The Anatomy of Friendship in a “Digital Age”

Why is the number of friendships that we can actively maintain limited to 150? The evolutionary psychologist and anthropologist Robin Dunbar at the University of Oxford is a pioneer in the study of friendship. Over several decades, he and his colleagues have investigated the nature of friendship and social relationships in non-human primates and humans. His research papers and monographs on social networks, grooming, gossip and friendship have accumulated tens of thousands of academic citations but he may be best known in popular culture for “Dunbar’s number“, the limit to the number of people with whom an individual can maintain stable social relationships. For humans, this number is approximately 150 although there are of course variations between individuals and also across one’s lifetime. The expression “stable social relationships” is what we would call friends and family members with whom we regularly interact. Most of us may know far more people but they likely fall into a category of “acquaintances” instead of “friends”. Acquaintances, for example, are fellow students and colleagues who we occasionally meet at work, but we do not regularly invite them over to share meals or swap anecdotes as we would do with our friends.

Dunbar recently reviewed more than two decades of research on humans and non-human primates in the article “The Anatomy of Friendship” and outlines two fundamental constraints: Time and our brain. In order to maintain friendships, we have to invest time. As most of us intuitively know, friendship is subject to hierarchies. Dunbar and other researchers have been able to study these hierarchies scientifically and found remarkable consistency in the structure of the friendship hierarchy across networks and cultures. This hierarchy can be best visualized as concentric circles of friendship. The innermost core circle consists of 1-2 friends, often the romantic partner and/or the closest family member. The next circle contains approximately 5 very close friends, then progressively wider circles until we reach the maximum of about 150. The wider the circle becomes, the less time we invest in “grooming” or communicating with our friends. The social time we invest also mirrors the emotional closeness we feel. It appears that up to 40% of our social time is invested in the inner circle of our 5 closest friends, 20% to our circle of 15 friends, and progressively less. Our overall social time available to “invest’ in friendships on any given day is limited by our need to sleep and work which then limits the number of friends in each circle as well as the total number of friendships.

The Circles of Friendship – modified from R Dunbar, The Anatomy of Friendship (2018)

The second constraint which limits the number of friendships we can maintain is our cognitive capacity. According to Dunbar, there are at least two fundamental cognitive processes at play in forming friendships. First, there needs to be some basis of trust in a friendship because it represents implicit social contracts, such as a promise of future support if needed and an underlying promise of reciprocity – “If you are here for me now, I will be there for you when you need me.” For a stable friendship between two individuals, both need to be aware of how certain actions could undermine this implicit contract. For example, friends who continuously borrow my books and seem to think that they are allowed to keep them indefinitely will find that there are gradually nudged to the outer circles of friendship and eventually cross into the acquaintance territory. This is not only because I feel I am being taken advantage off and the implicit social contract is being violated but also because they do not appear to put in the mental effort to realize how much I value my books and how their unilateral “borrowing” may affect me. This brings us to “mentalizing”, the second important cognitive component that is critical for stable friendships according to Dunbar. Mentalizing refers to the ability to read or understand someone else’s state of mind. To engage in an active dialogue with friends not only requires being able to read their state of mind but also infer the state of mind of people that they are talking about. These levels of mentalizing (‘I think that you feel that she was correct in …..) appear to hit a limit around four or five. Dunbar cites the example of how at a gathering, up to four people can have an active conversation in which each person is closely following what everyone else is saying but once a fifth person joins (the fifth wheel!), the conversation is likely to split up into two conversations and that the same is true for many TV shows or plays in which scenes will rarely depict more than four characters actively participating in a conversation.

Has the digital age changed the number of friends we can have? The prior research by Dunbar and his colleagues relied on traditional means of communication between friends such as face-to-face interactions and phone calls but do these findings still apply today when social media such as Facebook and Twitter allow us to have several hundred or even thousands of “friends” and “followers”? The surprising finding is that online social networks are quite similar to traditional networks! In a study of Facebook and Twitter social media networks, Dunbar and his colleagues found that social media networks exhibit a hierarchy of friendship and numbers of friends that were extremely similar to “offline” networks. Even though it is possible to have more than a thousand “friends” on Facebook, it turns out that most of the bidirectional interactions with individuals are again concentrated in very narrow circles of approximately 5, 15 and 50 individuals. Social media make it much easier to broadcast information to a broad group of individuals but this sharing of information is very different from the “grooming” of friendships which appears to be based on reciprocity in terms of building trust and mentalizing.

There is a tendency to believe that the Internet has revolutionized all forms of human communication, a belief which falls under the rubric of “internet-centrism” (See the article “Is Internet-Centrism a Religion“) according to the social researcher Evgeny Morozov. Dunbar’s research is an important reminder that core biological and psychological principles such as the anatomy of friendship in humans have evolved over hundreds of thousands of years and will not be fundamentally upstaged by technological improvements in communication. Friendship and its traditional limits are here to stay.

Reference

Dunbar R.I.M. (2018). The Anatomy of Friendship” Trends in Cognitive Science 22(1), 32-51

 

Note: An earlier version of this article was first published on the 3Quarksdaily blog.

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Neuroprediction: Using Neuroscience to Predict Violent Criminal Behavior

Can neuroscience help identify individuals who are most prone to engage in violent criminal behavior? Will it help the legal system make decisions about sentencing, probation, parole or even court-mandated treatments? A panel of researchers lead by Dr. Russell Poldrack from Stanford University recently reviewed the current state of research and outlined the challenges that need to be addressed for “neuroprediction” to gain traction.  The use of scientific knowledge to predict violent behavior is not new. Social factors such as poverty and unemployment increase the risk for engaging in violent behavior. Twin and family studies suggest that genetic factors also significantly contribute to antisocial and violent behavior but the precise genetic mechanisms remain unclear. A substantial amount of research has focused on genetic variants of the MAOA gene (monoamine oxidase A, an enzyme involved in the metabolism of neurotransmitters). Variants of MAOA have been linked to increased violent behavior but these variants are quite common – up to 40% of the US population may express this variant! As pointed out by John Horgan in Scientific American,  it is impossible to derive meaningful predictions of individual behavior based on the presence of such common gene variants.

One fundamental problem of using social and genetic predictors of criminal violent behavior in the legal setting is the group-to-individual problem. Carrying a gene or having been exposed to poverty as a child may increase the group risk for future criminal behavior but it tells us little about an individual who is part of the group. Most people who grow up in poverty or carry the above-mentioned MAOA gene variant do not engage in criminal violent behavior. Since the legal system is concerned with an individual’s guilt and his/her likelihood to commit future violent crimes, group characteristics are of little help. This is where brain imaging may represent an advancement because it can assess individual brains. Imaging individual brains might provide much better insights into a person’s brain function and potential for violent crimes than more generic assessments of behavior or genetic risk factors.

Poldrack and colleagues cite a landmark study published in 2013 by Eyal Aharoni and colleagues in which 96 adult offenders underwent brain imaging with a mobile MRI scanner before being released from one of two New Mexico state correctional facilities. The prisoners were followed for up to four years after their release and the rate of being arrested again was monitored.

This study found that lower activity in the anterior cingulate cortex (ACC- an area of the brain involved in impulse control) was associated with a higher rate being arrested again (60% in participants with lower ACC activity, 46% in those with higher ACC activity). The sample size and rate of re-arrest was too small to see what the predictive accuracy was for violent crime re-arrests (as opposed to all re-arrests). Poldrack and colleagues lauded the study for dealing with the logistics of performing such complex brain imaging studies by using a mobile MRI scanner at the correctional facilities as well as prospectively monitoring their re-arrest rate. However, they also pointed out some limitations of the study in terms of the analysis and the need to validate the results in other groups of subjects.

Brain imaging is also fraught with the group-to-individual problem. Crude measures such as ACC activity may provide statistically significant correlations for differences between groups but do not tell us much about how any one individual is likely to behave in the future. The differences in the re-arrest rates between the high and low ACC activity groups are not that profound and it is unlikely that they would be of much use in the legal system. So is there a future for “neuroprediction” when it comes to deciding about the sentencing or parole of individuals?

Poldrack and colleagues outline some of the challenges of brain imaging for neuroprediction. One major challenge is the issue of selecting subjects. Many people may refuse to undergo brain imaging and it is quite likely that those who struggle with impulse control and discipline may be more likely to refuse brain scanning or move during the brain scanning process and thus distort the images. This could skew the results because those most likely to succumb to impulse control may never be part of the brain imaging studies. Other major challenges include using large enough and representative sample sizes, replicating studies, eliminating biases in the analyses and developing a consensus on the best analytical methods. Addressing these challenges would advance the field.

It does not appear that neuroprediction will become relevant for court cases in the near future. The points outlined by the experts remind us that we need to be cautious when interpreting brain imaging data and that solid science is required for rushing to premature speculations and hype about using brain scanners in court-rooms.

Reference

Poldrack RA et al. (2017). Predicting Violent Behavior:What Can Neuroscience Add? Trends in Cognitive Science, (in press).

Note: An earlier version of this article was first published on the 3Quarksdaily blog.

Do We Value Physical Books More Than Digital Books?

Just a few years ago, the onslaught of digital books seemed unstoppable. Sales of electronic books (E-books) were surging, people were extolling the convenience of carrying around a whole library of thousands of books on a portable digital tablet, phones or E-book readers such as the Amazon Kindle. In addition to portability, E-books allow for highlighting and annotating of key sections, searching for keywords and names of characters, even looking up unknown vocabulary with a single touch. It seemed only like a matter of time until E-books would more or less wholly replace old-fashioned physical books. But recent data seems to challenge this notion. A Pew survey released in 2016 on the reading habits of Americans shows that E-book reading may have reached a plateau in recent years and there is no evidence pointing towards the anticipated extinction of physical books.

The researchers Ozgun Atasoy and Carey Morewedge from Boston University recently conducted a study which suggests that one reason for the stifled E-book market share growth may be that consumers simply value physical goods more than digital goods. In a series of experiments, they tested how much consumers value equivalent physical and digital items such as physical photographs and digital photographs or physical books and digital books. They also asked participants in their studies questions which allowed them to infer some of the psychological motivations that would explain the differences in values.

In one experiment, a research assistant dressed up in a Paul Revere costume asked tourists visiting Old North Church in Boston whether they would like to have their photo taken with the Paul Revere impersonator and keep the photo as a souvenir of the visit. Eighty-six tourists (average age 40 years) volunteered and were informed that they would be asked to donate money to a foundation maintaining the building. The donation could be as low as $0, and the volunteers were randomly assigned to either receiving a physical photo or a digital photo. Participants in both groups received their photo within minutes of the photo being taken, either as an instant-printed photograph or an emailed digital photograph. It turned out that the participants randomly assigned to the digital photo group donated significantly less money than those in the physical photo group (median of $1 in the digital group, $3 in the physical group).

In fact, approximately half the participants in the digital group decided to donate no money. Interestingly, the researchers also asked the participants to estimate the cost of making the photo (such as the costs of the Paul Revere costume and other materials as well as paying the photographer). Both groups estimated the cost around $3 per photo, but despite this estimate, the group receiving digital photos was much less likely to donate money, suggesting that they valued their digital souvenir less.

In a different experiment, the researchers recruited volunteer subjects (100 subjects, mean age 33) online using a web-based survey in which they asked participants how much they would be willing to pay for a physical or digital copy of either a book such as Harry Potter and the Sorcerer’s Stone (print-version or the Kindle E-book version) or a movie such as The Dark Knight (DVD or the iTunes digital version). Participants were also asked how much “personal ownership” they would feel for the digital versus the corresponding physical items by completing a questionnaire scored with responses ranging from “strongly agree” to “strongly disagree” to statements such as “feel like it is mine”.  In addition to these ownership questions, they also indicated how much they thought they would enjoy the digital and physical versions.

The participants were willing to pay significantly more for the physical book and physical DVD than for the digital counterparts even though they estimated that the enjoyment of either version would be similar. It turned out that participants also felt a significantly stronger sense of personal ownership when it came to the physical items and that the extent of personal ownership correlated nicely with the amount they were willing to pay.

To assess whether a greater sense of personal ownership and control over the physical goods was a central factor in explaining the higher value, the researchers than conducted another experiment in which participants (275 undergraduate students, mean age of 20) were given a hypothetical scenario in which they were asked how much they would be willing to pay for either purchasing or renting textbooks in their digital and print formats. The researchers surmised that if ownership of a physical item was a key factor in explaining the higher value, then there should not be much of a difference between the estimated values of physical and digital textbook rentals. You do not “own” or “control” a book if you are merely renting it because you will have to give it up at the end of the rental period anyway. The data confirmed the hypothesis. For digital textbooks, participants were willing to pay the same price for a rental or a purchase (roughly $45), whereas they would pay nearly twice that for purchasing a physical textbook ($88). Renting a physical textbook was valued at around $59, much closer to the amount the participants would have paid for the digital versions.

This research study raises important new aspects for the digital economy by establishing that consumers likely value physical items higher and by also providing some insights into the underlying psychology. Sure, some of us may like physical books because of the tactile sensation of thumbing through pages or being able to elegantly display are books in a bookshelf. But the question of ownership and control is also an important point. If you purchase an E-book using the Amazon Kindle system, you cannot give it away as a present or sell it once you are done, and the rules for how to lend it to others are dictated by the Kindle platform. Even potential concerns about truly “owning” an E-book are not unfounded as became apparent during the infamous “1984” E-book scandal, when Amazon deleted purchased copies of the book – ironically George Orwell’s classic which decries Big Brother controlling information –from the E-book readers of its customers because of some copyright infringement issues. Even though the digital copies of 1984 had been purchased, Amazon still controlled access to the books.

Digital goods have made life more convenient and also bring with them collateral benefits such as environment-friendly reduction in paper consumption. However, some of the issues of control and ownership associated with digital goods need to be addressed to build more trust among consumers to gain more widespread usage.

Reference

Atasoy O and Morewedge CK. (2017). Digital Goods Are Valued Less Than Physical GoodsJournal of Consumer Research, (in press).

Note: An earlier version of this article was first published on the 3Quarksdaily blog.

Optimizing Ourselves into Oblivion

The short story “Anekdote zur Senkung der Arbeitsmoral” (“An anecdote about the lowering of work ethic”) is one of the most famous stories written by the German author Heinrich Böll. In the story, an affluent tourist encounters a poorly clad fisherman who is comfortably napping in his boat. The assiduous tourist accidentally wakes up the fisherman while taking photos of the peaceful scenery – blue sky, green sea, fisherman with an old-fashioned hat – but then goes on to engage the lounging fisherman in a conversation. The friendly chat gradually turns into a sermon in which the tourist lectures the fisherman about how much more work he could be doing, how he could haul in more fish instead of lazing about, use the profits to make strategic investments, perhaps even hire employees and buy bigger boats in a few years. To what end, the fisherman asks. So that you could peacefully doze away at the beach, enjoying the beautiful sun without any worries, responds the enthusiastic tourist.

I remembered Böll’s story which was written in the 1960s – during the post-war economic miracle years (Wirtschaftswunder) when prosperity, efficiency and growth had become the hallmarks of modern Germany – while recently reading the book “Du sollst nicht funktionieren” (“You were not meant to function”) by the German author and philosopher Ariadne von Schirach. In this book, von Schirach criticizes the contemporary obsession with Selbstoptimierung (self-optimization), a term that has been borrowed from network theory and computer science where it describes systems which continuously adapt and “learn” in order to optimize their function. Selbstoptimierung is now used in a much broader sense in German culture and refers to the desire of individuals to continuously “optimize” their bodies and lives with the help of work-out regimens, diets, self-help courses and other processes. Self-optimization is a routine learning process that we all engage in. Successful learning of a new language, for example, requires continuous feedback and improvement. However, it is the continuous self-optimization as the ultimate purpose of life, instead of merely serving as  a means to an end that worries von Schirach.

She draws on many examples from Körperkult (body-cult), a slavish worship of the body that gradually replaces sensual pleasure with the purpose of discipling the body. Regular exercise and maintaining a normal weight are key factors for maintaining health but some individuals become so focused on tracking steps and sleep duration on their actigraphs, exercising or agonizing about their diets that the initial health-related goals become lose their relevance. They strive for a certain body image and resting heart rates and to reach these goals they indulge in self-discipline to maximize physical activity and curb appetite. Such individuals rarely solicit scientific information as to the actual health benefits of their exercise and food regimens and might be surprised to learn that more exercise and more diets do not necessarily lead to more health. The American Heart Association recommends roughly 30-45 minutes of physical activity daily to reduce high blood pressure and the risk of heart attacks and stroke. Even simple and straightforward walking is sufficient to meet these goals, there is no need for two-hour gym work-outs.

Why are we becoming so obsessed with self-optimization? Unfortunately, von Schirach’s analysis degenerates into a diffuse diatribe against so many different elements of contemporary culture. Capitalist ideology, a rise in narcissism and egotism, industrialization and the growing technocracy, consumerism, fear of death, greed, monetization of our lives and social media are among some of the putative culprits that she invokes. It is quite likely that many of these factors play some role in the emerging pervasiveness of the self-optimization culture – not only in Germany. However, it may be useful to analyze some of the root causes and distinguish them from facilitators. Capitalist ideology is very conducive to a self-optimization culture. Creating beauty and fitness targets as well as laying out timelines to achieve these targets is analogous to developing corporate goals, strategies and milestones. Furthermore, many corporations profit from our obsession with self-optimization. Companies routinely market weight regimens, diets, exercise programs, beauty products and many other goods or services that generate huge profits if millions of potential consumers buy into the importance of life-long self-optimization. They can set the parameters for self-optimization – ideal body images – and we just obey. According to the German philosopher Byung-Chul Han, such a diffusion of market logic and obedience to pre-ordained parameters and milestones into our day-to-day lives results in an achievement society which ultimately leads to mental fatigue and burnout.  In the case of “working out”, it is telling that a supposedly leisure physical activity uses the expression “work”, perhaps reminding us that the mindset of work persists during the exercise period.

But why would we voluntarily accept these milestones and parameters set by others? One explanation that is not really addressed by von Schirach is that obsessive self-optimization with a focus on our body may represent a retreat from the world in which we feel disempowered. Those of us who belong to the 99% know that our voices are rarely heard or respected when it comes to most fundamental issues in society such as socioeconomic inequality, rising intolerance and other forms of discrimination or prejudice. When it comes to our bodies, we may have a sense of control and empowerment that we do not experience in our work or societal roles. Self-discipline of our body gives our life a purpose with tangible goals such as lose x pounds, exercise y hours, reduce your resting heart rate by z.

Self-optimization may be a form of Ersatzempowerment but it comes at a great cost. As we begin to retreat from more fundamental societal issues and instead focus on controlling our bodies, we also gradually begin to lose the ability to dissent and question the meaning of actions. Working-out and dieting are all about HowWhen and What – how do I lose weight, what are my goals, when am I going to achieve it. The most fundamental questions of our lives usually focus on the Why – but self-optimization obsesses so much about HowWhen and What that one rarely asks “Why am I doing this?” Yet it is the Why that gives our life meaning, and self-optimization perhaps illustrates how a purpose-driven life may lose its meaning. The fisherman prompted the tourist to think about the Why in Böll’s story and perhaps we should do the same to avoid the trap of an obsessive self-optimization culture.

Reference:

von Schirach, Ariadne. Du sollst nicht funktionieren: für eine neue Lebenskunst. Klett Cotta, 2014.

 

Note: An earlier version of this article was first published on the 3Quarksdaily blog. 

How Does Sleep Deprivation Affect the Brain?

How many hours of sleep does the average person require? The American Academy of Sleep Medicine and the Sleep Research Society recently convened an expert panel which reviewed over 5,000 scientific articles and determined that sleeping less than 7 hours in adults (ages 18-60) was associated with worsening health, such as increased obesity and diabetes, higher blood pressure as well as an increased risk of stroke and heart disease. In addition to increasing the risk for illnesses, inadequate sleep is also linked to impaired general functioning, as evidenced by suppressed immune function, deficits in attention and memory, and a higher rate of errors and accidents. Since at least one third of adults report that they sleep less than 7 hours a day (as assessed by the Centers for Disease Control and Prevention in a survey of 444,306 adults), one can legitimately refer to insufficient sleep as a major public health issue. Even though insufficient sleep and other sleep disorders have reached epidemic-like proportions affecting hundreds of millions of adults world-wide, they are not adequately diagnosed and treated when compared to medical risk factors and conditions. For example, in most industrialized countries, primary care physicians perform annual blood pressure and cholesterol level checks, but do not routinely monitor the sleep duration and quality of their patients.

One reason for this may be the complexity of assessing sleep. Checking the blood cholesterol level is quite straightforward and provides a reasonably objective value which is either below or above the recommended cholesterol thresholds. However, when it comes to sleep, matters become more complicated. The above-mentioned expert panel acknowledged that there can be significant differences in the sleep requirements of individuals. Those who suffer from illnesses or have incurred “sleep debt” may require up to 9 hours of sleep, and then there are also significant environmental and genetic factors which can help determine the sleep needs of an individual. The average healthy person may need at least seven hours of sleep but there probably groups of individuals who can function well with merely 6 hours while others may need 9 hours of sleep. Then there is also the issue of the sleep quality. Sleeping for seven hours between 10 pm and 5 am has a higher quality of sleep than sleeping between 6 am and 1 pm because the latter will be associated with many more spontaneous awakenings and interruptions as well as less slow-wave sleep (a form of “deep sleep” characterized by classical slow wave patterns on a brain EEG recording during sleep). Unlike the objective cholesterol blood test, a true assessment of sleep would require an extensive sleep questionnaire asking details about sleep history and perhaps even recording sleep with activity monitors or EEGs.

Another reason for why insufficient sleep is not treated like other risk factors such as cholesterol and blood pressure is that there aren’t any easy fixes for poor sleep and the science of how poor sleep leads to cognitive deficits, diabetes and heart disease is still very much a topic of investigation.

In the case of cholesterol, numerous studies have shown that cholesterol levels can be effectively lowered by taking a daily medication such as a statin and that this intervention clearly lowers the risk of heart attacks and stroke. Furthermore, the science of how cholesterol causes stroke and heart disease has been worked out quite well by identifying the molecular mechanisms of how cholesterol contributes to the build-up of plaque in the arteries which can then lead to heart attacks and stroke. When it comes to sleep, on the other hand, multi-faceted interventions are required to restore healthy sleep levels. Medications to help patients sleep can be used in certain circumstances for a limited time but they are not a long-term solution. Instead, improving sleep requires individualized solutions such as developing a sleep schedule of fixed bed-times, minimizing the use of digital screens in the bedroom, and avoiding caffeine, large meals, nicotine or alcohol just before bedtime. The complexity of assessing and treating insufficient sleep also makes it very difficult to prove the efficacy of interventions. Controlled clinical studies can demonstrate that a cholesterol-lowering medication reduces the risk of heart attacks by treating thousands of patients with the active medication when compared to thousands of patients who receive a placebo, but how do you test the efficacy of individualized sleep interventions in thousands of patients?

Understanding the precise mechanisms by which insufficient sleep impairs our functioning and health has therefore become a major topic of research with significant advances that have been made in the past decades. Correlative studies which link poor sleep to worse health cannot prove that it is the inadequate sleep which caused the problems, but studies in which human subjects undergo well-defined sleep deprivation for a defined number of hours coupled with EEGs, brain imaging studies and cognitive assessments are providing important insights into how poor sleep can affect brain function. The sleep researcher Matthew Walker at the University of California and his colleagues recently reviewed some of the key studies in sleep research and identified some of the major categories of brain function impairment as a consequence of sleep deprivation:

1.      Attention:

Several studies of human subjects have consistently shown that sleep deprivation leads to a significant decrease in the ability to pay attention to tasks. Some studies have kept subjects awake for 24 hours at a stretch whereas other studies merely restricted sleep to a few hours a night and monitored the performance. Importantly, one study that restricted sleep to less than 3 hours for one week was able to show that the attentiveness and performance of subjects recovered rapidly once the sleep-deprived subjects were allowed to sleep for 8 hours but it still did not return back to the levels of those without sleep deprivation. This means that the after-effects of sleep deprivation can linger for days even when we start sleeping normally.

2.      Memory:

The impairment of working memory (the temporary memory we use to make decisions and complete tasks) is another key feature of sleep deprivation. Brain imaging studies have been able to identify specific abnormalities in certain areas of the brain that are critical for the “working memory” function such as the dorsolateral prefrontal cortex and thus provide somewhat objective measures of cognitive impairment. Interestingly, placing magnetic coils around the head of sleep-deprived subjects to initiate TMS (transcranial magnetic stimulation) has been reported to help restore some of the loss of visual memory, however, Walker and colleagues note that the benefits of TMS in sleep deprivation are not always consistent and reproducible.

3.      Responding to negative stimuli

Sleep deprivation increases responses to negative stimuli such as fear. For example, when subjects who had one night of sleep deprivation were shown images of weapons, snakes or mutilations, their aversion responses were much stronger than those of control subjects. Hyper-responsiveness of the amygdala, the part of the brain which processes emotional reactions, is thought to be one major element in these exaggerated responses of sleep-deprived subjects.

Walker and colleagues note that not all changes seen in the brain imaging studies are necessarily detrimental. In fact, some of these changes may be adaptations that have evolved to help our brains cope with the stress of sleep deprivation. Even though significant progress has been made in sleep deprivation research, understanding differences between individuals in terms of how and why they respond differently to sleep deprivation, distinguishing the mechanisms of beneficial adaptations in brain function from detrimental responses and also developing new studies that study the effects of chronic sleep deprivation – one that occurs over a period of weeks and months and thus mimics real-life sleep deprivation – instead of the short-term acute sleep deprivation studies that are currently performed in the laboratory are major challenges for sleep researchers. Hopefully, advances in sleep research will lead to a better understanding of sleep health and ultimately also translate into sleep becoming an integral part of medical exams in order to address this burgeoning public health problem.

References

Watson NF, Badr MS, Belenky G, Bliwise DL, Buxton OM, Buysse D, Dinges DF, Gangwisch J, Grandner MA, Kushida C, Malhotra RK, Martin JL, Patel SR, Quan SF, Tasali E. Recommended amount of sleep for a healthy adult: a joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society. J Clin Sleep Med 2015;11(6):591–592.

Liu Y, Wheaton AG, Chapman DP, Cunningham TJ, Lu H, Croft JB. Prevalence of Healthy Sleep Duration among Adults — United States, 2014. MMWR Morb Mortal Wkly Rep 2016;65:137–141

Krause AJ, Simon EB, Mander BA, Greer SM, Saletin JM, Goldstein-Piekarski AN, Walker MP. (2017). The sleep-deprived human brain. Nature Reviews Neuroscience

 

Note: An earlier version of this article was first published on the 3Quarksdaily blog.

Dismantle the Poverty Trap by Nurturing Community Trust

Would you rather receive $100 today or wait for a year and then receive $150? The ability to delay immediate gratification for a potentially greater payout in the future is associated with greater wealth. Several studies have shown that the poor tend to opt for immediate rewards even if they are lower, whereas the wealthy are willing to wait for greater rewards. One obvious reason for this difference is the immediate need for money. If food has to be purchased and electricity or water bills have to be paid, then the instant “reward” is a matter of necessity. Wealthier people can easily delay the reward because their basic needs for food, shelter and clothing are already met.

Unfortunately, escaping from poverty often requires the ability to delay gratification for a greater payout in the future. Classic examples are the pursuit of higher education and the acquisition of specialized professional skills which can lead to better-paying jobs in the future. Attending vocational school, trade school or college paves the way for higher future wages, but one has to forego income during the educational period and even incur additional debt by taking out educational loans. Another example is of delayed gratification is to invest capital – whether it is purchasing a farming tool that increases productivity or investing in the stock market – which in turn can yield greater pay-out. However, if the poor are unable to pursue more education or make other investments that will increase their income, they remain stuck in a vicious cycle of increasing poverty.

Understanding the precise reasons for why people living in poverty often make decisions that seem short-sighted, such as foregoing more education or taking on high-interest short-term loans, is the first step to help them escape poverty. The obvious common-sense fix is to ensure that the basic needs of all citizens – food, shelter, clothing, health and personal safety – are met, so that they no longer have to use all new funds for survival. This is obviously easier in the developed world, but it is not a trivial matter considering that the USA – supposedly the richest country in the world – has an alarmingly high poverty rate. It is estimated that more than 40 million people in the US live in poverty, fearing hunger and eviction from their homes. But just taking care of these basic needs may not be enough to help citizens escape poverty. A recent research study by Jon Jachimowicz at Columbia University and his colleagues investigated “myopic” (short-sighted) decision-making of people with lower income and identified an important new factor: community trust.

The researchers first used an online questionnaire (647 participants) to assess trust and asked participants to choose between a payoff in the near future that is smaller and a larger pay-off in the distant future. They also measured community trust by asking participants to agree or disagree with statements such as “There are advantages to living in my neighborhood” or I would like my child(ren) to be raised in the neighborhood I currently live in”. They found that lower income participants were more likely to act in a short-sighted manner if they had low levels of trust in their communities. In a second online experiment, the researchers recruited roughly 100 participants from each state in the US and assessed their community trust levels. They then obtained real-world data on payday loans – a sign of very short-sighted financial decision-making because people take out cash advances at extraordinarily high interest rates that have to be paid back when they get their paycheck – for each state. They found that the average community trust for each state was related to the use of payday loans. In states with high average community trust ratings, people were less likely to take out these payday loans, and this trend remained even when the researchers took into account unemployment rates and savings rates for each state.

Even though these findings all pointed to a clear relationship between community trust and sound financial decision-making, the results did not prove that increased community trust is an underlying cause that helps improve the soundness of financial decisions. To test this relationship in a real-world setting, the researchers conducted a study in rural Bangladesh by collaborating with an international development organization based in Bangladesh. The vast majority of participants in this study were poor even by Bangladeshi standards, earning less than $1/day per household member. The researchers adapted the community trust questionnaire and the assessment of financial decision-making for the rural population, with live interviewers asking the questions and filling out the responses for the participants. After assessing community trust and the willingness to delay financial rewards for greater payouts in the future, half of the participants received a two year intervention to increase community trust. This intervention involved volunteers from the community that acted as intermediaries between the local government and the rural population, providing input into local governance and community-level decisions (for example in the distribution of social benefits and the allocation of funds for development projects).

At the end of the two year period, participants who had received the community intervention showed significant increases in their community trust levels and they also improved their financial decision-making. They were more likely to forego immediate lower financial rewards for greater future rewards when compared to the villagers who did not receive any special intervention.

By combining correlational data from the United States with an actual real-world intervention to build community trust, the researchers show how important it is to build trust when we want to help fellow humans escape the “poverty trap“. This is just an initial study with a limited group of participants and a narrow intervention that needs to be replicated in other societies and with long-term observation of the results to see how persistent the effects are. But the results should make all of us realize that just creating “jobs, jobs, jobs” is not enough. We need to invest in the infrastructures of communities and help citizens realize that they are respected members of society with a voice. Empowering individuals and ensuring their safety, dignity and human rights are necessary steps if we are serious about battling poverty.

Reference

Jachimowicz, J. M., Chafik, S., Munrat, S., Prabhu, J. C., & Weber, E. U. (2017). Community trust reduces myopic decisions of low-income individuals. Proceedings of the National Academy of Sciences, 201617395.

Note: An earlier version of this post was first published on the 3Quarksdaily blog.

ResearchBlogging.org

Jachimowicz, J., Chafik, S., Munrat, S., Prabhu, J., & Weber, E. (2017). Community trust reduces myopic decisions of low-income individuals Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1617395114

Are American Professors More Responsive to Requests Made by White Male Students?

Less than one fifth of PhD students in the United States will be able to pursue tenure track academic faculty careers once they graduate from their program. Reduced federal funding for research and dwindling support from the institutions for their tenure-track faculty are some of the major reasons for why there is such an imbalance between the large numbers of PhD graduates and the limited availability of academic positions. Upon completing the program, PhD graduates have to consider non-academic job opportunities such as in the industry, government agencies and non-profit foundations but not every doctoral program is equally well-suited to prepare their graduates for such alternate careers. It is therefore essential for prospective students to carefully assess the doctoral program they want to enroll in and the primary mentor they would work with. The best approach is to proactively contact prospective mentors, meet with them and learn about the research opportunities in their group but also discuss how completing the doctoral program would prepare them for their future careers.

students-in-library

The vast majority of professors will gladly meet a prospective graduate student and discuss research opportunities as well as long-term career options, especially if the student requesting the meeting clarifies the goal of the meeting. However, there are cases when students wait in vain for a response. Is it because their email never reached the professor because it got lost in the internet ether or a spam folder? Was the professor simply too busy to respond? A research study headed by Katherine Milkman from the University of Pennsylvania suggests that the lack of response from the professor may in part be influenced by the perceived race or gender of the student.


Milkman and her colleagues conducted a field experiment in which 6,548 professors at the leading US academic institutions (covering 89 disciplines) were contacted via email to meet with a prospective graduate student. Here is the text of the email that was sent to each professor.

Subject Line: Prospective Doctoral Student (On Campus Next

Monday)

Dear Professor [surname of professor inserted here],

I am writing you because I am a prospective doctoral student with considerable interest in your research. My plan is to apply to doctoral programs this coming Fall, and I am eager to learn as much as I can about research opportunities in the meantime.

I will be on campus next Monday, and although I know it is short notice, I was wondering if you might have 10 minutes when you would be willing to meet with me to briefly talk about your work and any possible opportunities for me to get involved in your research. Any time that would be convenient for you would be fine with me, as meeting with you is my first priority during this campus visit.

 Thank you in advance for your consideration.

Sincerely,

[Student’s full name inserted here]

As a professor who frequently receives emails from people who want to work in my laboratory, I feel that the email used in the research study was extremely well-crafted. The student only wants a brief meeting to explore potential opportunities without trying to extract any specific commitment from the professor. The email clearly states the long-term goal – applying to doctoral programs. The tone is also very polite and the student expresses willingness of the prospective student to a to the professor’s schedule. Each email was also personally addressed with the name of the contacted faculty member.

Milkman’s research team then assessed whether the willingness of the professors to respond depended on the gender or ethnicity of the prospective student.  Since this was an experiment, the emails and student names were all fictional but the researchers generated names which most readers would clearly associate with a specific gender and ethnicity.

Here is a list of the names they used:

White male names:  Brad Anderson, Steven Smith

White female names:  Meredith Roberts, Claire Smith

Black male names: Lamar Washington, Terell Jones

Black female names: Keisha Thomas, Latoya Brown

Hispanic male names: Carlos Lopez, Juan Gonzalez

Hispanic female names: Gabriella Rodriguez, Juanita Martinez

Indian male names: Raj Singh, Deepak Patel

Indian female names: Sonali Desai, Indira Shah

Chinese Male names; Chang Huang, Dong Lin

Chinese female names: Mei Chen, Ling Wong

The researchers assessed whether the professors responded (either by agreeing to meet or providing a reason for why they could not meet) at all or whether they simply ignored the email and whether the rate of response depended on the ethnicity/gender of the student.

The overall response rate of the professors ranged from about 60% to 80%, depending on the research discipline as well as the perceived ethnicity and gender of the prospective student. When the emails were signed with names suggesting a white male background of the student, professors were far less likely to ignore the email when compared to those signed with female names or names indicating an ethnic minority background. Professors in the business sciences showed the strongest discrimination in their response rates. They ignored only 18% of emails when it appeared that they had been written by a white male and ignored 38% of the emails if they were signed with names indicating a female gender or ethnic minority background. Professors in the education disciplines ignored 21% of emails with white male names versus 35% with female or minority names. The discrimination gaps in the health sciences (33% vs 43%) and life sciences (32% vs 39%) were smaller but still significant, whereas there was no statistical difference in the humanities professor response rates. Doctoral programs in the fine arts were an interesting exception where emails from apparent white male students were more likely to be ignored (26%) than those of female or minority candidates (only 10%).

The discrimination primarily occurred at the initial response stage. When professors did respond, there was no difference in terms of whether they were able to make time for the student. The researchers also noted that responsiveness discrimination in any discipline was not restricted to one gender or ethnicity. In business doctoral programs, for example, professors were most likely to ignore emails with black female names and Indian male names. Significant discrimination against white female names (when compared to white males names) predicted an increase in discrimination against other ethnic minorities. Surprisingly, the researchers found that having higher representation of female and minority faculty at an institution did not necessarily improve the responsiveness towards requests from potential female or minority students.

This carefully designed study with a large sample size of over 6,500 professors reveals the prevalence of bias against women and ethnic minorities at the top US institutions. This bias may be so entrenched and subconscious that it cannot be remedied by simply increasing the percentage of female or ethnic minority professors in academia. Instead, it is important that professors understand that they may be victims of these biases even if they do not know it. Something as simple as deleting an email from a prospective student because we think that we are too busy to respond may be indicative of an insidious gender or racial bias that we need to understand and confront. Increased awareness and introspection as well targeted measures by institutions are the important first steps to ensure that students receive the guidance and mentorship they need, independent of their gender or ethnic background.

Reference:

Milkman KL, Akinola M, Chugh D. (2015). What Happens Before? A Field Experiment Exploring How Pay and Representation Differentially Shape Bias on the Pathway Into Organizations. Journal of Applied Psychology, 100(6), 1678–1712.

Note: An earlier version of this post was first published on the 3Quarksdaily Blog.

ResearchBlogging.org

Milkman KL, Akinola M, & Chugh D (2015). What happens before? A field experiment exploring how pay and representation differentially shape bias on the pathway into organizations. The Journal of applied psychology, 100 (6), 1678-712 PMID: 25867167