Does Google know about a suicide before it happens?

According to the CDC, suicide is in the top 10 leading causes of death for people in the United States between the ages of 10 and 64. Among individuals in age groups 10-14, 15-24, and 25-34, it is the 2nd leading cause of death. In the year 2014 alone, we lost 42,772 Americans to suicide. Truthfully, this is probably somewhat of an underestimate because suicide is often miscategorized by as "unintentional injury," leading to false records.

If you are a clinical psychologist, you spend a lot of time thinking about ways to detect when a patient is entertaining thoughts that life is no longer worth living. Unfortunately, many completed suicides are unpredictable, and occur in moments where extreme hopelessness intersects with impulse and access to means. As a field there are many brilliant scientists and clinicians working on ways to identify and help individuals at this extreme of human suffering.

Among them is Dr. Christine Ma-Kellams, University of La Verne, and colleagues who were interested in understanding whether Google search trends can be used to predict suicide, and whether these trends are more effective in predicting suicide rates than our existing measures.

To answer this question, they pulled together data from several different sources. First, they found data from the CDC National Vital Statistics System on the number of completed suicides in the United States. From the U.S. Census Bureau, she collected demographic data that included information like income, population, home-ownership rates, unemployment, and percent of the population under the poverty line,  age, and racial categories. From the National Survey on Drug Use and Health, they collected nationally representative data on suicide vulnerability as reported on the existing gold-standard, clinical measures for suicide risk. Finally, from Google trends, they recorded the relative frequency of google searches for the terms "suicide," "how to suicide," "how to kill yourself," and "painless suicide" compared to the search term "weather." All of the data used in the study were from the years 2008-2009.

They found that the frequency of these Google search terms was significantly associated with the rate of completed suicides recorded by the CDC. They also found that frequency of these search terms was more predictive of suicide rates than the existing self-report measures we use to estimate suicide risk.

The Google search terms weren't perfect, though. They were less effective at accurately predicting suicide rates in states with lower incomes, higher crime rates, and a larger minority population. Also, it's important to acknowledge the limitations of this study. Even though this data was pulled from many different sources, is nationally representative, and cover two years, there is no way for us to know which direction the effect is going. We think these data mean that people are searching for "how to commit suicide" and then those same people are completing suicide, but it is just as plausible that individuals completed suicide, and then people in their community went online and searched for these terms. It is true that a single suicide in a community can inspire increases in discussions of suicide among the members of that community, but either way the problem to be solved is the same. Find a way to help people who feel like life isn't worth living, and prevent suicide. Google can help us find those people.

So, what does this mean? Google knows where you've been, where you're going, what you want, and how you want it. As it turns out, Google also knows who is thinking of committing suicide. Knowledge is power, and here power is life. Google is already implementing the use of sponsored ads for suicide hotlines that target individuals searching for terms just like the ones in this research study. But we are only at the beginning of understanding how to leverage this type of data in ways that can save lives. For example, can we target specific communities in the wake of a tragedy or disaster when suicide rates increase? Can we create sophisticated programs for online chatting for people going through a moment of hopelessness? Can we use the data to identify communities for whom more mental health resources would prevent these feelings of hopelessness? What ideas do you have about how to harness the power of the internet to reduce suicide rates?

Need Help? Know someone who does? Contact the National Suicide Prevention Lifeline
at 1-800-273-TALK (1-800-273-8255) or use the online Lifeline Crisis Chat.  You’ll be connected to a skilled, trained counselor in your area. Both are free and confidential. For more information, visit National Suicide Prevention Lifeline
Ma-Kellams, C., Or, F., Baek, J. H., & Kawachi, I. (2015). Rethinking Suicide Surveillance Google Search Data and Self-Reported Suicidality Differentially Estimate Completed Suicide Risk. Clinical Psychological Science, 2167702615593475.

Photo credit: Garrett Sears via www.unsplash.com

This is your brain on Facebook.

Social media has revolutionized the way we communicate with one another. Part of the tremendous success of social media platforms, such as Facebook, is that it enables individuals to receive rapid social feedback which is highly rewarding. There is a complex neural network in the human brain that responds to rewards. In particular, the nucleus accumbens is a structure in the brain that has repeatedly been identified as the neural structure that processes rewards that motivate human behavior such as food and money. In fact, the magnitude of activation of this brain structure when viewing photos of food will predict how much a person eats. However, there has long been a debate about whether primary biological needs such as food are motivated by the same neural networks that motivate social needs.

In order to better understand how our brain processes social rewards, a team of psychological scientists from the Freie University in Berlin, Germany conducted a study examining how the brain responds to social and monetary rewards. To do this, the team recruited 31 young adults (ages 19-31). These individuals came into the lab twice. First, they completed a questionnaire describing their regular use of Facebook, including questions about how many friends they have, how many minutes per day they spend on Facebook, and how connected they feel to Facebook. Then, participants were asked to participate in a 15 minute video interview. During this interview the participants briefly introduced themselves, then answered questions such as "Do you like living in Berlin?" and "Please pick one problem facing modern German society and briefly state your opinion on the matter." and "Please think of a creative work, such as a film, book, song or artwork. What is it and why do you like it?" The participants were told that their videos would be evaluated by 10 independent reviewers.

A few weeks later, participants returned to the lab for a brain scan, or fMRI. During this scan, the participants completed two tasks. In the first task, they played a random money game where there were three boxes on a computer screen, A, B, and C. Each box had a different value associated with it. The participant chose a box, and then were told how much money they won. The game required no skill or learning, each value was randomly assigned to a box during each trial, and the research team was only interested in the activation of reward structures in the brain when they saw how much money they won on each trial. In the other task, the participant saw series of photos of either themselves or another individual. In the task they were to indicate whether the photo was their own, or of someone else. Then a word was displayed under the photo. The participants were told that these words were used by the reviewers of their video to describe them. Some of the words were highly positive and complimentary, while others were not. In this task, the research team was interested in the activation of reward structures in the brain when they saw highly positive words about themselves.

They found that the nucleus accumbens activated both when the participant won the most money and when the participant received a positive word describing them. They also found that the magnitude of activation in response to positive social feedback predicted how much the participant used Facebook, while the magnitude of response to winning money did not. For neuroscience nerds like me, this is quite interesting because it shows that the nucleus accumbens responds differently to different types of rewards and stands is opposition to arguments that a reward is a reward is a reward.

The results of this study can be interpreted in a couple of different ways. These data definitely show that, for the average person, positive social feedback activates the neural structure that responds to reward and motivates future behavior, the nucleus accumbens. Further, the activation of this structure in response to social feedback predicted how much the participants used and were connected to Facebook. This is important because it means that any person running a business can benefit from the neural salience of social reward. In the example of Facebook, the masses show their approval by "liking" what others do. More likes = better e-reputation = happier social brain. Another interpretation of the present study's data is that some people are more sensitive to social feedback than others, that sensitivity is rooted in the functioning of the nucleus accumbens, and people who are sensitive to social feedback use Facebook more than those who are not. Either way, we as a field are learning every day, with every new study, how important the social world is to our neurobiology.

Unfortunately, this study is largely limited by issues of causality. Receiving social feedback doesn't cause Facebook use, and also the authors don't directly address comparisons between neural responses to monetary versus social rewards. Wouldn't it be fascinating if someone were to tackle the important marketing question of whether attention or money was more effective as a business strategy. For example, would the average customer prefer 10% off products or 10% more likes on everything they post on social media. This study might suggest that in this digital world, likes might be more valuable than a dollar.


Meshi, D., Morawetz, C., & Heekeren, H. R. (2013). Nucleus accumbens response to gains in reputation for the self relative to gains for others predicts social media use. Frontiers in human neuroscience, 7.

Happy tweets, healthy hearts.

Heart disease is the leading cause of death in the United States. The most prominent risk factors for heart disease are smoking, obesity, hypertension, diabetes, low income, and low education. However, psychological science has taught us that living in a social environment that is hostile and un-supportive also contributes to poor health, specifically heart disease.

In the past ten years, the social environments we interact with have grown exponentially with the introduction of social media such as Facebook and Twitter. This introduces an entirely new dimension of social interaction but also a window of opportunity for psychological science researchers. Specifically, a recent study pursued the question:

Does language on Twitter relate to heart disease mortality?

To answer this question, Johannes Eichstaedt and colleagues collected 50,000 words tweeted between 2009 and 2010 from users all across the United States. They systematically review the words for frequency, content, and the location of the user based on their user profile. Then they gathered county specific data on rates of obesity, smoking, marital status, hypertension, income, education, race, and mortality due to Athlerosclerotic Heart Disease from the CDC for the years 2009 and 2010. The data represented in the study represents 148 million county-mapped tweets across 1,347 counties, and CDC data from 88% of the United States.

They found that combining known physical and social risk factors, including income, education, smoking, diabetes, hypertension, obesity, race and marital status, accounted for about 35% of heart disease mortality within a county. However, language used on Twitter alone accounted for about 42% of heart disease mortality within a county. Combining Twitter language and known risk factors accounted for about 43% of heart disease mortality risk. This suggests that language used on Twitter is an important indicator of health outcomes. But what were these people saying on Twitter that predicted heart disease in their county?

The research team identified 3 categories of language use that specifically predicted increased risk for heart disease mortality in their county: aggression & hostility, interpersonal tension, and disengagement. Anger and hostility was a category comprised of frequent use of expletives. Interpersonal tension was a category comprised of frequent use of words such as “hate,” “jealous,” “fake,” and “drama,” not to mention some more expletives. Finally, disengagement was a category comprised of frequent use of words related to boredom and fatigue. Each of these categories was a significant predictor of increased heart disease mortality in a county.

There were also three other categories. These categories were Skilled Occupations, with words referring to attending conferences, learning, and meeting new people; Positive Experiences, using words that refer to friends, weekends, food, company, and things described as wonderful and fantastic; and finally Optimism, which reflects the use of words reflecting possibilities, achievements, father, goals, success, strength, and courage. Frequency of Twitter content in each of these 3 categories was protective against heart disease risk in counties.

But what does this mean? Saying bad words on Twitter causes you to die of heart disease? Posting angry, hostile tweets causes your neighbors to die of heart disease?

Because this research is cross-sectional, these are just correlations, not causes of heart disease. It’s possible that pre-existing heart disease causes people to be more hostile, angry and pessimistic. In that case, language patterns on social media may be an early sign of undiagnosed heart disease that is an area for future preventive science to explore. It’s also possible that engaging with the world with more anger, hostility, and pessimism causes physiological changes to the body that lead to heart disease. Since we know that stress causes heart disease, this pathway is extremely plausible. However, the people who die of heart disease tend to be older, while the people on Twitter tend to be younger. The people in this study that were tweeting expletives were not the ones dying that year, so there’s something much greater reflected in these findings than what predicts heart disease within an individual.

What these findings really suggest to me is that older people living in communities filled with people who are angry, pessimistic, bored, tired, hostile, and curse a lot, are more likely to die of heart disease. The important assumption being made here is that people behave on Twitter the way they behave in the world. In many ways this isn’t really true. But do you think a person that is mean on social media is also the type of person who honks at older drivers when they hesitate to turn right on red, or run a yellow light? I would venture to say yes. The authors suggest that the “combined psychological character of the community” is being represented by Twitter language in this study, and it has robust associations with health. 

We all live in communities, big and small. Other people matter, but more importantly, your behavior matters in the lives of other people.

Eichstaedt, J. C., Schwartz, H. A., Kern, M. L., Park, G., Labarthe, D. R., Merchant, R. M., ... & Seligman, M. E. (2015). Psychological language on twitter predicts county-level heart disease mortality. Psychological science,26(2), 159-169.

There’s an app for that?!?! How your social network influences important healthcare decisions.

There are tens of thousands of people around the world who conduct research on developing treatments for illnesses, including me. These range from publicly funded to private sector investigations, on illnesses from depression to multiple sclerosis, from behavioral interventions to surgery techniques. In the past century, we have tested countless interventions for their ability to effectively reduce symptoms, morbidity, and mortality. To do this we recruit samples of people with the illness we want to treat, randomly assign half of them to the treatment we are testing, and the others get an appropriate control (either a placebo, waitlist condition, or a competing treatment). If the treatment turns out to effectively reduce the impact of the illness on the participants, we call it an Evidence Based Practice or EBP for short.

Once we have evidence that a treatment works, we try to find ways to get it into the hands of professionals and patients in the community who could benefit from it. You’d think that everything that comes before this step would be the hard part; that once we had strong, repeated evidence that we have developed a treatment that worked, the people who are sick would embrace the treatment with open arms. Unfortunately, that’s not the case. Getting new EBPs out into the community is next to impossible in almost every field of health care, from psychology to cardiac surgery. As a result of this problem, researchers spend some of their time conducting studies that help us understand what leads patients to choose non-EBPs instead of EBPs. A great example of this is a study by Katherine Pickard and Dr. Brooke Ingersoll about what predicts use of EBPs for the treatment of autism.

Roughly 1 in 68 children have an Autism Spectrum Disorder (ASD). Since ASD affects all ethnic, racial and socioeconomic groups we thought it would be an important topic to address. Individuals with ASD often struggle with emotional, social, and communication skills. They can be resistant to change and engage in repetitive behaviors. The signs of ASD typically start during early childhood and will last through out the lifespan. The most effective treatment for the symptoms and difficulties related to ASD is behavioral intervention for between 15 to 30 hours per week, of which there are many to choose from depending on the age of the patient, community availability, and symptom severity. Children with ASD who are treated with EBPs grow up to have more friends, complete more formal education, have higher IQs, among many other positive outcomes. So, you can imagine why we are enthusiastic about getting more kids into treatment with EBPs. Pickard and Brooke were too. Specifically, they asked:

“How do social networks contribute to decisions about the use of EBPs for the treatment of Autism Spectrum Disorders?”

To answer this question, the sent a survey out to the members of the Interactive Autism Network (IAN), an online community of 43,000 families created to connect parents of children with ASD to research. They recruited 244 parents of a child with ASD. The children were about 6 years old, but ranged between 2 and 17 years of age. The parents provided demographic information and ASD symptom severity of their children. Parents then made a list of all of the people they had received advice from about their child’s care, their profession and personal role in the child’s like, listed what that advice was, and whether they followed through on it. Parents then saw a list of 54 services commonly provided among treatment programs for autism. Of these, 24 were EBPs, 24 were non-EBPs, and 6 were supplemental services. They were asked to “mark which ones you’ve heard of, and which ones you’ve used in the past 6 months.”

The research team then combed through the parent reports of their social networks to mark which members of the parents’ network were “formal ties” vs “informal ties.” Formal ties were teachers, therapists, & other intervention providers. They hypothesized that formal ties would lead to greater use of EBPs because professionals are part of scientifically integrated professional organizations, thus increasing the chances of their patients hearing about new, effective treatments. In contrast, informal ties tend to have more limited social ties, and mostly share information amongst themselves, thus decreasing the likelihood that new information will infiltrate the network.

They found that parents of children with ASD in this sample were using between 1 and 35 types of services, with an average of about 6. Parents of children with ASD also reported seeking advice from an average of 6 people in the past 6 months. The good news was that 94% of the sample were using at least one EBP, but 58% of the sample were also using at least one non-EBP. This means that more than half of the sample was spending time and money on services for their children despite there being little evidence that it would help. What’s a bit more concerning was that only 58% of parents reported that their primary intervention for their child was an EBP... The rest of the article explained how a parent’s social network determined use of EBPs to help their child.

They found that about 15% of the use of EBPs was explained by social network size and composition. Further, social network variables predict parental EBP use above income, education, and severity of the ASD symptoms in their child. Having a larger social network, or wider net cast for advice, predicted a higher likelihood of using EBPs. They also found that people reporting more formal ties in their network were more likely to use EBPs as their primary source of intervention and had more hours of EBP intervention.

The EBPs were, not surprising, being recommended by professionals such as teachers, speech-language pathologists, social workers, respite care providers, psychologists, neurologists, early intervention providers, counselors, case managers, and behavioral specialists. Non-EBPs were being recommended by parents of children with autism, the internet, friends, family, colleagues, tutors, and physical therapists. Important to keep in mind here is that not all professionals give good advice, and not all other parents with ASD will recommend non-EBPs. What is important to note is the theory behind why larger networks lead to use of more effective treatments: professionals have contact with larger groups of other professionals so new information about treatments that are effective can reach their patients.

But how do you change your social network? 

The truth is that parents of children with ASD need more help that they are getting. The most common source of advice these parents reported was family members, then teachers, then other parents. They are reaching out to the people nearby because it’s expensive and time-consuming to seek professional advice, and difficult to change your social network. Or at least it used to be. Which leads me to the title of this article, “There’s an app for that?”

Recently, a company called Maven decided to revolutionize health care access. The first thing you see on their website is, “You have ten places to be, and a waiting room isn’t one of them.” They realized that when you have a child, there are a million questions that come up regarding how to manage health-related issues for your child. So, they created an app that allows you to choose from a list of healthcare professionals including a pediatrician, nurse practitioner, nutritionist, lactation consultant, OB/GYN, a doula, psychologists, and social workers. Then you can choose an appointment time that works for you, even later that day. Then you can have a video appointment with them for consultation on your issue, from the privacy of your own phone, wherever that may be. There is flat fee per appointment that’s comparable to a common co-pay with no need for hassles with health insurance. For example, it’s $18 for a 10 minute conversation with a nurse practitioner. Easy, convenient, and inexpensive. With services like Maven, parents can easily double check the latest fads with a professional, before spending time and money on something that won’t help.

If you want to sign up, and why wouldn’t you, use the promo code SCIENCE to get $10 off your first visit, and get help that will actually help.

Before you go, one limitation of this study is that participants in this study were all part of the IAN, which is for families who are interested in contributing to and accessing the most recent innovations in treatments and resources for ASD. Therefore, this sample is likely an over-estimating use of EBPs in the community. Related to that point, the sample was also 90% white with 80% male children with ASD. ASD is twice as common in males as females, but a sample with more diversity would certainly help us understand how social networks influence decisions about health care in more communities.

Pickard, K. E., & Ingersoll, B. R. (2014). From Research Settings to Parents The Role of Parent Social Networks in the Choices Parents Make About Services for Their Child With Autism Spectrum Disorder. Clinical Psychological Science, 3(2), 256-269. doi: 10.1177/2167702614534240

What Don Draper could do with an fMRI…

Humans are terribly inaccurate at predicting their own behavior. Yet, marketing and advertising industries have historically relied upon individuals’ predictions about whether they would use select products, when, and why via focus groups and marketing surveys. 

Luckily, advances in psychological science, in this case with the use of fMRI, we have a window into how the brain responds to the world that is, in some ways, independent from our subjective report. Thus, inquiring minds were eager to test whether brain activity might be a better predictor of our behavior than our reports. For example, in 2011, Dr. Emily Falk and her colleagues published a study showing that neural activation in the medial prefrontal cortex (MPFC), an area involved in self-referential thinking, while watching advertisements for smoking cessation was a better predictor of quitting smoking than self-reports. This is pretty fascinating on the surface, but also very intuitive. People lie. If anyone appreciates that fact, it’s psychologists. We have dedicated years of research to developing ways of patterning the way people lie in order to more accurately measure psychological constructs.

There are a lot of reasons people who want to quit smoking might have inaccurate self-reports on whether they will quit smoking. First and foremost, doctors want their patients to quit smoking, so smokers tell their doctors what they want to hear. However, Dr. Falk and her colleagues conducted a follow-up study where they were interested in whether neural activation to smoking advertisements would predict the behavior of others. In other words, they asked the question:

Can neural responses to advertisements in a few people predict how effective they will be for others? 

To answer this question, the research team recruited 30 individuals (15 males) who were about 44 years old. Each of these individuals were “heavy smokers” with “strong intention to quit” smoking. Each participant then watched 16 smoking cessation advertisements during an fMRI session, where images of activation in their brain were taken. These advertisements were part of 3 different ad campaigns (campaign A, B, C) sponsored by the National Cancer Institute’s Smoking Quitline (1-800-QUIT-NOW). These were real advertisements that were aired locally in a different part of the country, and none of the participants had seen them before. After watching all of the advertisements in the fMRI, participants rated each advertisement’s effectiveness, including whether it motivated them to quit and how persuasive it was. Then, the research team collected data from the Smoking Quitline on how effective each advertisement actually was. To do this, they compared the number of calls they received during the month before each advertisement aired with the number of calls during the month after that advertisement aired.

Based upon the participants’ ratings of advertisement effectiveness, the most effective advertisement campaign was campaign B, followed closely by campaign A, and then campaign C by a larger margin. In contrast, the MPFC demonstrated the greatest activation when watching campaign C, followed closely by campaign B, and then campaign A. So, the brain and self-report are telling us something different, and Dr. Falk’s previous paper suggests that the neural activation in this region would more likely predict who will actually quit smoking. So, which was correct?

Based upon the change in calls to the Quitline before and after each advertisement aired, campaign C was by far the most effective. Campaign C resulted in a 32-fold increase in call volume to the Smoking Quitline, while campaign B resulted in a 12-fold increase, and campaign A only resulted in a 3-fold increase. This effectiveness ranking between campaigns (C > B > A) matches that predicted by neural activation in the MPFC.

Many companies spend millions of dollars creating, filming, and airing advertisements, especially for big events such as the Superbowl (This was my favorite Superbowl XLIX commercial, by the way: #likeagirl). These millions of dollars are intended to be an investment in the even larger revenue generated by the advertisement. Based on this article, the time may be quickly approaching when experimental approaches using fMRI may extend into the private sector, helping advertising agencies determine which campaigns will give them the most bang for their buck.

Obviously, this study was very specific to a target audience where self-reports are perhaps more susceptible to bias than consumer products like which dish soap you buy. It remains to be seen whether neural activity to an advertisement in a group of random individuals in the community, including smokers who have no intention to quit and non-smokers, would return the same results. Given that the brain region with the predictive value (MPFC) is associated with self-referential thinking, I would expect that this finding is limited only to sub-groups of individuals for whom the ad is relevant. However, that’s not too different from marketing focus groups; they use housewives for focus groups on laundry detergent and athletes for focus groups on high-performance running shoes. To truly compare, they would need to conduct this study again comparing the predictions of focus groups on ad effectiveness with the predictions based on neural activity.

Even so, this team of creative researchers still have strong evidence that what a person’s brain is doing in Los Angeles when watching a new advertisement will predict whether a person in Louisiana will call a hotline after seeing the same advertisement. And that, my friends, is very cool.

Falk, E. B., Berkman, E. T., & Lieberman, M. D. (2012). From neural responses to population behavior neural focus group predicts population-level media effects. Psychological science, 23(5), 439-445.

Schizophrenia & the Heritability of Mental Illness

In the past decade, genetics have burst our approach to mental illness wide open, and some of these major findings have trickled into main stream media distilled into the doom-and-gloom prophecy that serious mental illness is “genetic” and therefore may not be able to be prevented or treated in many people. The purpose of this week’s article is to clarify some of the “it’s all in your genes” lore. Remember that one of the cornerstone principles of SFW is that most science journalism is NOT written by scientists, and therefore may misinterpret much of what was actually done by the research team.

Don’t get me wrong, genetics are fascinating, and the brilliant minds that have been shaping this field in mental illness are nothing short of remarkable. However, they will also be the first to tell you that genes are not the only answer to how individuals develop mental illness, because even if genes make up most of the story, there is a process by which genes can be “turned on and off” by the environment through a process called methylation. Essentially, most of us are comprised of genes to live in the environment our parents lived in, but also built to only use these genes as necessary given that environments change over time and humans travel through different environments frequently. Using some now famous studies of identical and fraternal twins, we determined that mental illness is “heritable,” or the product of genes. What we are learning more recently, individuals are not inheriting illness from their parents through one gene, but rather several that need to be “turned on” together. 

This week, I will briefly review a recent study published in the American Journal of Psychiatry by Javier Arnedo and his colleagues in the Department of Computer Science and the Department of Psychiatry and Genetics at Washington University. The article was sent to me by one of my favorite people, now a medical student at Tufts University and U.S. Navy Medical Service Corps Officer, Julia Jacobs.

The article is about the genetics of Schizophrenia, which is a serious mental illness that occurs in about 1% of the population. Based on twin studies, Schizophrenia is considered highly heritable or “genetic.” Briefly, individuals with Schizophrenia typically first experience flat affect (limited facial expressions, monotonous tone of voice), and loss of interest or pleasure in activities and social interactions. These are referred to as negative symptoms and can be confused with depression. Individuals with Schizophrenia also experience what we refer to as positive symptoms, including disorganized thoughts and speech, hallucinations, and paranoia. A common misconception about people with Schizophrenia is that they are dangerous, however the incidence of violence among people with this illness is low, and among those who may be dangerous the violence is self-directed as 10% of people with this illness commit suicide. For more on what we currently know about Schizophrenia, check out this page organized by the NIMH (http://www.nimh.nih.gov/health/topics/schizophrenia/index.shtml). Schizophrenia has also been made familiar and accessible to mass audiences through such films as Out of Darkness, A Beautiful Mind, and The Soloist. 

What I learned in this article from the outset was that while Schizophrenia is 81% heritable, only 25% of variability is explained by specific genetic variants according to traditional methods used in genetic studies. So where is the rest coming from? And why such a big gap? 

Arnedo and colleagues, in this study, tried better characterize what we call Schizophrenia and the genetic markers that may lead to the illness.

To do this, they used genetic information gathered from the blood of 4,196 cases and 3,827 controls from the Molecular Genetics of Schizophrenia study. Among these participants, they identified patterns of genetic polymorphisms (SNPs) that cluster within individuals (without regard for whether they have Schizophrenia or not). This resulted in 723 clusters. Then, they calculated the “risk” for having Schizophrenia from each of these clusters, and identified 42 genetic polymorphism clusters that were associated with a 70% or greater increase in risk for having Schizophrenia. They then re-tested the association between these genetic polymorphism clusters and risk for Schizophrenia in two other studies of Schizophrenia with more than 1000 more people.

The research team then identified distinct clinical features (phenotypes) of the individuals in the MGS study that account for different presenting symptoms of Schizophrenia (primarily positive symptoms versus primarily negative symptoms), different trajectories of the illness (people who became very ill very quickly, versus those whose onset was more slowly progressing). Once they identified clinical features that were distinct, they calculated the association between each of their genetic polymorphism clusters and these clinical features. They found that some genetic clusters were associated with their clinical features. Again, they re-tested their findings in two additional large samples.

The result of this highly complex and tedious work was 8 genotype-phenotype relationships and concluded that what we call Schizophrenia today may actually be several distinct clinical syndromes with different genotypic networks. By identifying these genetic polymorphism clusters, the research team was able to account for 90% of the clinical cases, which is much improved from the 25% accounted for by past approaches. Unfortunately, this creates a problem for anyone who studies Schizophrenia, given that it is already challenging to study a phenomenon that occurs in 1% of the population, but now those subgroups are likely even smaller. Alas, we would not be scientists if we didn’t want to conquer the seemingly impossible. 

So, if you’re still with me, you may be wondering why I found this to be relevant to SFW readers. when only 1% of the population has this illness. To me, this article speaks volumes about genetics and mental illness outside of Schizophrenia. There seems to be a lore out there in the public forum that if something is “genetic” then there is a single gene for that single ailment. This study is evidence to me that genetics are far too complex to be distilled into such a misconception. There is no “Schizophrenia gene,” instead, there are clusters of genes that when present together predict important features of each disorder. In the case of this article, there may be clusters if genetic predictors of “hallucinations” and a different set of genetic predictors of “disorganized speech.”

I know a few young people who have faced incredible obstacles in their short lives so far. In some cases, there was a parent with a mental illness who started a hurricane of difficulties for these people, one wave of which was the belief that “this will be me one day,” as though it were unavoidable and inevitable. That’s really only helpful if you are going to actively seek prevention, but inevitability tends to lead people to believe that prevention is futile. Research on genetics and mental illness is one of the best examples of how science is grossly misrepresented by journalists and then the public through social media. Ultimately, it’s the responsibility of scientists who often don’t communicate clearly enough.

Furthermore, I would be remiss as a clinical psychologist if I didn’t mention that this article also speaks to common stereotypes about mental illness. Schizophrenia has many faces and usually won’t look like Russell Crowe in A Beautiful Mind. This goes for many different forms of mental illness. Don’t dismiss a person’s suffering because it doesn’t always look the same. The best, and most far-reaching example I can give of this, is the mood difficulties common to depression. Sometimes depression can look like sadness and isolation, other times it can look more like irritability and anger, but both cases indicate equal human suffering. The homeless person outside your neighborhood park may be unusual, but they are still a human being who seeks to be understood.

Arnedo, J., Svrakic, D. M., del Val, C., Romero-Zaliz, R., Hernández-Cuervo, H., Fanous, A. H., ... & Molecular Genetics of Schizophrenia Consortium. (2014). Uncovering the hidden risk architecture of the schizophrenias: Confirmation in three independent genome-wide association studies.

In memory of a hero, a visionary, and a leader: Our grandpa.

It is with immense sadness that I write this in the wake of the passing of my grandfather, Dr. James Theodore Johnson, Jr. at the age of 90. While I knew my grandfather as a man with a sweet tooth who loved golf and the Denver Broncos, he was many things before I entered his life. Of historical importance, he was the navigator on a B24 Liberator for the US Air Force during WWII and was on the 2nd plane to land in Japan after the signing of the Peace Treaty. Of local importance, he was also the superintendent of Bonita Unified School District in Southern California for 17 years. Between these two lines in his obituary, he earned a Ph.D. in Education from Columbia University. In fact, he helped conduct an innovative study in the Denver Public Schools on how to incorporate television into helping elementary school children learn in the classroom. This project was known as the Denver-Stanford Project. In an effort to pay my respects to him as a scientist and innovator in the 1960s, I will share with you the design and results of some of this research.

Something I learned from the beginning of the articles was that in 1963, when these papers were published, there was a great deal of controversy in the field of education about whether parents should help their children with their schoolwork. In fact, the consensus among leaders in education research insisted that parents helping their children with their schoolwork did more harm than good; given that parents are not trained in child development or how to explain new concepts clearly enough, parent help would lead to the child becoming more confused. 

From what I could find, he co-authored 4 papers on this project. Their primary research question was: 

Can television help parents help their children learn?

They chose to test this question in the Denver Public Schools in foreign language classes for 5th graders, specifically learning Spanish. They recruited 6,500 children with the help of the PTA, and assigned their classrooms to be in one of 4 conditions for one academic year: 

1) The parent help condition (experimental) where children saw the instructional videos in class, again at home, and then completed in-home activities with their parents. 
2) Instructional videos in school with 15 minutes of teacher instructed activities following
3) Instructional videos in school and once again in the evening
4) The control condition with Spanish instructional videos in school with no additional teacher or home

After accounting for each student’s grades for the previous academic year, current GPA, IQ, spelling and language ability scores on a standardized achievement test, they looked at which group showed better performance on listening comprehension and speaking in Spanish at the end of one semester and at the end of the year. 

Their findings were simple. The children who learned the most Spanish at the end of the 1st semester were those with only classroom instruction. Without question, the group with parent help demonstrated superior ability in Spanish in speaking and listening compared with all groups without parent help by the end of the academic year. In addition, parents reported an increased interest and agency in participating in their child’s schoolwork in all subjects which may have contributed to their child’s benefit. Important to keep in mind here though is that the study allowed for very clearly defined activities between the parent and the child to facilitate learning, which likely helped the parents immensely. 

We’ve come a long way since 1963, television instruction is used commonly in many subject areas. Certainly more people would agree that children benefit from their parents’ help with schoolwork, even if those benefits are outside of the actual homework content (e.g., time, attention, support, encouragement). That being said, I don’t remember receiving instructional videos in school or homework videos being sent home for that matter. Instead, television in my classrooms were used to show us documentaries about historical events on rainy days. It appears that as television has become ubiquitous in school, our use of this technology in an evidence-based, systematic manner has diminished. 

As is the case with all research, there are limitations to this finding. In particular, Dr. Hayman and my grandfather chose Spanish as the subject area because very few parents would have any prior training or knowledge of Spanish at the time, thus would be learning with their child rather than confounding their learning. Thus, parent help in other subjects where different families would have varying knowledge in the subject (e.g, math, literature) area may produce different results. Another hiccup that arose in the study was that after the first semester, they changed some of the conditions of the study so that the students in the control condition, no additional instruction were dividing among the other groups. This is common in studies conducted in actual schools, because all children in the public school are entitled to an equal education, and by the end of the 1st semester there was objective data suggesting that these children were falling behind. 

Another interesting detail of this study was that the classrooms were assigned to their conditions based upon their teacher’s Spanish speaking ability, or inability, as the case may be. Thus, students in classes with a teacher who speaks Spanish may have had an advantage in this domain from the outset, compared with children placed in the parent help condition because their teacher did not know Spanish. However, Spanish speaking teachers were less common in the 1960s, so there were not enough teachers with proficiency in Spanish, and in any case there were no differences in Spanish speaking or listening scores at the end of the semesters to suggest that having Spanish instruction by a Spanish speaking teacher was advantageous. 

We are all many things throughout our lives. Here’s to the brilliant minds who shaped how we teach our children, who then went on to be extraordinary grandparents. 

In loving memory of James Theodore Johnson, Jr. 

October 1, 1924 - January 7, 2015

For more on Dr. Johnson’s life, see his obituary: 

http://obits.ocregister.com/obituaries/orangecounty/obituary.aspx?n=james-theodore-johnson&pid=173800233

Hayman, J. L., & Johnson, J. T. (1963). Parents help educate their children through instructional television. The Journal of Experimental Educational, 175-180.

Additional Papers: 

Hayman, J. L., & Johnson, J. T. (1963). Exact vs. varied repetition in educational television. Educational Technology Research and Development,11(4), 96-103.

Barcus, D., Hayman, J. L., & Johnson, J. T. (1963). Programing instruction in elementary Spanish. Phi Delta Kappan, 269-272.

Andrade, M., Hayman, J. L., & Johnson, J. T. (1963). Measurement of listening comprehension in elementary-school Spanish instruction. The Elementary School Journal, 84-93.

Can we use TV to prevent depression?

I was recently in Miami for the annual meeting for the International Society for Traumatic Stress Studies (www.istss.org) where the theme of the meeting was “Healing Lives and Communities: Addressing the Effects of Childhood Trauma Across the Lifespan.” There was an interdisciplinary panel at the meeting on “Using media to prevent trauma” between scientists and filmmakers. The goal of this panel was to open a dialogue within the scientific community about whether trauma is too prevalent to treat individually, and whether population based “interventions” are a more effective way to prevent the negative psychological consequences of trauma. Are we using a teaspoon to remove water from our punctured lifeboat? During this discussion, they brought up The San Francisco Mood Survey Project, which is uber-cool, so I was inclined to share it with you.

In the late 1970s, mental health awareness was increasing, and epidemiological surveys confirmed that almost 10% of people are depressed*, while 25% of people will be depressed at some point in their life. Even then, it is remarkable to note, there was an understanding among research-oriented clinical psychologists that cognitive-behavioral therapy (CBT) was the most effective way to treat depression. More about that in this past post.

Dr. Ricardo Muñoz of University of California- San Francisco is a psychologist specializing in effective interventions for the treatment of depression. Today, he focuses mostly on interventions using the internet, however in 1978, the best option for community intervention was television. Luckily, the host of a television news program in San Francisco approached him and a group of psychologists at UCSF and UC Berkeley to develop a mini-series on depression. So, the research group compiled active components of effective CBT for depression and compiled them into ten 4-minute segments that were aired during the noon, evening, and nightly news for two weeks. This is considered “primary prevention” because “rather than waiting for people to become depressed enough to seek therapy, preventive educational interventions can be made available to the general public.”

One week before airing the 10 segments, they conducted a phone survey by asking 216 individuals (~ 40 years) about their symptoms of depression and whether they engage in any of the behaviors that would (unbeknownst to them) be recommended on the television segments.

Some examples of the content of these segments are: making a list of 15 pleasant activities, writing out a contract to exercise and eat healthy, showing ways people can reward themselves for following the contract, listing positive thoughts, and showing how to relax.

One week after the 10th segment was aired, they conducted phone interviews with 220 individuals (58 were new). Participants reported on their depression symptoms, how often they engage in the behaviors recommended in the segments, and whether they watched any of the segments on the news in the past 2 weeks.

Unfortunately, only 47 of the participating individuals watched at least one of the segments of the intervention, however the results of the intervention were promising. Individuals whose pre- intervention depression scores were high (clinically significant) who also watched at least one segment, reported a decrease in depression symptoms one week after the intervention. This is an important finding because one of the biggest criticisms of community interventions like these, and more recently on the internet, is the worry that people who are depressed will stop seeking treatment and be at increased risk for persistent illness or suicide. See a past article about depression and suicide risk here. So not only did Muñoz and colleagues find that depression symptoms declined in people who watched the segments, but specifically in those with clinically significant symptoms.

Overall, I find it remarkable that this was done 30 years ago, but disappointing that more programs like this have not “taken off.” Clearly, there are benefits, but apparently the benefits don’t outweigh the costs. This study is no exception given how much time and money it must have taken to compose and produce the 10 segments, to only reach ~20% of a population. But perhaps we should be interested in long term gains, not 2 week gains. In graduate school, I learned about a concept called Gross National Happiness, was proposed by the King of Bhutan, as a way of dedicating national resources to promoting quality of life rather than productivity (GNP) per se.

What is also remarkable to me about this study was whether it was prevention or intervention. Keep in mind, the main finding was that people with clinically significant symptoms showed reductions. This implies that the segments were therapeutic, or served as an intervention. However, for some historical context, the first segment was aired the day after the Guyana mass suicide, not to mention the Mayor of San Francisco Moscone and Supervisor Harvey Milk were shot one week later. Thus, it is possible that the intervention somehow buffered the impact of these major socio-political traumas as evidenced by a lack of increasing symptoms.

This brings me back to my original topic, which is the question of whether we can prevent the negative impacts of trauma using media. And if we can, what might that look like? I often take my training as a clinical psychologist for granted, and forget that everyone is not trauma-informed. What clinical psychologists know about trauma is that telling your story with others is part of the healing process, as long as those others are “safe.” We know that when someone tells us about a personal experience, either rape or assault or a motor vehicle accident, that is privileged information that was very difficult to share. As receivers of that information, we are responsible for showing gratitude for that information, and validating them by recognizing the overwhelming emotions that must have accompanied their experience. The media does not routinely do that. Only the rarest journalists do that. As a result, we live in a world where emotions are stigmatized, shame is marketed, destitution is disgusting, and victims of trauma are never validated unless they can afford to pay for it. I wonder what the world would look like if instead everyone was “safe.”

*Depression is defined by two weeks of persisting low or negative mood and loss of pleasure in previously enjoyed activities which are then accompanied by several other unpleasant experiences (changes in sleep, appetite, worry, thoughts about death). If you are worried that you might be suffering from depression, you should take an online survey here, or contact your primary care physician for a referral to a therapist.

Muñoz, R. F., Glish, M., Soo-Hoo, T., & Robertson, J. (1982). The San Francisco mood survey project: Preliminary work toward the prevention of depression. American Journal of Community Psychology, 10(3), 317-329.

Does Brain training “work”?

In clinical psychology, brain training has applications for children with ADHD by training working memory and attention, in TBI patients who are working to regain cognitive functioning, and for elderly populations who are experiencing aging and disease related declines in processing speed and memory. Lately, these brain training programs have even been marketed to the general public, and several friends have asked me whether “brain training” programs actually work. Cautiously, I have responded to them by asking what they mean by “work,” as the very delineation of something that either “works” or “doesn’t work” is too simple when it comes to the human brain.

In psychology research, how these programs “work” is divided into near transfer and far transfer. Near transfer is when a brain training program makes you better at the specific skill you are training. For example, does training yourself to shift attention between different topics, images, or tasks, make you better at shifting your attention between different topics, images, or tasks. Far transfer is when a brain training program makes you better at the skill you are training as well as skills that are related to the skill you are training. For example, does practicing retaining information in your short-term memory help you improve your reading comprehension?

When transfer occurs, either near or far, there is scientific value in understanding how that transfer impacts the brain. For example, if attention training demonstrates far transfer to a skill like reading, is there a change in the communication between different parts of the brain? Or do certain regions of the brain work less when completing specific tasks.

So far, there is clear evidence that near transfer occurs. Practicing one cognitive skill will relate to improved performance on tests of that skill in the future. Far transfer, on the other hand, is harder to demonstrate and isn’t as reliable. Thus, there has been little opportunity to evaluate the far transfer related changes that occur in the brain or explain how far transfer works.

Luckily, Dr. Maren Strenziok of George Mason University and her colleagues were interested in answering the question:

Does cognitive training transfer relate to changes in brain connectivity?

To address this question, they recruited 42 healthy adults with an average age of 69 years to participate in a brain training study. All of these participants completed an fMRI brain scan to assess brain functioning and the strength of connectivity between different structures within the brain. These participants also complete a series of psychological tests to measure performance in memory and reasoning.  Then, each participant was randomly assigned to one of three brain training games on the computer. These games were “Rise of Nations,” “Brain Fitness,” and “Space Fortress.”

“Rise of Nations” is a real-time strategy computer game. At the beginning of this game, the participant was assigned a nation and the object of the game is to increase that nation’s territory. This game has been previously shown to engage skills such as working memory, reasoning, task-switching, and visuo-spatial processing. “Brain Fitness” is an auditory perception game where participants were expected to match, detect, and discriminate sounds of high and low volume and tone, and follow complex instructions. “Space Fortress” is a complex game requiring the participant to navigate and destroy a space fortress which likely engaged attention shifting, inhibition, rule-learning, and hand-eye coordination. After the participants were assigned to their game, they participated in a learning paradigm in order to familiarize themselves with how to play the game. Participants were then asked to play their game for one-hour each day for 6 weeks. At the end of these 6 weeks, the participants returned to the laboratory to participate in a post-training scan of their brain as well as complete psychological tests aimed at measuring any changes in their memory or reasoning ability.

They found that “Rise of Nations” was associated with increases in mathematical reasoning, decreases in working memory, and no change in speed of cognitive performance. Participants who were assigned to “Brain Fitness” demonstrated no changes in working memory, and improvement in mathematical reasoning, and an increase in speed of cognitive performance. Finally, participants who were assigned to “Space Fortress” demonstrated increases in working memory ability, a decrease in mathematical reasoning, and an increase in speed of cognitive performance.

But do these changes in performance relate to changes in the way the brain works?

The short answer appears to be yes. Participants who were assigned to train in the Brain Fitness game demonstrated decreases in connectivity between the inferior temporal lobe (ITL) and the superior parietal cortex (SPC) compared with participants in the “Rise of Nations” group. The inferior temporal lobe is the part of the brain associated with visual processing, while the superior parietal cortex is the part of the brain associated with spatial reasoning and sensorimotor functioning. This suggests that training in auditory perception decreases the connectivity between these two structures in the brain, and results in faster performance on cognitive tasks, aka increased efficiency. This was also true when comparing “Space Fortress” to “Rise of Nations”. In comparison, “Rise of Nations” resulted in increased connectivity between the ITL and the SPC.

So, what does it all mean? From this study, it appears that games like “Rise of Nations” which create a sort of artificial world and involve developing strategies to advance within that world have some cognitive benefits but do not result in far transfer, or cognitive benefits that extend to skills outside of the game. Furthermore, playing this game may result in increased need for connectivity between structures within the brain in order to achieve the same results. In comparison, “Brain Fitness” and “Space Fortress” both demonstrated cognitive benefits outside of the skills engaged while playing the game, and also resulted in more efficient cognitive processing after only 6 weeks.

Obviously, one should consider the limitations of this study before using its results to justify buying Lumosity or dropping out of school to do Brain Metrix. This was a small study, of older adult participants, and far transfer was measured using psychological tests after a brief training, with no long-term follow-up. It would be enormously interesting to see whether these cognitive benefits remained months later. The utility of these results for the average adult who works, lives, and plans for the future is more compelling. Wouldn’t it be nice if we could be 3 lattes sharp at all times, read quickly, focus our attention exactly when we want to, and figure out how to solve problems on a dime. And wouldn’t it be nice if we could all play videogames for hours in order to achieve those goals? I imagine that the average person who asks me about whether these programs “work” is interested in these outcomes. This study shows us that practicing one skill repeatedly over time has near transfer and results in that skill improving. So, if you’re interested in something that “works” for one problem area in your life, then practicing that skill over-and-over-and-over will give you more bang for your buck. If you’re more interested in improving general cognitive functioning, there may be something to these programs that help you hone in on specific core domains of cognition such as working memory, attention shifting, and auditory perception. These domains of cognitive functioning influence many cognitive abilities and you’re likely to notice gains after as little as 6 weeks of daily practice.

Strenziok, M., Parasuraman, R., Clarke, E., Cisler, D. S., Thompson, J. C., & Greenwood, P. M. (2014). Neurocognitive enhancement in older adults: comparison of three cognitive training tasks to test a hypothesis of training transfer in brain connectivity. NeuroImage, 85, 1027-1039.

Why should you use technology to enhance your workouts?

Last week, I reviewed an article characterizing depression across different age groups (click here to catch up). This week, I thought it only appropriate to follow-up with some hope. While depression can have what seems like an insurmountable negative impact on a life, there are many effective habits that can prevent the onset of depression, mitigate the symptoms, and even treat the illness directly. One in particular that has had moderate effectiveness in all three of these areas is physical activity.

Physical activity acts on the psychological as well as the neurobiological underpinnings of depression. Psychologically, engaging in physical exercise has the potential to increase self-esteem as well as directly reduce anxiety and improve mood. Neurobiologically, depression is linked to a deficit of serotonin in the brain, and regular physical exercise increases serotonin. In fact, some studies have found that 30-minutes of aerobic exercise daily for 12 weeks can be as effective in treating depression as medications or traditional therapy; not to mention cost effective.

The problem is that these studies have mostly been conducted under strict research conditions with monetary incentives, which don't necessarily map onto the reality of life very well. Other studies have tried to simply prescribe physical activity to depressed individuals, only to find that very few people stick with the recommended level of activity, and many even drop-out altogether. The point is, depression is characterized by low motivation, so depressed patients can't be expected to be motivated to exercise even if it will help them. It's kind of like telling a deaf person to attend a symphony.

Furthermore, the physical activity of children and teenagers is much different from that of adults. Adults go to sterile gyms and run in place on a machine or repetitively lift heavy pieces of metal every which way until they can't lift anymore. That couldn't be more boring to a child, and even most teenagers. They want to be outside, with other kids their own age, and doing exercise that more closely resembles play than torture. Thus, getting a teenager to comply with a regular, prescribed regimen pf physical exercise is  next to impossible without a personal trainer breathing down their necks.

Luckily, innovations over the past decade have brought us products that help monitor and motivate physical activity, like FitBit for walking, Strava for cycling, and now Trace for surfing, skiing and skateboarding. All of these products include a social component where your friends will  notice if you've become inactive lately, and you can compare yourself with others to increase your motivation.

What we know from a hundred years of social psychology is that a person running on a treadmill beside another person will run longer and faster than a person running on a treadmill alone. Given this, I can't help but wonder how this new generation of social networking junkies could be better serving our mental and physical health, especially for young populations who still need to have fun while they exercise.

This is a tough predicament. Children who get depression stay sick longer, get sick repeatedly across their lives, and go on to have serious substance abuse problems; while depressed teenagers are at high risk for attempting suicide. The incidence of these negative consequences could be reduced by regular physical activity, but kids find typical aerobic workouts monotonous, boring, and stupid.

So how do you build a depressed teenager's motivation to be active? 

That's why I am so excited about devices like Trace  and the future of sports. Trace was developed by a young team of creative surfers who put their math and design skills to the test. They were tired of hearing on Facebook about their friend who just ran 6 miles, when they couldn't share about the 2 hours they just spent in the ocean. How many waves did they catch? How fast did they go? How high did they jump? Now there's Trace, where users can motivate each other to be more active in fun activities like surfing, skiing/snowboarding, and skateboarding by sharing information about their activity with one another while also building their self-esteem in a chosen skill and improving their mood. Now if you're the parent of even a moody teenager, you'll know how valuable a good mood and self-esteem can be; but if your child needs more motivation to get active maybe this is what you've been waiting for. Learn more about how to pre-order Trace here. 

How is Facebook influencing your behavior?

We have all heard the phrase, “It’s not what you know, but who you know.” My late mentor and friend, Chris Peterson lived by the words, “Other people matter.” Jackie Robinson chose to have, “A life is not important except in the impact it has on others lives,” written on his tombstone. In the intriguing, and highly addictive, Netflix original series House of Cards, Francis (Kevin Spacey) wisely states that, “Generosity is its own form of power.” Each of these idioms highlight the unique value of social currency among human beings, who are the only mammals who spend most of their time with non-kin.

Last week, I had the honor of giving a talk at the Anxiety and Depression Association of America’s (ADAA) annual meeting in La Jolla, Ca. The keynote was given by Dr. James Fowler, a professor at University of California-San Diego. Dr. Fowler studies social networks, or how humans influence one another. For example, he discussed longitudinal evidence that obesity in the United States truly is an epidemic such that if one person is obese, their friends have a higher likelihood of being obese, as do their friends’ friends. He remarked that this finding was picked up by major news outlets in Europe and the US with very different messages. In Europe, the headlines read, “Are you making your friends fat?” while in the states the headlines read, “Are your friends making you fat?” Ironically, the subtle difference emphasizes the ever-present layer of cultural context on all of these social dynamics.

The experiment I want to share today was one in which many of you were likely participants. If you were one of the 61-million people who had a Facebook account and logged in on the day of the US congressional election in 2010, then you contributed to the research I’m about to share. Thank you for your participation! Basically, Dr. Fowler conducted a randomized intervention to test whether the behavior of your friends influences your voting behavior. To do this, he rigged Facebook so that 1/3 of everyone who logged on that day saw a banner at the top of their news feed that looked like the picture above. It included a reminder that today was election day, a button for you to click to share with the world that you voted, and then a row of photographs of your friends who had also clicked the “I Voted” button. Another 1/3 of participants saw almost the same advertisement on their news feed; however there were no photographs of their friends. The final 1/3 saw their regular, old news feed with no Election Day banner at all. Their question was:

If you think your friends voted, are you more likely to vote?

No surprises, the people who saw the photos of their friends were 2% more likely to click the “I Voted” button than those who saw the other Election Day banner. Now, 2% sounds like a small effect, but across 61 million people that is 400,000 voters. To put that into context, 537 votes meant the difference in the entire presidential election in 2000. Be that as it may, I know what you’re thinking: “Anyone can lie on Facebook and say they voted, but does this translate to real voting behavior?” Good question. The short answer is yes.

Most people don’t realize, but whether or not you vote is a matter of public record. So, they dug into the records and looked at whether seeing photos of your friends resulted in more actual voting. We all know that voter turnout increases when swarms of college students go door to door on behalf of their campaign, but can that be replicated on the internet? Until the present study, we thought the answer was no because efforts to get people out to vote via email has been ineffective. In this study, they found that people who saw the election information on the their news feed (without photos of their friends) were no more likely to vote than people who saw nothing at all, but the people who saw the election message with photos of their “voting” friends were 0.4% more likely to actually vote. Thus, see photos of their friends who voted actually caused almost 60,000 people to vote in the congressional election.

But wait, there’s more. They also looked at how influential specific people were in their effect on true voting behavior. In short, the effect of seeing photos of your friends on your voting behavior was stronger if those friends were your close friends (e.g., tagged in photos together, write on each others’ walls) rather than people you knew in high school but don’t really interact with much. In fact, that influence exerts a sort of contagion effect throughout your friendships, and your friends’ friends.

It goes without saying that a 0.4% increase in voting isn’t a huge impact unless you are reaching millions of people like in this study. Nonetheless, this finding introduces some interesting questions. First, in what other small ways are the things we are passively viewing and clicking influencing our behaviors and the behaviors of those around us? At the very least, this finding reminds us that even though we live in a world where “everyone should mind their own business,” we are actually doing quite the opposite. This study suggests that we are all influencing one another, so an increased awareness of how may help us live in a society more consistent with what we want. This is obvious to most people about the “real” world, while the internet started as a place where people could behave anonymously and thus social behavior was not influential in the same ways. By now, all that has changed. What you do on the internet, or even what you seem to be doing on the internet, reaches a large audience; click wisely.

If you’re interested in reading more about social epidemics, Dr. Fowler and his colleague, Dr. Christakis published a popular psychology book on the topic which you can purchase here.

Bond, R. M., Fariss, C. J., Jones, J. J., Kramer, A. D., Marlow, C., Settle, J. E., & Fowler, J. H. (2012). A 61-million-person experiment in social influence and political mobilization. Nature, 489(7415), 295-298.

Modern Family

I was born and raised in Southern California and my entire family pretty much still lives there. As they would argue, “Why would anyone leave?” Being the too-independent-for-my-own-good, citizen-of-the-world type of girl, I left and have not lived in California for almost a decade. Unfortunately, this means that I have skirted my familial responsibilities merely due to geographic location. So I have missed many birthdays, rides to the airport, sick days, emergency pet-sitting, and broken down cars. As an 18-year-old, these are not the things you think you will miss when you leave your family, but they are the things that matter most.

But today the world is remarkable, and coincidentally, today my big brother has food poisoning. If I lived near him (San Francisco), I would have stopped by after work to check on him; bring him ginger ale, saltine crackers, and chicken noodle soup. As I talked with him on gchat about how awful he was feeling, it made me sad that I was thousands of miles away and could do nothing for him but recommend that he immediately begin binge-watching the Netflix original series, House of Cards. Then I wondered whether they have grocery delivery services in San Francisco, like they do in New York City. I tried Safeway, created an account in my brother’s name, and even filled up my shopping cart with the necessary get well ingredients. Unfortunately, upon check out I learned that you need to order by 8:30am in order to get same day delivery. Now, if I was up and accomplishing tasks by 8:30am, ordering groceries online would not be one of them. I was back to square one. But then, I found a website called Task Rabbit (https://www.taskrabbit.com/).

Today we live in a world where you can outsource anything: editing your dissertation, the design for your company logo, organizing your passwords to websites. Task Rabbit is a website where you can outsource tasks to people in the community. Within minutes I had an account, within seconds I had posted my request for groceries to be delivered to my brother, and within hours a lovely woman named Anne M. was calling to ask whether he would prefer salted or unsalted crackers for his soup. Needless to say, my brother was grateful for the reinforcements and, not to mention, impressed by my resourcefulness. Today is remarkable because a girl in Ann Arbor can send soup to her brother in San Francisco on a whim when he’s sick. Today is remarkable because there are communities of strangers sitting on their computers waiting to go out and do good on behalf of other strangers.