Category Archives: News

AEPS Upcoming Mental Health Symposium

The Applied Evolutionary Psychology Society (AEPS) is proud to announce our upcoming Mental Health Symposium, set to take place from 1pm-4pm on Tuesday, June 4th, 2019 at the NonProfit Center in Boston, Massachusetts.

The symposium will be targeted toward mental health practitioners (clinical & counseling psychologists, mental health counselors, social workers, psychiatrists, etc.) and will focus on specific, practical ways in which the evolutionary behavioral sciences can inform day-to-day mental health practice. The keynote speaker will be Dr. Stefan Hofmann of Boston University, a clinical psychologist specializing in anxiety disorders, who will give a talk entitled “Integrating Evolutionary Science into Clinical Practice.” AEPS is currently looking into the feasibility of offering CEU credits for clinicians.

The symposium is open to all, whether or not you’re a professional clinician, so any interested parties are encouraged to come! AEPS has some funds available to subsidize student travel expenses for graduate or undergraduate students who are interested in attending the symposium. Please reach out to for more details!

2016 Darwinism Applied Winner – Dr. Kalman Glantz!

AEPS is pleased to announce our most recent winner of the Darwinism Applied Award: Dr. Kalman Glantz! Kalman studied at universities on 3 plus continents without ever hearing the name Darwin. He has been, among other things, an assistant at the National School of Political Science in Paris, a professor of social science in Cambridge, a Visiting Scientist at MIT, and is now a psychotherapist in private practice in the Boston area. He was converted to evolution on a line that began with Robert Ardrey, moved on to Richard Alexander, and ultimately to E.O.Wilson, Richard Dawkins, Robert Trivers, and the Tooby and Cosmides duo. His first publication, with John Pearce, was entitled Exiles From Eden: Psychotherapy from an Evolutionary Perspective, was the first book to incorporate modern evolutionary psychology with practice-oriented clinical psychology. Next came Staying Human In The OrganizationBeyond Diversity: A Curriculum for What All Kids Have in CommonReuniting America: Saving the Market System (From Itself), and Self-Evaluation And Psychotherapy In The Market System, these four coauthored with J. Gary Bernhard.

Applying Evolutionary Theory to Psychiatry

Our emotions are the result of hundreds of thousands of years of evolutionary pressure and have been described as “Darwinian algorithms of the mind” by evolutionary scientists John Tooby and Leda Cosmides. Though emotions have likely evolved to serve specific adaptive purposes, there are currently several psychiatric diagnoses identifying what is presumed to be ‘pathological’ emotion states such as generalized anxiety disorder (GAD) in the case of excessive anxiety, or major depressive disorder (MDD) in the case of excessive sadness or apathy.

Rather than being pathological, these emotional states could in fact be somewhat adaptive if looked at through an evolutionary lens, as physician Randolph Nesse and evolutionary biologist George Williams argue in their book, “Why We Get Sick: The New Science of Darwinian Medicine.”

Let us take the case of anxiety. Anxiety has likely evolved to keep us away from dangerous situations, and to activate cognition and behaviors to help us escape from dangerous situations we find ourselves in. Nesse and Williams mention “the berry picker who does not flee a grizzly bear” and “the fisherman who sails off alone into a winter storm” (p. 212) to illustrate examples where anxiety is crucial to our survival.

It would then seem that high, constant levels of anxiety would lead to the greatest evolutionary fitness, as individuals always aware of and ready to flee from dangerous situations would have highest rates of survival. Though for the individual it may not be pleasant to constantly experience high levels of anxiety, as Nesse and Williams eloquently and bluntly phrase it, “natural selection cares only about our fitness, not our comfort” (p. 212).

The reason why all of us do not experience high levels of anxiety constantly is explained by its biological costs. The ‘fight or flight’ response associated with anxiety is calorically expensive, which in turn allows less energy expenditure for other processes. Furthermore, a large body of work has suggested negative effects of chronic stress on the body and on the mind. Thus, though perpetual high levels of anxiety would indeed help us guard ourselves from danger, the costs of doing so may be substantial enough as to negate the potential benefits.

The levels of anxiety that have been labeled as pathological have been designated as such by mental health professionals and not by evolutionary scientists, leading to potential differences in the ways physicians and evolutionary thinkers would classify pathological emotion. Large, empirical studies have not been conducted to determine whether individuals diagnosed with GAD actually have lower fitness as compared to individuals without a diagnosis.

Interestingly, looking on the other side of the anxiety spectrum, anecdotal evidence suggests that too little anxiety may jeopardize an individual’s fitness and survival. Such individuals are often unable to accurately assess potential dangers, and more frequently end up in socially and physically undesirable situations. However, there is currently no psychiatric diagnosis for this end of the anxiety spectrum, despite it being the end of the spectrum that may be ultimately more detrimental to the individual.

Throughout their chapter on mental disorders and throughout the rest of the book, Nesse and Williams stress the potential utility of evolutionary theory across a wide range of fields in medicine (see this previous AEPS post on Nesse’s contributions to cancer biology). Before jumping to disrupt a certain natural biological process or emotional/cognitive state, it is important to remain cognizant that such processes and states have been crafted to increase our genetic fitness, and that in some cases, we may perhaps be best off letting the “Darwinian algorithms of the mind” and body run their course.

Sexual Harassment Is About Wanting Sex, Not Wanting Power Over Women

A 2012 paper in Evolution and Human Behavior by Leif Edward Ottesen Kennair and Mons Bendixen takes a much-needed evolutionary look at the issue of sexual harassment. They write in their paper:

While traditional social science theories have explained harassment as male dominance of females, the evolutionary perspective has suggested that sex differences in the desire for sex are a better explanation.

And their finding, in brief, was that an “unrestricted” sexuality “motivates people to test whether others are interested in short-term relations in ways that sometimes might be defined as harassment.”

The competing prediction suggesting that male dominance over females is the primary motivation for harassment was largely unsupported in this study. Not only was female harassment of males quite prevalent, so too was same-sex peer harassment. In addition, other competing social factors did not outweigh the importance of sociosexual orientation in explaining variations in sexual harassment for either of the sexes.
They further explain:
The main idea behind our predictions was the hypothesis that harassment is an unrestricted sociosexual style of behavior, aimed at testing out whether a potential sexual partner is available for a short-term sexual encounter, and that perceived harassment behavior to a large degree is motivated by a desire for sex. However, many instances of harassment in our study were cases of same-sex harassment. This may be understood from a similar perspective. It is an example of sexual surgency or dominance, and sexual competitiveness (Campbell, 2004). Thus, the logic of the evolved psychology of derogation (Schmitt & Buss, 1996) is relevant for understanding this behavior.
And their conclusion:
While more boys sexually harass and coerce than girls, both sexes commit sexual harassment and coercive acts. And while many different negative precursors and correlates have been suggested, it would seem that the main motive is an interest in short-term sex indicated by an unrestricted sociosexuality. This same characteristic also causes behavior that advertises an interest in sex, increasing the attraction of nonattractive partners. Furthermore, these individuals probably have an increased interest in sexual competition, thus both being subject to and partaking in same-sex derogation. Thus, an unrestricted sociosexual orientation is related to both harassing behavior and being a victim of harassment in high school.

The Mating Crisis Among Educated Women

David Buss at Edge:

Every year, more women than men become college-educated. The disparity is already prevalent across North America and Europe, and the trend is beginning to spread across the world more widely. At the University of Texas at Austin where I teach, the sex ratio is 54 percent women to 46 percent men. This imbalance may not seem large at first blush. But when you do the math it translates into a hefty 17 percent more women than men in the local mating pool. Speculations about reasons range widely. They include the gradual removal of gender discrimination barriers and women’s higher levels of conscientiousness (relative to men’s) that translate into better grades and superior college app qualifications. Whatever the causes turn out to be, the disparity is creating a dramatic and unintended mating crisis among educated women.


…Most women are unwilling to settle for men who are less educated, less intelligent, and less professionally successful than they are. The flip side is that men are less exacting on precisely these dimensions, choosing to prioritize, for better or worse, other evolved criteria such as youth and appearance. So the initial sex ratio imbalance among educated groups gets worse for high achieving women. They end up being forced to compete for the limited pool of educated men not just with their more numerous educated rivals, but also with less educated women whom men find desirable on other dimensions.


…What are the potential solutions to the mating pool shortage for educated women? Adjust their mate preferences? Expand the range of men they are willing to consider as mates? Mating psychology may not be that malleable. The same mating desires responsible for the skewed gender imbalance to begin with continue to create unfortunate obstacles to human happiness. As successful women overcome barriers in the workplace, they encounter new dilemmas in the mating market.

The Evolution of Music as Medicine: Improving Mood Regulation, Focus, and Well-Being

Psychologist Michael Hogan asks at Psychology Today, “What are the adaptive functions of music listening?” He explains:

Research has highlighted mood regulation to be the most important function of music listening, but people also listen to music for its cognitive benefits, such as increased focus and attention, the experience of cognitive complexity, to facilitate social interaction and bonding, and reinforce social identity. More recently, research has started to focus on how music promotes wellbeing, which we can think of as simply the hedonic balance of positive and negative emotions, or more broadly in terms of our life engagement, meaning, and overall psychological and social well-being. It seems that beyond hedonic well-being, the broader, so-called “eudaimonic” aspects of wellbeing become more important as we age, but we know very little about how music interacts with these aspects of wellbeing. Research does suggest, however, that music brings about not only pleasure but also absorption and transcendence in listeners, so it is worth considering how music enhances wellbeing in the fullest possible sense, drawing upon the rich collective intelligence of experienced listeners.

Referencing his research with Jenny Groarke, he writes:

While both younger and older adults emphasized the importance of music in bringing about strong emotions, these emotions had a more positive, transcendent quality for older adults, who consistently spoke about music taking them to “another world”, “a different dimension”, and “transcending the mundane”. Transcendent experiences are functionally significant and have been related to benefits such as increased happiness and meaning in life, higher life satisfaction, and reduced loneliness in older adults.  Indeed, for the older adults in our study it seems that listening to music plays an important role in easing feelings of loneliness. At the same time, while older adults spoke about using music to reduce feelings of isolation, younger adults spoke about how music allowed them to carve out a personal space where they could limit social connection. As one young woman described it, “When I’m listening to music, I can escape sort of, even though there’s people around… I can escape that stress,” (Female, 24). It seems that while younger adults may be using music to ease the stresses associated with their active social lives, older adults may listen to music to compensate for their feelings of social isolation.

Both age groups discussed using music to aid reminiscence. Analysis of the collective intelligence transcripts revealed that reminiscence is linked to personal growth and empathy for older adults, whereas for younger adults reminiscence may serve self-regulatory functions that facilitate coping with life. For example, while older adults spoke about listening to music to bring back fond memories such as “lovely memories of a particular person that may have passed on” (Female, 65), younger adults described using music to consciously remember significant others, for example when feeling homesick, and even for less adaptive reasons such as “break-up songs, just to torture yourself” (Female, 22). In relation to personal growth, older adults described music as enhancing reflection which, in turn, helped them to foster feelings of compassion for themselves and others.

Our study was the first to use Interactive Management to explore the connections between music listening and wellbeing, and consider how the functions of music listening may differ between younger and older adults. It appears that both older and younger adults believe that music has an effect on their wellbeing. A meta-analysis of the systems thinking of younger and older adults highlighted the importance of intense emotional experiences, reminiscence, and eudaimonic experiences such as meaning and transcendence in driving all other adaptive functions of music listening. These aspects of music listening function adaptively to enhance feelings of wellbeing across the lifespan, in old and young alike.

Read the full version of their paper here. And check out their site, The Adaptive Functions of Music Listening.


The Science of Sexy Backs: Women’s Evolved Lumbar Curvature Signals Ability to Handle Shift of Mass During Pregnancy

Evolutionary psychologists tell us there is an unmistakably Darwinian logic to the things we find sexually attractive. As we know, everyone alive today is the product of an unbroken line of ancestors who all succeeded in the game of survival and reproduction.

The first task a person must solve to have offspring is to find a fertile mate. Evolutionary psychology research suggests that modern humans have inherited a preference for looks that signal fertility: a low “waist-to-hip ratio,” for example — that hourglass shape that women aspire to have and men adore. Well, it turns out that a low waist-to-hip-ratio correlates with fewer complications in childbirth. And then there’s how men, more than women, are attracted by cues of youthfulness? In all likelihood, this is because fertility is sharply age-graded in women, more so than in men.

The latest kid on the block of Darwinian approaches to beauty is the unsexy term lumbature curvature. In a new paper published in Evolution and Human Behavior by David Lewis, Eric Russell, Laith Al-Shawaf and David Buss, the authors investigated which kinds of curvature of a woman’s lower back that men find most attractive. The reason? One adaptive problem uniquely faced in our bipedal species is a forward-shifted center of mass during pregnancy.

During pregnancy, if the center of mass could not somehow be moved back over the hips, our ancestral mothers would have suffered a nearly 800% increase in hip torque. One solution that women’s spines — though not men’s — evolved in order to deal with this challenge is a “wedging” in the third-to-last vertebra. That is, women’s third-to-last vertebra is shaped a bit like a wedge, with one thick end and tapering to the other, thinner end.  This makes it easier for pregnant mothers to bring the trunk’s center of mass back on top of their hips by extending their back. However, there is a delicate balance to strike — between enabling a move of center of mass during pregnancy and still retaining ordinary skeletal reinforcement.

To make a long story short, the researchers predicted that men will have evolved a preference for female backs that signal the optimal angle of lumbar curvature, which according to the orthopedic medical literature is around 45.5°. They conducted two experiments to test their hypothesis. First, they showed men images of women in profile, in which they manipulated the curvature of the lower back. (Technically, they varied the external angle formed between the buttock and thoracic spine.) The images that the men rated most attractive were those with a lower back that fit the magical 45.5 optimal degree of vertebrate wedging.

The curvature of the back, however, is not just influenced by vertebral wedging, but also by buttock mass. And in the researchers’ first study, the images varied in “buttock protrusion.” So the researchers conducted a second study in which men viewed images identical in buttock protrusion, but in only one condition was the buttock protrusion a cue to vertebral wedging. They found that men preferred women where buttock protrusion signaled optimal vertebral wedging. Men’s preference for a curved back, then, seems not to be just a by-product of a preference for buttock mass (Sir Mix-A-Lot notwithstanding), but a preference for backs that signal a specific degree of vertebrate wedging.

Here’s to the sexy backs.

Stop Counting, Start Collecting: Hormone Measurements in Evolutionary Psychology Research

In recent years, evolutionary psychologists have conducted lab-based and naturalistic studies suggesting that naturally cycling women (i.e. women who are not on hormonal contraceptives, such as the pill) experience a suite of behavioral and cognitive changes depending whether they are in the follicular, ovulatory, or luteal phase of their menstrual cycles. During ovulation, when a woman’s chance of conception is highest, she is likely to report higher levels of sexual desire, have a strong preference for masculine-looking men, and wear certain types of clothing—specifically, red clothing.

In 2013, a study conducted by psychologists Alec Beall and Jessica Tracy found that women at high conception risk (women who self-reported being on days 6-14 of the cycle) were over 3 times as likely as women at low conception risk (women who self-reported being on days 0-5 and 15-28 of the cycle) to wear red or pink shirts. Day of the cycle was determined by counting the number of days since women’s last self-reported menses.

There was just one problem—that “day of the cycle was determined by counting the number of days since women’s last self-reported menses.” This counting method is frequently employed in studies relating cycle phase to behavior because of its ease relative to collecting and assaying saliva samples for hormone concentrations. However, prior to when this study was conducted, there were several reasons to doubt its accuracy in classifying high versus low fertility days, which may make results from studies using this method suspect.

Acknowledging this flaw, evolutionary psychologists Adar Eisenbruch, Zachary Simmons, and James Roney conducted similar analyses to Beall and Tracy, but instead of using the counting method, they collected saliva samples (that were then assayed for hormone concentrations) each time women came into the lab. They then also used the counting method, and examined the concordance between the counting and hormonal methods of conception risk classification.

Using the counting method, there was no difference in the percentage of low and high conception risk women who wore red. When using the hormonal method, however, a significantly higher percent of high conception risk women wore red than did low conception risk women. So, while the use Beall and Tracy’s methods resulted in an inability to replicate their own original findings, the use hormonal methods for conception risk classification resulted in support for high conception risk women being more likely to wear red.

Perhaps more interesting, and certainly more worrisome than this central finding, was the lack of concordance between the counting and hormonal methods of classification—the two agreed in a mere 64% of cases. In other words, for more than 1/3 of the time, these two methods classified women as being in opposite conception risk categories. Further, almost half of the days identified as high conception risk by hormonal methods were classified as low conception risk by the counting method.

That the counting method can differ substantially from hormonal methods of conception risk classification challenges the reliability of some prior findings of cycle phase effects. While it is certain that using the counting method is easier, quicker, and less expensive than collecting and assaying saliva samples, it is unclear whether these advantages outweigh the findings of Eisenbruch et al.  suggesting that the counting method may be incorrect more than third of the time.

It may be that as evidence of the flaws of the counting method continues to accumulate, its use in evolutionary psychology will become increasingly harder to justify, thus opening the door for broader use of more methodologically-sound research practices.

Men’s Mate Preferences: What OkCupid Can Tell Us About Evolutionary Psychology

In 2014, approximately 10 million people used the online dating website OkCupid. While for users this means that billions of messages were exchanged and (probably) thousands of bad dates were had, for OkCupid CEO Christian Rudder, this means there’s an endless pool of data on interpersonal interactions begging to be analyzed.

In his 2014 book Dataclysm, Rudder analyzes data from OkCupid along with other social media sites (e.g. Twitter) to teach us about how we see ourselves, and how we interact with others. While many of his findings are noteworthy, he describes a phenomenon particularly relevant to the potential evolutionary mechanisms that influence mate choice.

Rudder asked men from ages 20 to 50 to rate the attractiveness of women of all ages. He then figured out the age of the women who looked best (i.e. got the highest ratings) to men who were 20, to men who were 21, and so on.

Men who were 20 rated women who were 20 as the most attractive. Men who were 21 rated women who were 20 as the most attractive. Jumping forward a bit, men who were 30 rated women who were 20 as the most attractive, as did men who were 31, as did men who were 46, as did men who were 47…

As you can see, the men in Rudder’s sample prefer more or less the same thing across all ages: women who are 20. From an evolutionary standpoint, this kind of innate preference for women of this age makes some sense: a woman’s chance of conception is highest in her early 20s, and decreases continually thereafter.

So, if we believe that some behaviors and preferences in men are driven by evolutionary mechanisms to facilitate the creation of offspring, men with preferences for women at peak fertility could potentially be more reproductively successful than men with preferences for women who are older and thus less fertile.>

Interestingly, this preference of men for women in their early 20s did not translate to actual behavior on the site. When indicating their preferences, most men said they were looking for someone around their age, and sent the most messages to women within 10 years of their own age.

This disconnect between what men say they want and who they rate as most attractive may be in part due to what women on the site want. While men rate women who are 20 as most attractive regardless of their own age, women rate men who are in their own age range as the most attractive, and indicate that they are looking for someone in that same range.

What does this mean practically? While a 40 year old man messaging many 20-year-old women on the site may get some positive responses, he is much more likely to get them from women in their 30s and 40s, and should take this into account to maximize his changes of finding love (or whatever else he may be looking for on OkCupid).

For more findings about how Twitter has influenced the way we write, which phrases are most common in White OkCupid users and least common in Asian users, and why the variability in your attractiveness rating is more important than your average rating, check out Rudder’s book, Dataclysm: Love, Sex, Race, and Identity–What Our Online Lives Tell Us about Our Offline Selves.

Hormone Measurements in Evolutionary Psychology Research, Part 2: The Prevalence of False Negatives

In a blog post a few weeks ago, I reviewed a study that highlighted the discrepancies between counting and hormonal methods in classifying women as either high or low conception risk in evolutionary psychology research. I concluded that evidence of such discrepancies may “challenge the reliability of some prior findings of cycle phase effects.”

What I mean to suggest with that sentence is not that previous findings of cycle phase effects are false positives, but rather that some null findings in unpublished studies may actually be false negatives, and/or that cycle phase effects may be stronger than currently suggested in the literature.

But why would using a messy, proxy measurement of conception risk (in this case, the counting method) result in false negative findings, or underestimates of a true effect size? Let’s use a simple thought experiment to make this a little clearer:

Say we have a population of 13 males and 13 females, and we are interested in whether there is a significant difference in height between the two sexes. We measure each individual’s height in inches, arrange them in order, and come up with these data. The pink cells represent values for females, and blue for males.

The two distributions overlap a bit, but overall, it looks like males on average are taller than females. We do an independent samples t-test on our small sample, and voila! At p<0.01, our statistical test is significant, and we can conclude that the average height for males and females differ.

Let’s say that for some reason, rather than asking individuals what their biological sex is, we’ll use a proxy measurement to determine biological sex: hair length. We decide that individuals with long hair will be classified as females, and individuals with short hair will be classified as males.

Unfortunately for us, that is a horrible way to differentiate between the biological sexes in this day and age. Plenty of females have short hair, while plenty of males have long hair (especially these days, with the popularity of man-buns reaching an all-time high).

Our data may end up looking a little more like this—our two columns, rather than being ‘female’ and ‘male,’ are ‘long hair’ and ‘short hair,’ because of how we decided to classify sex. Pink cells still reflect values for (truly) biological females, and blue for (truly) biological males.

The mean heights for these two groups still aren’t the same, but we do the same independent samples t-test that we did earlier, and our p value (p=0.12) is no longer statistically significant. This would lead us to conclude that there is no height difference between females and males; however, since we know this is not true, that conclusion would be a false negative.

In the thought experiment above, about 31% of the total sample was misclassified by sex, and this magnitude of misclassification was enough to lead us to a false negative finding. Looking at cycle phase research specifically, classification of days as being either low conception or high conception using the counting method may be incorrect up to 36% of the time when compared to more accurate, hormonal methods. While most of the women classified as high conception risk by counting methods are classified correctly and thus display a specific phenotype in behavior or preferences, mistakenly including low conception risk women (who display a different phenotype) in that group interferes with our ability to truly understand the full extent and magnitude of cycle phase effects.

Now, it has been suggested that some previously reported findings are false positives (rather than false negatives) due to something called ‘researcher degrees of freedom.’ Because the days of the menstrual cycle considered high or low conception risk days are not agreed upon, the classification schema used by a team of researchers to distinguish between phases of the menstrual cycle is in part arbitrary (see this article for a great chart showing the variability among studies in the way phases of the cycle are defined). If statistically significant cycle phase effects are not observed when using one classification schema, it could be that researchers change the days they consider to be high and low risk, and do so until the desired effect is significant.

Though this is possible, meta-analyses and examination of p-curves suggest that this is not the case, and that further inquiry on the extent and breadth of changes in behavior and cognition over the menstrual cycle is warranted.

Note: For those reading who are as interested in counting and hormonal methods of conception risk classification as I am, check out this cool recent article in Evolution and Human Behavior.

Special thanks to Adar Eisenbruch, a current evolutionary psychology graduate student, for his guidance on topics discussed in this post.