Can We Foresee the Future? Explaining and Predicting Cultural Change

What does the future hold? Our enduring fascination with predicting the future is reflected on the silver screen, as excitement builds over the Blade Runner sequel. We continue being mesmerized by ancient prophecies, such as Nostradamus' Quatrains. And we certainly pay very well to pundits, economists, and intelligence analysts who try to predict coming social, economic, and political events. Unfortunately, this abiding interest in prediction has not translated into the ability to forecast future events with much accuracy. In the late 19th and early 20th centuries, left-leaning social theorists envisioned a future in which societies were self-organized, and countries, religions, and private property were relics in the rubbish heap of history. Twentieth-century futurists envisioned a 21st century entirely different from the one we inhabit, including flying bicycles as the predominant means of transportation and permanent lunar colonies by the year 2000. Such futurists and social theorists are in good company. Even professionals, whose job description consists of forecasting future social trends, on the whole, do little better than lay people at predicting future geopolitical events. In fact, neither experts nor lay people do much better than chance (Tetlock, 2006; Tetlock & Gardner, 2016). As the seminal science fiction author Isaac Asimov -- inventor of the fictional discipline of psycho-history -- pointed out, there seems to be little hope for a real science of the future.

screen capture from the film blade runner

A portrayal of the future from the 1982 film Blade Runner depicting Los Angeles in 2019. Flying cars, androids, anonymity and omnipresent advertising. Some of these visions have come to fruition, most have not. Source: https://www.warnerbros.com/sites/default/files/blade_runner_background1.jpg

But there may be some hope after all. In our view, modeling cultural change on a large scale using cross-temporal data and theories derived from behavioral ecology can usher in a new era in social psychological and personality research. We have the potential to shift from explaining the past to predicting the future. This new approach to cultural change has led not only to the discoveries we report below,  but also has fundamental implications for psychometric assumptions and replicability in psychological science. We discuss these ideas in depth in our article published online ahead of print in Perspectives on Psychological Science (Varnum & Grossmann, 2017), and we highlight key contributions and promises of the emerging psychology of cultural change in the present piece.

To predict the future, we first have to understand the past. To do so, our research group and others have begun to conduct systematic research aimed at identifying the patterns of cultural change across a wide range of psychological phenomena. For example, we now know that over the past several decades, self-esteem, narcissism, and intelligence have increased in many Western societies (Twenge & Campbell, 2001; Twenge, Konrath, Foster, Campbell, & Bushman, 2008; Flynn, 1984; Trahan, Stuebing, Fletcher & Hiscock, 2014), whereas social capital (e.g. involvement in civic organizations and voter turn-out) has been on the decline (Putnam, 1995; 2000). More recently, our research group has found that over the past 60-70 years gender equality has been on the rise in the Western world (Varnum & Grossmann, 2016) and that individualist attitudes, practices, and relational patterns have increased across more than 60 countries around the globe (Grossmann & Varnum, 2015; Santos, Varnum & Grossmann, 2017). 

The idea that cultures are not static and do change is not novel. At least since Kurt Lewin and Lev Vygotsky, theorists have pointed out that psychological phenomena unfold within a temporal context. What is unique is a rigorous theory-driven attempt to not only document but to test explanations for patterns of societal change empirically. This emerging work suggests that among the most powerful contributors to cultural changes in areas like individualism, gender equality, and happiness are shifts in essential features of our ecologies. The idea that variations in ecological dimensions and cues like scarcity or population density might be linked to behavioral adaptations has been widely explored in the animal kingdom, and recently started to gain prominence as a way to explain variations in human behavior (Ellis, Bianchi, Griskevicius, & Frankenhuis, 2017; Sng, Neuberg, Varnum, & Kenrick, 2017). As we detail below, insights from behavioral ecology, along with statistical tools common to the field of econometrics, have enabled greater rigor and precision in understanding the causes of cultural change.

Individualism/Collectivism: A few years ago we wondered whether we might be able to use ecology as a way to understand rising individualism - - an increased focus on uniqueness and independence and emphasis on self-expression - - in the United States. To do so, we gathered data from numerous sources, ranging from national census surveys to types of words used in Google books, to preferences for relatively unique vs. common baby names for one’s children. Simultaneously, we aggregated country-level data concerning several theoretical explanations of why societies may become individualist or collectivist, including resource scarcity, climatic stress, urbanization, frequency of natural disasters, and the prevalence of infectious diseases. Next, we used cross-lagged statistical models to evaluate the magnitude and direction of the effects: Do shifts in individualism occur before or after possible shifts in respective ecological indicators? Using cross-correlation functions and tests of Granger causality we started to unpack these relationships. As it turned out, a shift toward greater affluence and white- (vs. blue) collar occupations was the most robust ecological predictor of levels of individualism over time, further shifts in levels of SES consistently preceded changes in levels of individualism in America (Grossmann & Varnum, 2015) – a finding that has since been extended and cross-validated by our team in a study examining the rise of individualism around the globe (Santos, Varnum, & Grossmann, 2017).

Changes in baby naming practices in the US from the 1880’s to the 2010s and predictions for future trends through 2030.

Changes in baby naming practices in the US from the 1880’s to the 2010s and predictions for future trends through 2030. Adapted from Grossmann and Varnum (2015).

Gender Equality: Next we turned to another marked cultural change in recent decades -- shifts in gender equality. The US has seen an increase in gender equality in the past several decades. This shift has been reflected in changes in laws and policies, greater representation of women in high-status professions and roles (including government), and shifts in social attitudes regarding gender. When we think about why our society may have become less sexist, social movements (like Women's Liberation), laws (like Title 9), landmark legal rulings (like Roe v. Wade), and medical advances like contraception all come readily to mind. Though these events all likely have played a significant role, we suspected that here too subtle shifts in our ecology might play a role in this cultural shift. Once again, we aggregated time series data concerning gender equality (e.g., male/female wage ratio, political representation, pronoun use in books and sexist work attitudes) and numerous social-ecological factors in the US and used a variety of statistical techniques to assess the strength and direction of relationships between various ecological dimensions and levels of gender equality. It turned out that a decline in levels of infectious disease was the most robust factor predictor of rising gender equality, a finding we were able to replicate in the UK, and in both societies we found evidence that changes in pathogen levels preceded shifts in gender equality (Varnum & Grossmann, 2016).

Happiness: Independently, other scholars have explored changes in levels of subjective well-being over time. Research examining affect in books and newspaper articles over a 200-year span shows a long-term decline in American happiness (Iliev, Hoover, Dehghani, & Axelrod, 2016). Levels of well-being in these studies appeared linked to Okun’s Misery Index, an economic indicator that combines unemployment and inflation rates (Iliev et al., 2016), consistent with the idea that scarcity or abundance of resources matters for happiness. Another study exploring the cause of changes in levels of well-being over time in the US found strong links to levels of economic inequality, suggesting that happiness decreases as inequality increases (Oishi, Kesebir, & Diener, 2011), suggesting that not only absolute levels of resources but their distribution in an environment (what behavioral ecologists call “resource patchiness”) help to explain changes in well-being over time.

So how can we use these findings and this emerging field to predict what our societies may look like in 2047 or 2117? We believe that an integration of current theories, and methods from cultural change research (i.e., ecological framework, big data, and econometric tools) along with insights from machine learning may enable a genuinely predictive science of cultural change. In fact, data from the studies described above may serve as a starting point for efforts to develop robust predictive models and to assess the ability of such models to predict future cultural changes. Beyond helping us to understand why cultural shifts occur in phenomena like individualism or gender equality, such an integration could help us to anticipate what our societies may look like in the future.

The emerging science of cultural change is likely to be of broad interest both inside and outside academia, appealing to behavioral scientists, policymakers, and the general public. But what if you are a social or personality psychologist and not interested in cultural change per se, why should this work matter to you?

We can think of several reasons. First, we all study samples embedded in a particular socio-cultural context. Most samples we collect are “WEIRD,” consisting largely of white American middle-class college students who it turns out are not psychologically representative of humanity (Henrich, Heine, & Norenzayan, 2010).  But perhaps more importantly emerging insights from the cross-temporal study of psychological processes suggest that as psychologists, whether we are aware of it or not, we are studying a moving target. There is no guarantee that the structure of psychological constructs (and their relationship to each other) remains consistent over time – a critical insight for anybody studying individual differences or the interaction of the social context and personality.

Second, in behavioral and management sciences that focus on cross-cultural comparisons, we need to ensure that our measurements are made contemporaneously. One widely used set of variables in cross-cultural psychology and management research comes from Hofstede’s work identifying key dimensions of cultural variation (Hofstede, Hofstede, & Minkov, 2010), yet it turns out that country-level scores in many societies were calculated from data collected decades apart! Researchers should be wary of using such indicators in the future, given what we know about cultural changes in dimensions like individualism over the past half-century.

Third, for those interested in the ways socio-cultural context impacts human minds, the new field of cultural change enables better tests of theories regarding the origin and evolution of cross-cultural variations than the cross-sectional approaches that are currently standard in the field. Time series data permit stronger inferences regarding the causes of cultural variation than is possible from datasets where putative causes and outcomes are measured only once and at the same time.

Finally, our emerging field may have some implications for debates about replicability (Greenfield, 2017; Varnum & Grossmann, 2017). This is not to say that cultural change is likely the explanation for many or most failures to replicate previous findings, but when there is a large temporal remove between the original studies and replication attempts, it may be wise to consider this when interpreting any discrepancies or changes in effect sizes.

We hope that most social and personality psychologists will be genuinely interested in integrating insights about cross-temporal change into their models of human behavior. As a field, we should not ignore the increasing availability of massive-scale data on human behavior and ecology, and the refinement of econometric and machine-learning forecasting tools. Using them wisely, we may one day move from an explanatory to a predictive psychological science (Yarkoni & Westfall, 2017).


By Igor Grossmann and Michael E. W. Varnum

 

References:

Ellis, B. J., Bianchi, J., Griskevicius, V., & Frankenhuis, W. E. (2017). Beyond risk and protective factors: An adaptation-based approach to resilience. Perspectives on Psychological Science, 12(4), 561–587. http://doi.org/10.1177/1745691617693054

Flynn, J. R. (1987). Massive IQ gains in 14 nations: What IQ tests really measure. Psychological Bulletin101(2), 171 – 191. doi: 10.1037/0033-2909.101.2.171.

Greenfield, P. M. (2017). Cultural change over time: Why replicability should not be the gold standard in psychological science. Perspectives on Psychological Science12(5), 762-771. doi: 10.1177/1745691617707314

Grossmann, I. & Varnum, M. E. W. (2015). Social structure, infectious diseases, disasters, secularism, and cultural change in America. Psychological Science, 26(3) 311-324. doi: 10.1177/0956797614563765

Henrich, J., Heine, S.J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33, 62–135. doi:10.1017/S0140525X0999152X

Hofstede, G., Hofstede, G. J., & Minkov, M. (2010). Cultures and organizations: Software of the mind (revised and expanded). New York, NY: McGraw-Hill I

liev, R., Hoover, J., Dehghani, M., & Axelrod, R. (2016). Linguistic positivity in historical texts reflects dynamic environmental and psychological factors. Proceedings of the National Academy of Sciences of the U.S.A, 113(49), 7871-7879. doi: 10.1073/pnas.1612058113

Oishi, S., Kesebir, S., & Diener, E. (2011). Income inequality and happiness. Psychological science22(9), 1095-1100. doi: 10.1177/0956797611417262

Putnam, R. D. (1995). Bowling alone: America's declining social capital. Journal of Democracy6(1), 65-78.

Putnam, R. D. (2000). Bowling alone: America’s declining social capital. In Culture and politics (pp. 223-234). Palgrave Macmillan US.

Santos, H. C., Varnum, M. E. W., Grossmann, I. (2017). Global increases in individualism. Psychological Science. doi: 10.1177/0956797617700622

Sng, O., Neuberg, S. L., Varnum, M. E., & Kenrick, D. T. (2017). The crowded life is a slow life: Population density and life history strategy. Journal of Personality and Social Psychology112(5), 736 754. doi: 10.1037/pspi0000086

Tetlock, P. E. (2006). Expert Political Judgment. How Good Is It? How Can We Know? Princeton, NJ: Princeton University Press.

Tetlock, P. E., & Gardner, D. Superforecasting: The art and science of prediction. Broadway Books.

Trahan, L. H., Stuebing, K. K., Fletcher, J. M., & Hiscock, M. (2014). The Flynn effect: A meta-analysis. Psychological Bulletin140(5), 1332 - 1360. doi: 10.1037/a0037173

Twenge, J. M., & Campbell, W. K. (2001). Age and birth cohort differences in self-esteem: A cross-temporal meta-analysis. Personality and Social Psychology Review5(4), 321-344. doi: 10.1207/S15327957PSPR0504_3

Twenge, J. M., Konrath, S., Foster, J. D., Keith Campbell, W., & Bushman, B. J. (2008). Egos inflating over time: A cross-temporal meta-analysis of the Narcissistic Personality Inventory. Journal of Personality76(4), 875-902. doi: 10.1111/j.1467-6494.2008.00507.x

Varnum, M. E. W. & Grossmann, I. (2017). Cultural change: The how and the why. Perspectives on Psychological Science. doi: 10.1177/1745691617699971

Varnum, M. E. W. & Grossmann, I. (2016). Pathogen prevalence is associated with cultural changes in gender equality. Nature Human Behaviour, 1(0006). doi:10.1038/s41562-016-0003

Yarkoni, T., & Westfall, J. A. (2017). Choosing prediction over explanation in psychology: lessons from machine learning. Perspectives on Psychological Science. doi: 10.1177/1745691617693393

Rationalizing the “Irrational”

Economists are famous for attempting to rationalize seemingly irrational behavior. One of the more extraordinary is Gary Becker and Kevin Murphy’s theory of rational addiction, in which they hypothesized that addicts plan their consumption of addictive goods. When deciding whether to smoke a cigarette or take a hit, the theory goes, addicts choose in full knowledge and consideration of the health costs and the future costs of their smoking or drug use due to addiction.

It’s tempting to claim that others’ actions are irrational; to delay such judgement involves a healthy degree of humility. After all, an external witness to a person’s actions doesn’t know what that person’s objectives are. But attempting to rationalize every behavior is also risky (as in policing and crime, for example), making it difficult to simply declare there is alignment between objectives and actions.

If we wish to assess whether someone’s actions are likely to achieve their objectives, we need an alternative way to understand what that person’s objectives are. And one place that might provide insight into these objectives is evolutionary biology.

Every person is the product of billions of years of natural selection. Without fail, every one of our ancestors managed to survive to reproductive age, find a partner to reproduce with (at least since the advent of sexual reproduction 1.2 billion years ago) and have offspring that in turn survived to reproductive age. The result is a mind and body selected to have preferences that would tend to result in survival and reproduction and the continuation of one’s evolutionary line.

Of course, evolution does not shape our preferences to explicitly seek these objectives. With few exceptions most of us don’t spend our time plotting how we can maximize our reproductive output. Rather, evolution shapes our preferences so that we seek proximate objectives that, at least in the environment they were shaped in, led to our ancestors surviving, attracting partners, and having offspring that survived.

Some of these preferences are obvious. A desire to have sex—(largely) necessary to pass on your genes, although today often thwarted by birth control. A taste for fatty and sweet foods—quite useful in a calorie-constrained environment, but not without problems in today’s abundance. A desire for relative status to attract partners—still important. A strong bond to those otherwise income- and leisure- reducing children—with the modern welfare state, not quite as critical to child survival as it once was.

When we examine objectives from an evolutionary biology perspective, we see that what appears irrational might simply be a misunderstanding on our part of what someone’s objectives are.

Some parts of economics and behavioral science indirectly tap into an understanding of the types of preferences likely to have evolved. From the economists, resources and consumption are important to survival. From the behavioral scientists, social norms reflect our need for status and the way we learn the skills we need to survive. But in many ways the surface has only been scratched.

Continue reading the post by visiting Behavioral Scientist.


Jason Collins is data science lead with Australia's corporate, markets, and financial services regulator. He specializes in economics, evolution, and behavioral science.

Does being wealthy make you more charitable?

By Ashley Whillans

Each year, the average American family donates approximately 3.4 percent of its discretionary income to charity. Most of these charitable contributions are made from October to December, known as the “giving season” in the nonprofit sector.

So what inspires individuals to donate to charity?

Given the incredible cost to solicit donations – US$1 for every $6 collected – understanding the answer to this question is critical. The recent election means the stakes are even higher.

The United States is a world leader in contributions to foreign aid. Yet, there is uncertainty about Donald Trump’s stance on such contributions. The new administration may also provide less support to social programs, such as Planned Parenthood. As a result, it may be increasingly necessary for charities to step up and raise more money to support these key policy areas.

One factor in understanding people’s decisions to donate to charity is how much money each potential donor has. Yet, the effect of wealth on charitable giving is not always clear. In recent research, two colleagues and I tried to find out what makes a person more likely open his or her wallet.

Do wealthy people give more?

It might seem obvious that wealthy individuals should be the most generous.

After all, they are in the best financial position to help those in need. It is, however, also possible that people who make the least money might be the most empathetic toward those in need because they can better understand what it is like to not have enough.

Interestingly, when looking at the data, both patterns appear to be true. Many studies show that the more money people have, and the higher in social class that people feel, the more money they donate to charity.

However, the evidence is not always consistent. Some studies fail to find a link between charitable giving and income, while other studies find that less wealthy individuals are more compassionate and that this compassion in turn predicts greater generosity.

Looking at the relationship between wealth and generosity, research suggests that lower-income households donate a greater proportion of their income to charity as compared with higher-income households – once again suggesting a complex relationship between wealth and giving.

Who’s the most generous of them all?

Given that financial generosity is possible for individuals across the socioeconomic spectrum, I along with colleagues Eugene Caruso at the University of Chicago and Elizabeth Dunn at the University of British Columbia conducted a series of experiments to find out the conditions under which both wealthy and less wealthy individuals are motivated to donate to charity.

As I noted, wealthy people should be the most generous, given their largess, but the problem for charities may be that they’re working against a behavioral bias.

Wealth – and even the feeling of being wealthy – can generate a feeling of autonomy and self-sufficiency, or what behavioral scientists call “agency” or “independence.” This feeling of agency can lead people to focus on personal goals as opposed to the needs and goals of others.

In contrast, having less wealth and the feeling of being less wealthy can generate a feeling of connection to others, what behavioral scientists call “communion.” This feeling of communion can lead people to focus on the needs and goals of others, rather than their own needs and goals.

Since charity is a fundamentally community-focused activity for the good of society, the idea that wealth may be linked to the absence of community-mindedness might create a hurdle for charities that typically emphasize the social relevance of contributing to their various causes.

‘You = Life Saver’

My colleagues and I suspected that if we tailored messages to the goals and motivations that coincide with wealth, we might be able to encourage charitable giving among those with the greatest capacity to give.

To test this question, we conducted three studies with over 1,000 Canadian and American adults. In these studies, we examined how the wording of the charitable appeals might influence giving among people with average and above average wealth.

In one study, one set of ads contained the text, “Let’s Save a Life Together. Here’s How.” Another read: “You = Life Saver. Like the sound of that?” Individuals with average and below-average levels of wealth were more likely to donate when they were shown the first type of ad. On the other hand, individuals with above-average levels of wealth were more likely to donate when they were shown the second type of ad. These effects may have occurred in part because these messages provided a better fit with each groups’ personal goals and values.

Indeed wealth would seem to be the only distinguishing factor between the two groups: There were no significant differences between age, ethnicity or gender.

Our team recently replicated these findings as part of a large annual funding campaign with 12,000+ alumni of an elite business school in the United States. In this study, wealthier individuals who read charitable appeals that focused on personal agency (vs. communion) and who made a donation to the campaign contributed an average of $150 more than individuals who read the charitable appeals that focused on communion.

Fundraising research matters

Taken together, our research suggests that by tailoring messages to fit with people’s wealth-based mindsets and motivations, it is possible to encourage charitable giving across the socioeconomic spectrum.

These findings dovetail with an emerging body of research showing that campaigns that remind donors of their identity as a previous donor provide donors with the ability to make public donations and remind donors that wealth incurs a responsibility to give back to society can also encourage charitable giving among those with the most wealth.

Fundraising solicits hundreds of billions of dollars each year, yet it is often a painstaking and costly practice. Using principles of psychological science can help charities efficiently meet their growing demands.


Ashley Whillans, Ph.D. Candidate in Social Psychology, University of British Columbia

This article was originally published on The Conversation. Read the original article.

The Case for Handgun Waiting Periods

More than 33,000 people in the United States die from gun-related injuries each year, making firearms the second leading cause of injury-related death. Many of these deaths could be avoided through policy—for example, Australia all but eliminated gun deaths through a series of gun control measures that included a massive gun buyback program, an assault weapons ban, and strict gun-trafficking policies. In the U.S., the current political climate would prohibit such dramatic changes. And yet, we believe there is still room for politically viable gun legislation that will save lives.

Our recent empirical research shows that handgun waiting periods that delay gun purchases (typically by a few days) lead to large reductions in gun violence and can provide a politically acceptable revision to U.S. gun policy.

To understand why waiting periods can have a significant impact it is helpful to consider the behavioral foundations underlying such a policy. Research from behavioral economics and psychology has found that intense emotions like anger and sadness—“visceral factors,” in academic language—can cause people to take actions they later regret, such as resorting to gun violence.

Yet research also suggests that these emotions are often transitory. Given sufficient time to cool off, the types of intense negative emotions that lead to violent tendencies can pass. This suggests that inserting even a short delay in the gun-buying process has the potential to reduce gun violence, without restricting anyone’s right to own a gun. (Delaying a gun purchase might have the additional benefit of closing the window of opportunity for would-be perpetrators of violence to harm their victims.) In a recent project, we set out to test the impact of handgun waiting periods, which impose precisely such a delay, on homicides.

Continue reading the post by visiting Behavioral Scientist.


By Michael Luca, Deepak Malhotra, and Christopher Poliquin

The ‘Great Gatsby’ Curve: Perceptions of Economic Mobility are Caused by Perceptions of Inequality

In 1931, James Truslow Adams defined the American dream as the idea that “each man and each woman shall be able to attain to the fullest stature of which they are innately capable, and be recognized by others for what they are, regardless of the fortuitous circumstances of birth or position.” At present, however, social mobility is remarkably stagnant, with one’s circumstances of birth having a large effect on later social class. Despite this fact, many people overestimate social mobility. Shai Davidai, of the New School for Social Research, suggests that beliefs about social mobility are tied directly to perceptions, or misperceptions, of the level of income inequality in society. Davidai’s research has demonstrated an inflated sense of economic mobility among Americans. Participants overestimate both an individual’s chance of upward mobility, and America’s level of societal mobility compared to those of other nations.

New work by Davidai shows that not only are perceptions of inequality negatively related to perceptions of mobility, but that perceptions of inequality may be causing perceptions of mobility. In two studies, participants who believed their state had low levels of inequality believed that both they and others had a greater ability to move from a lower social standing to a higher one; those who saw evidence of more extreme inequality thought that social mobility was far less likely.

The ‘Great Gatsby curve’ is a term coined to refer to the phenomenon of nations with higher economic inequality also having social immobility between generations. Davidai argues that this research demonstrates that people do have an intuitive grasp of this relationship - but that they underestimate levels of inequality, and thus overestimate levels of mobility.

What might be the consequences of people holding more accurate social mobility beliefs? The overestimation of mobility can lead to higher meritocracy beliefs, and a greater tolerance for inequality. Perceiving high (and accurate) levels of inequality can also lead people to make more external, and fewer internal, attributions for both wealth and poverty, versus those who believe in lower levels of inequality. This may be psychologically important for those who cannot improve their lot in life.

But accuracy may be a double-edged sword. Those who are accurate about low levels of mobility may also shift to a more present-focused mindset, which could lead to greater impulsivity and risk-taking. Davidai and Martino Ongis have found that indeed, when looking at State of the Union addresses, the use of future-focused language decreases when America’s level of inequality increases. Furthermore, when examining addresses by zip code, an increase in local inequality was related to a higher proportion of local accounts on the extramarital affair website Ashley Madison. It seems that while recognizing the difficulty of upward mobility is important, it may come at a price.


Written by: Sarah L. Williams, Wilfrid Laurier University, Waterloo, Ontario, Canada

Presentation: "Why Do Americans Overestimate Economic Mobility?" was part of the symposium Inequality, Perceived Mobility, and Economic Growth: Advances and Future Directions held Saturday, March 3, 2018.

Speaker: Shai Davidai, New School for Social Research

 

Wealth Doesn’t Always Equal Health

“Wealth equals health” has been a commonly accepted principle for decades. Beginning in 1967, the classic Whitehall studies revealed that higher-class British civil servants had lower risks of mortality from a wide range of diseases than their lower-class counterparts. Since then, much research has continued to support the idea that higher socioeconomic status (SES) means better health. And, this link between health and wealth seems like it may explain some important health disparities in the United States. For example, Black Americans, who tend to be lower SES than White Americans, live about four years less than White Americans. 

But, there is one case where wealth does not necessarily equal health among Americans, as Dr. John Ruiz discussed at the Society for Personality and Social Psychology’s Social Personality Health Pre-Conference. Hispanics tend to be lower SES than non-Hispanic Whites. Despite this, Hispanics have a lower mortality rate than non-Hispanic WhitesAs the Center for Disease Control reports, Hispanics are less likely to die from the 10 leading causes of death than non-Hispanic Whites. A recent meta-analysis of 58 studies involving over 4.6 million participants showed that Hispanics have about a 17.5% lower risk of death compared with other racial groupsThis challenges the maxim that “wealth equals health.” Hispanics, despite being lower SES than non-Hispanic Whites, have better health outcomes.

Researchers often call this the “Hispanic Mortality Paradox. What could lie behind this paradox? In his talk, Dr. Ruiz outlined several possibilities. Hispanics in the United States are less likely than Whites to engage in key risk behaviors such as smoking. But Hispanic health advantages are also present among non-smokers, suggesting that other factors must be at play. 

It could be that Hispanics are more resilient in the face of illness. Supportive of this, a recent study showed that Hispanics tend to be hospitalized 2-3 days less per person. Or Hispanics may age differently from other racial and ethnic groups. In fact, some recent research indicates that Hispanics may have a slower rate of genetic aging than non-Hispanic Whites. 

There may also be a role for culture in shaping these effects. Many values in Hispanic culture emphasize strengthening social bonds - values like simpatía (harmony in social relationships)familismo (importance of family), and respeto (respect for elders). Importantly, meta-analyses of studies show that social bonds can be as protective of health as not smoking or getting enough exercise, and Hispanic cultural values may facilitate these bondsThese, and other reasons, may all contribute to Hispanic people’s longevity in the face of adversity.

There’s one other reason why the “Hispanic Mortality Paradox” might exist. There is a growing disparity in the amount of biomedical research that is published using Hispanic participants, and very few studies that compare Whites with Hispanics. The current models of mortality risk may be miscalibrated by not including Hispanic participants. So, one way to shed light on this paradox is simply to gather more information, by encouraging researchers to include Hispanic participants in their studies. Further, since health risk may vary by Hispanic subgroup, researchers should record details about their Hispanic participants’ background.  

These studies begin the process of illuminating how and why minority groups’ health may importantly differ from one another. This research counters a single notion of “minority health” and helps to turn some common notions like “wealth equals health” on their heads.


Lauren Howe is a 6th year PhD candidate in social psychology at Stanford University and the Shaper Family Stanford Interdisciplinary Graduate Fellow. Her research interests include social acceptance and social rejection, trust in expertsand patient-physician interactions

The material is from work presented by John Ruiz during the Social Personality & Health Preconference.

 

The Psychology of Raising the Minimum Wage

By David Nussbaum

Barry Schwartz discusses the psychology of anchoring in Slate and how raising the minimum wage would affect other wages as well.

You might be suspicious that raising the anchor set by the minimum wage will not have this general effect. After all, employers are pretty savvy. They know about what the labor market has to offer. They know how much they can raise their prices without suffering. Surely these factors will influence wage-setting rather than an externally imposed anchor. If you think this, you underestimate the power of anchors. They have effects even among extremely sophisticated people.

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