender integration suggested that when a single female joins an exclusively male group, performance sometimes suffers, yet once gender distribution is equalized, the decline reverses and, in some ways, improves (Allmendinger and Hackman, 1995). Empirical investigation of optimal age mixes for various jobs is essential.

There is growing evidence that benefits may accrue to employers with mixed-age teams—benefits that can also extend to consumers. A report from McDonald’s documented greater customer satisfaction at locations employing a mix of older and younger workers (Lancaster University, 2009). Automaker BMW reported that mixed-age workforces facilitate knowledge transfer (Kracht and Bethkenhagen, 2010). Mentorship training models also appear to benefit productivity (Allen et al., 2004).

The foregoing examples likely are the tip of the iceberg. Coupling the wisdom of the old with the speed and efficiency of the young may result in notable increases in productivity society-wide. Innovation also will come from older social entrepreneurs. Robert Chambers, winner of the 2006 Purpose Prize, founded a company called More Than Wheels to provide low-interest car loans to the rural poor after observing this cohort being exploited repeatedly at used car dealerships. When he was honored at the White House, Chambers said, “I was old enough to know injustice when I saw it—and experienced enough to do something about it.”

Does Ageism Limit Intervention Effectiveness?

Author and gerontologist Robert Kastenbaum famously chastised gerontology for its preoccupation with “counting the wrinkles of age,” as opposed to searching for causes and mechanisms underlying age differences. There continues to be a rather remarkable absence of efforts to improve aging outcomes, despite evidence for the profound influence that environments have on late-life outcomes. Cohort comparisons make this point well: One recent comparison of two birth cohorts of elderly people born in Denmark just ten years apart (1905 versus 1915) revealed striking gains in cognitive and physical functioning at advanced ages in the later born cohort, most likely associated with increased availability of education, improved living conditions, and medical advances (Christensen et al., 2013). Moreover, behavioral interventions are sometimes even more effective with older people than younger people. One large lifestyle intervention, which prescribed a low-fat diet and 150 minutes of exercise per week for people at risk for diabetes, was especially effective in older adults (Goldberg and Mather, 2012).

Yet in other domains, interventions have had limited success. Consider physical fitness: Americans generally fail to meet guidelines for physical activity, and older Americans are the most sedentary of any age group (National Center for Health Statistics, 2014). Given that physical activity decreases risks for developing a wide range of diseases, including dementia and diabetes, it is an obvious intervention target. Nonetheless, compared to efforts to modify lifestyles and increase physical fitness in the young, interventions targeting activity levels in older people are rare. Moreover, when older people are targeted, the modal approach is to apply interventions designed for younger populations to older people, as opposed to tailoring interventions to the goals and needs of older adults.

The consensus, unsurprisingly, is that interventions are less effective with older people. One recent effort by the Carstensen research group, however, demonstrated that an intervention tailored specifically to preferences and goals of older adults resulted in a near doubling in walking over a thirty-day period (Notthoff and Carstensen, 2014).

We must apply the best scholarship to understand the powerful role social class and education play in the striking heterogeneity in aging outcomes, especially considering that the cumulative effects of poverty, harsh working conditions, and persistent stress leave an alarming proportion of people with little in the way of personal resources as they approach old age (Adler and Stewart, 2010). These long-term outcomes, often attributed to aging, are more about disadvantage. Research on the accrued effects of disadvantage over decades may help signal individuals and policy makers that, as a nation, we literally cannot afford grossly inequitable lives.

We maintain that there is every reason to believe that functioning at advanced ages can be greatly improved above and beyond what it is today. It is essential that we focus efforts on identifying and modifying factors that lead to high levels of functioning very late in life, and find ways to distribute such efforts widely in the population.

Understanding the Role of Ageism in Science

Implicit ageism in science must be included in the research agenda. First and foremost, we must regularly include older people in studies of biological functioning, physical health, and human behavior. In a world where the fastest growing segment of the population is people older than age 85, it is essential that we stop the practice of considering young people as the prototypical humans. We need policies to ensure the inclusion of older adults in clinical trials of pharmaceuticals and new treatments so that medications and procedures are appropriate and optimized for this cohort.

The strong tradition in science to rely on central tendencies when characterizing samples and research findings obscures heterogeneity within age groups. Because variability increases systematically with age, these practices are increasingly likely to conflate the performance of high and low performers and characterize them by the average. There are at least two serious implications: we conflate sick and healthy people at increasingly older ages; and we attribute identified problems to aging as opposed to illness or other potentially modifiable causes. The traditional account of normal cognitive aging, for example, portrays performance as a steady downward trajectory. Nonetheless, a groundbreaking longitudinal study by Robert Wilson and colleagues, based on a sample of initially healthy older adults, showed that these practices may lead to erroneous conclusions (Wilson et al., 2011). Participants in a sixteen-year longitudinal study were assessed with an intensive cognitive battery of tests on multiple occasions over the course of the study. Some participants developed dementia. Rather than simply exclude these participants from the study when they displayed symptoms, Wilson and colleagues re-analyzed the data from the start of the study separately for those people who eventually displayed Alzheimer’s Disease and for those who never developed symptoms.

Their findings challenge the long-standing presumption that linear decline typifies “normal” cognitive aging. Instead, decline appears to be negligible among those who remain healthy, but notably pronounced in those who develop dementia. Importantly, participants who develop the disease show steep declines in cognition after a few years—years before their diagnosis. Presumably, investigators regularly and inadvertently include participants in the earliest stages of dementia in studies of normal aging; and because the incidence of dementia doubles every ten years, the percentage systematically increases. The bottom line is that cognitive decline associated with normal aging has been exaggerated.

In many cases, we simply do not know whether people enrolled in research are suffering from various pathologies. We need to assess this issue explicitly and develop standard reporting practices that acknowledge uncertainties where they exist.

Finally, we need much more research on subgroups of people who are aging exceptionally well, such as those who display negligible cognitive aging (Dubal et al., 2014) or display high levels of resilience (Ong et al., 2006). In this way, scientific models of successful aging can be developed that include cellular and behavioral targets that are amenable to change.


The presence of substantial numbers of older people offers societies a resource that has never before existed—millions of experienced, wise, older citizens who are healthier and better educated than any previous generation. To allow all individuals the opportunities to age successfully, it is crucial to combat ageism in workplace structures and policies, beliefs about aging that discourage interventions, and research practices that conflate normal aging with disease states. We must not aim too low. By addressing these issues, we can revise knowledge about aging and begin to redesign the life course to reap the individual and societal benefits that longer lives represent.

Sarah Raposo, B.A., is a doctoral candidate in the psychology department at Stanford University in Stanford, California. Laura L. Carstensen, Ph.D., is professor of psychology, the Fairleigh S. Dickinson Jr. Professor in Public Policy at Stanford University, and director of the Stanford Center on Longevity.

Editor’s Note: This article is taken from the Fall 2015 issue of ASA’s quarterly journal, Generations, an issue devoted to the topic “Ageism in America: Reframing the Issues and Impact.” ASA members receive Generations as a membership benefit; non-members may purchase subscriptions or single copies of issues at our online storeFull digital access to current and back issues of Generations is also available to ASA members and Generations subscribers at Ingenta Connect. For details, click here.


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