The Syrian slaughter. North Korea nuclear warheads. ISIS attacks. School shootings. Social media-fed teen depression. Thugs victimizing people of color and women. Inequality increasing. Online privacy invaded. Climate change accelerating. Democracy flagging as autocrats control Turkey, Hungary, China, and Russia, and as big money, voter suppression, and Russian influence undermine American elections. U.S. violent crime and illegal immigration soaring.   For news junkies, it’s depressing. We know that bad news predominates: If it bleeds, it leads. But we can nevertheless take heart from underreported encouraging trends. Consider, for example, the supposed increases in crime and illegal immigration.   Is it true, as President Trump has said, that “crime is rising” and in inner cities “is at levels that nobody has seen”? Seven in 10 Americans appeared to agree, when reporting to Gallup in each recent year that violent crime was higher than in the previous year. Actually, crime data aggregated by the FBI (shown below) reveals that violent (and property) crime have dramatically fallen since the early 1990s. And is the U.S. being flooded with immigrants across its Mexican border—“evil, illegal immigrants who commit violent crimes,” as a 2018 DonaldJTrump.com campaign ad declared? In reality, the influx has subsided to a point where, Politifact confirms, “more illegal Mexican immigrants are leaving the United States than entering it.” (Should we build a wall to keep them in?)   But what about immigrant crime—fact or fiction? “Americans are five times more likely to say immigrants make the [crime] situation worse rather than better (45% to 9%, respectively),” reports Gallup. Not so. Multiple studies find that, as the National Academy of Sciences reports, “immigrants are less likely than the native-born to commit crimes” and are underrepresented in American prisons.   For more good news, consider other heartening long-term trends: World hunger is retreating. Child labor is less common. Literacy is increasing. Wars are becoming less frequent. Explicit racial prejudice (as in opposition to interracial marriage) has plummeted. Gay, lesbian, and transgender folks are becoming more accepted. Infant mortality is rarer and life expectancy is increasing. Such trends are amply documented in Steven Pinker’s recent books, The Better Angels of Our Nature and Enlightenment Now, and in Johan Norber’s Progress, and Gregg Easterbrooks, It’s Better Than It Looks. As President Obama observed, if you had to choose when to live, “you’d choose now.”   Yes, in some ways, these are dark times. But these are also the times of committed Parkland teens. Mobilized citizens. Machine learning. Immune therapies. #MeToo. #BlackLivesMatter. Low inflation. Near full employment. Digital streaming. Smart cars. Wearable technologies. Year-round fresh fruit. And Post-It notes.   To paraphrase Charles Dickens, it is the worst of times, it is the best of times. It is an age of foolishness, it is an age of wisdom. It is a season of darkness, it is a season of light. It is the winter of despair, it is the spring of hope. ... View more

My colleague, Lindsay Root Luna, has new data showing that virtues correlate. People’s scores intercorrelate on scales assessing humility, justice, wisdom, forgiveness, gratitude, hope, and patience. Show her a forgiving person and she will likely show you a humble, grateful person.   Root Luna’s observations triggered my thinking about other human dispositions that come bundled. First, there are the anti-virtues.   As the concept of ethnocentricism conveys, prejudices often coexist: anti-gay, anti-immigrant, anti-Black, anti-Muslim, and anti-women sentiments often live inside the same epidermis. People intuitively know this. Thus, as Diana Sanchez and colleagues have observed, White women often feel threatened by someone who displays racism, and men of color by sexism.   Likewise, people’s tendencies on the “dark triad”—narcissism, Machiavellianism, and psychopathy—are “substantially intercorrelated.” Show Peter Muris and colleagues a narcissist (perhaps your least favorite politician?), and they’ll show you a likely Machiavellian and amoral person.   On the brighter side, some good things, in addition to the virtues, also tend to come wrapped in the same skin. Charles Spearman recognized this long ago with the concept of general intelligence (g). Those who score high in one cognitive domain have some tendency to score higher than average in other areas such as reasoning or spatial ability, or even perceptual speed.   Athleticism offers another example of packaged gifts. The ability to run fast is distinct from muscular strength or the eye-hand coordination involved in the precise pitching of a ball. Yet there remains some tendency for athletic excellence in one domain to correlate with that in another. Good tennis players may also be better than average basketball players.   Surely this does not exhaust the list. Can you think of other examples of correlated good things and bad things? ... View more

Credit President Trump with consistency in cultivating public fears of immigrants: “When Mexico sends its people . . . they’re bringing drugs. They’re bringing crime. They’re rapists.” (2015) A January, 2018 DonaldJTrump.com ad offered images of an illegal-immigrant murderer while a narrator referred to “evil, illegal immigrants who commit violent crimes,” noting that “Democrats who stand in our way will be complicit in every murder committed by illegal immigrants.” “If we don’t get rid of these loopholes where killers are allowed to come into our country and continue to kill … if we don’t change it, let’s have a shutdown,” Trump said two weeks later.   Horrific rare incidents feed the narrative, as in Trump’s oft retold story of the Mexican national who killed a young woman in San Francisco (with a ricocheted bullet), or in his February 6th tweet about the unauthorized immigrant drunk driver who killed a Baltimore Colts linebacker.   The effect of this rhetoric and these publicized incidents appears in a recent Gallup survey: “On the issue of crime, Americans are five times more likely to say immigrants make the situation worse rather than better (45% to 9%, respectively).” Are they (and the President) right?   With 11 million unauthorized immigrants in the U.S., there will, of course, be ample opportunities to illustrate both immigrant horrors and heroism. Mindful that emotionally compelling stories can illustrate larger truths or deceive us, I searched for data that would answer this question: Are the President’s words illustrating a painful fact that justifies anti-immigrant views, or are they fear mongering demagoguery? Here’s what I found (drawn from my contribution to an upcoming social psychology symposium on human gullibility): Immigrants who are poor and less educated may fit our image of criminals. Yet studies find that, compared with native-born Americans, immigrants commit less violent crime (Butcher & Piehl, 2007; Riley, 2015). “Immigrants are less likely than the native-born to commit crimes,” confirms a National Academy of Sciences report (2015). After analyzing incarceration rates, the conservative Cato Institute (2017) confirmed that “immigrants are less likely to be incarcerated than natives relative to their shares of the population. Even illegal immigrants are less likely to be incarcerated than native-born Americans.” Noncitizens are reportedly 7 percent of the U.S. population and 6 percent of state and federal prisoners (KFF, 2018; Rizzo, 2018). Moreover, as the number of unauthorized immigrants has tripled since 1990 (Krogstad et al., 2017), the U.S. crime rate plummeted.   Alas, when pitted against memorable anecdotes, data—which are merely the sum of all anecdotes—often lose. The availability heuristic—the human tendency to estimate the commonality of an event based on its mental availability (often influenced by its vividness) frequently hijacks human judgments. When data on immigrant arrest or prison population proportions are set against this 2.5 minute excerpt from the 2018 State of the Union address—highlighting the teary parents of two daughters reportedly murdered by a gang with illegal immigrant members—which will people more likely remember?   Moreover, social psychologists Leaf Van Boven and Paul Slovic recently noted that the White House has also promoted its immigrants-as-killers thesis with misleading statistics. “Nearly 3 in 4 individuals convicted of terrorism-related charges are foreign-born,” the President tweeted last month. But that statement, and the administration report on which it was based, were “deeply misleading” the psychologists explain, for two reasons. First, the report excluded domestic terrorists, whom Americans fear most, and was inflated with tenuously relevant terrorism-related activities such as perjury and petty theft. Second, the scary-sounding statistic exploited people’s statistical illiteracy. Consider, they say, that 3 in 4 NBA players are African-American. Even so, “a vanishingly small” percentage of African-American men—less than 0.01 percent—play in the NBA. Thus, knowing only that a man is African-American, the chances are 99.99+ percent that he is not an NBA player. And knowing only that someone has been born outside the U.S., you can be similarly confident that the person is not a terrorist, or a killer. Donald Trump’s fear mongering and repeated misrepresentation of truth has me thinking again of George Orwell’s Nineteen Eighty-Four—a world where repeated falsehoods come to be believed: “Freedom is slavery.” “Ignorance is strength.” “War is peace.” I do wonder: When Trump proclaims these falsehoods, does he know they are untrue, or does he believe what he proclaims?   Pope Francis offered a possible answer, quoting Dostoevsky’s The Brothers Karamazov: “People who lie to themselves and listen to their own lie come to such a pass that they cannot distinguish the truth within them, or around them, and so lose all respect for themselves and for others.”   ... View more

Over lunch recently, a friend told about taking a firearm course, which enabled her to carry a concealed pistol and thus, she presumed, to live at less risk of harm.   Isn’t it obvious: If more of us have guns, and if gun-toting criminals therefore fear our having a gun, then they will be less likely to rob or attack us? The NRA likes to remind us that “the only thing that stops a bad guy with a gun is a good guy with a gun.”   But two new Science reports indicate quite the opposite.   It’s no secret, as Stanford researchers Philip Cook and John Donohue report, that some 36,000 Americans a year die of gunshot, and that the U.S. gun suicide rate is eight times that of other high-income countries, and the gun-murder rate is 25 times higher. More newsworthy is their reporting an “emerging consensus,” using sophisticated statistical analyses, that right-to-carry laws “substantially increase violent crime.”   For example, from 1977 to 2014, U.S. violent crime rates fell by 4.3 percent in states that adopted right-to-carry laws, but by a whopping 42.3 percent in states that did not adopt such laws. In tense situations, from car accidents to barroom and domestic arguments, guns enable deadly responses. Anecdotes of private guns deterring violence are offset by many more incidents of innocent deaths.   In the second report, economists Phillip Levine and Robin McKnight studied firearm sales after the Sandy Hook Elementary School massacre of 20 children and six adults. They associated a spike in firearm sales after the massacre with a corresponding spike in firearm deaths—in the very places where firearm sales had significantly increased. “We find that an additional 60 deaths overall, including 20 children, resulted from unintentional shootings in the aftermath of Sandy Hook.”   These new findings confirm what other evidence tells us: Guns purchased for safety make us less safe. ... View more

I recently finished Sam Kean’s (2012),  The Violinist’s Thumb the history, the present, and the future of DNA research. Kean writes, “Genes don’t deal in certainties; they deal in probabilities.” I love that – and I’m using it the first day of Intro Psych next term: “Psychology doesn’t deal in certainties; it deals in probabilities.” I already talk about correlations as probabilities. The stronger the correlation, the higher the probability that if you know one variable, you can predict the other variable. In the learning chapter, it’s not unusual for a student to say, “I was spanked, and I turned out okay.” Now I can repeat, “psychology doesn’t deal in certainties; it deals in probabilities.” When children are spanked, it increases the probability of future behavioral problems (Gershoff, Sattler, & Ansari, 2017). It is not a certainty. Whenever aggression comes up as a topic, a student will say, “I play first-person-shooter games, and I’ve never killed anybody.” Again, “psychology doesn’t deal in certainties; it deals in probabilities.” Playing violent video games increases the chances of being aggressive. Watching violent movies increases the chances of being aggressive. Listening to violent-themed music increases the chances of being aggressive. (List is not exhaustive.) The more of those factors that are present, the greater the probability of behaving aggressively (Anderson, C, Berkowitz, L, Donnerstein, E, Huesmann, L, Johnson, J, Linz, D, Malamuth, N, & Wartella, 2003). It is not a certainty. A student says, “I was deprived of oxygen when I was being born, and I haven’t developed schizophrenia” (McNeil, Cantor-Graae, & Ismail, 2000). (Okay, I have never had a student say this, but I wanted one more example.) Being deprived of oxygen at birth increases the probability of developing schizophrenia. It is not a certainty. Any time a student reports an experience that does not match what most in a research study experienced, I can say “Like genetics, psychology doesn’t deal in certainties; it deals in probabilities.”   References Anderson, C, Berkowitz, L, Donnerstein, E, Huesmann, L, Johnson, J, Linz, D, Malamuth, N, & Wartella, E. (2003). The influence of media violence on youth: . Psychological Science In The Public Interest (Wiley-Blackwell), 4(3), 81–110. https://doi.org/10.1111/j.1529-1006.2003.pspi_1433.x Gershoff, E. T., Sattler, K. M. P., & Ansari, A. (2017). Strengthening Causal Estimates for Links Between Spanking and Children’s Externalizing Behavior Problems. Psychological Science, 95679761772981. https://doi.org/10.1177/0956797617729816 Kean, S. (2012). The Violinist’s Thumb. New York City: Little, Brown, and Company. McNeil, T. F., Cantor-Graae, E., & Ismail, B. (2000). Obstetric complications and congenital malformation in schizophrenia. In Brain Research Reviews (Vol. 31, pp. 166–178). https://doi.org/10.1016/S0165-0173(99)00034-X ... View more

One of psychology’s most reliable phenomena is “the overconfidence phenomenon”—the tendency, when making judgments and forecasts, to be more confident than correct. Stockbrokers market their advice regarding which stocks will likely rise while other stock brokers give opposite advice (with a stock’s current price being the balance point between them). But in the long run, as economist Burton Malkiel has repeatedly demonstrated, essentially none of them beat the efficient marketplace.   Or consider psychologist Philip Tetlock’s collection of more than 27,000 expert predictions of world events, such as the future of South Africa or whether Quebec would separate from Canada. As Nathan DeWall and I explain in Psychology, 12 th Edition, His repeated finding: These predictions, which experts made with 80 percent confidence on average, were right less than 40 percent of the time. Nevertheless, even those who erred maintained their confidence by noting they were “almost right.” “The Québécois separatists almost won the secessionist referendum.”   My fellow Worth Publishers text author and Nobel laureate economist, Paul Krugman, has described similar overconfidence and reluctance to admit error among economists and politicians. When Bill Clinton raised taxes on the rich, conservative politicians and economists predicted economic disaster—but the economy instead boomed, with 23 million jobs added during the Clinton years. When Kansas politicians passed large tax cuts with the promise that growth would pay for them, the result was an unexpected state funding crisis. When, in 2008, the Federal Reserve responded to the recession by cutting interest rates to zero, conservative economists and pundits published an open letter warning of soaring inflation to come. But it hasn’t.   When none of the predicted economic outcomes happened, did the forecasters own their error and change their thinking? Contacted by Bloomberg, not one of the inflation open letter signatories acknowledged error. Instead, they offered (in Krugman’s words) “some reason wrong was right … and never, ever, an admission that maybe something was wrong with [their] initial analysis.” Overconfidence—the human bias that our own Nobel laureate, Daniel Kahneman, would most like to eliminate—feeds another potent phenomenon, “belief perseverance”—our tendency to cling to our beliefs in the face of contrary evidence. The more we explain why our beliefs might be true, the more they persist. Thus we welcome belief-supportive evidence—about climate change, same-sex marriage, or the effects of today’s proposed tax cuts—while discounting contrary evidence. To believe is to see.   Perhaps, then, we should all aspire to a greater spirit of humility. Such recognizes, as I have written elsewhere, that We are finite and fallible. We have dignity but not deity. [Thus] we should hold our own untested beliefs tentatively, assess others ’ ideas with open-minded skepticism, and when appropriate, use observation and experimentation to winnow error from truth. ... View more

“It’s official: Dog owners live longer, healthier lives” reads the headline on Time’s website. The refreshing change is that the headline – and the article – carefully explain that the data are correlational, not causal (MacMillan, 2017). When this article appeared in my local paper, The Seattle Times, it came with a sub-headline: “It may be correlation, not causation, but the risk of death was about 33 percent lower for dog-owners than non-owners, a study found.” You won’t be surprised to hear that the journalist, Amanda MacMillan, has a BA in journalism/science writing with minors in “science, technology, and society” and physics [shout out to Lehigh University, her alma mater.] Researchers looked at national records for 3.4 million people in Sweden over a 12-year span. Those records included whether the people registered a dog and their health reports. “Dog ownership registries are mandatory in Sweden, and every visit to a hospital is recorded in a national database.” Researchers learned that “[p]eople who lived alone with a dog had a 33% reduced risk of death [over that 12-year span], and an 11% reduced risk of cardiovascular disease, than people who lived alone without a dog.” The findings were less pronounced for people who lived with other people, I’m going to put this study into my correlation lecture. After sharing these results, I’ll ask students to work in pairs to generate possible reasons for these relationships and then share their ideas with the class. This is a nice opportunity to show that while correlations do not tell us about cause and effect, they provide a goldmine of hypotheses for future research. One possibility, the article points out, is that owning a dog causes better health in the owner: owning a dog causes people to be more active (“gotta walk the dog”). Or dogs may share their microbiome with their owners, giving their human immune systems a boost – as I reflect on how I woke this morning with my dachshund standing on my head and licking my face. Or by walking our dogs, we meet people, extending our social network; social networks are also correlated with better health. Another possibility, the article also points out, is that more active (read “healthy) people are more likely to get a dog. And then there are the third variables. For example, “[o]ther studies have suggested that growing up with a dog in the house can decrease allergies and asthma in children.” It may be that having a dog growing up made people more likely to get a dog as an adult and that the exposure to dogs as children gave us a stronger adult immune system. As instructors of psychological science, let’s continue to help our students understand what research does and does not tell us, so that when they get jobs as journalists, they can accurately interpret research findings for the general public as this journalist has done.   References MacMillan, A. (2017, November). It’s official: Dog owners live longer, healthier lives. Retrieved from http://time.com/5028171/health-benefits-owning-dog/ ... View more

Here are some survey data your students may find interesting. This will be most compelling for your psychology majors. The American Psychological Association (APA) mined the data from the 2015 National Survey of College Graduates (NSCG) and learned some interesting things about psychology’s bachelor’s degree recipients (American Psychological Association, 2017). The NSCG estimates that there are about 58 million people in the United States with a bachelor’s degree; that probably includes you. The NSCG sampled 135,000 of them in 2015 (National Science Foundation, 2017).    After covering survey research in, say, Research Methods, ask students to work in groups to take a few minutes and think of what variables they would include in such a survey and why. Ask each group, in turn, for one variable that no other group has yet mentioned. Write the variables on the board (or computer screen) as groups report out. Keep rotating through the groups until all variables have been reported or as time allows. Next, share with students this list of key variables (scroll to 2.h.) included in the NSCG survey. Ask students if there are any groups they would exclude from the survey. The NCSG excludes people who are institutionalized, who live outside the U.S., and who are 76 years old or older (scroll to 3.b). Ask students what kind of sampling design they would use. The NCSG used stratified sampling on “demographic group” (with “an oversample of young graduates), “highest degree type,” and “occupation/bachelor’s degree field” (scroll to 3.c.). Researchers started with a web survey. For those who didn’t respond to that, researchers sent them a survey in the mail. And for those who didn’t respond to that, they got a phone call for “computer-assisted telephone interviewing” (scroll to 4.a.). What did APA find in that 2015 survey data about those of us with bachelor’s degrees in psychology (American Psychological Association, 2017)? 4 million people in the U.S. have at least a bachelor’s degree in psychology 2% got a master’s degree in psychology 8% got a master’s degree in psychology first and then went on to complete a doctorate/professional degree in psychology 3% got a master’s degree in something else and then a doctorate/professional degree in psychology 7% directly earned a doctorate/professional degree in psychology, bypassing the master’s degree   Adding up those numbers, that’s 13%. What about the other 87% of psychology bachelor’s degrees holders? 30% earned a masters or doctorate/professional degree in something other than psychology 57% did not earn a graduate degree Those 30% who earned a graduate degree in something else is nice evidence that a psychology degree is a good all-purpose sort of degree. The father of one my students took his bachelor’s in psychology to law school. He is now a judge. I wish all judges had degrees in psychology! Those 57% who did not earn a graduate degree are undoubtedly putting their psychology degrees to good use, no matter what they are doing. Although some of them aren’t fully cognizant of what their education is doing for them now. Give students a copy of the American Psychological Association Guidelines for the Major. Divide students into groups, and give each group two possible jobs a person might have. Drew Appleby’s list is a nice one to choose from. Ask each group to put a checkmark for each job on their Guidelines for the Major the knowledge and skills (outcomes) that would be useful to have in their assigned jobs. For each outcome have one person in each group raise their hand if the group thought the outcome was important for one of their jobs. Have two persons in each group raise their hands if they the outcome was important for both of their jobs. Tally the number of hands for each outcome. Give students an opportunity to share why they thought particular knowledge and skills (outcomes) is important and how the psychology major is helping them achieve that knowledge and skills. For any holes in your students' observations, let them know where in the curriculum students are gaining that knowledge and those skills. ... View more

As if cell phone use in cars isn’t bad enough, car manufacturers are building distractions into our automobiles, which I affectionately call Built-in Automotive Driving Distraction Systems TM . Automakers now include more options to allow drivers to use social media, email and text. The technology is also becoming more complicated to use. Cars used to have a few buttons and knobs. Some vehicles now have as many as 50 buttons on the steering wheel and dashboard that are multi-functional. There are touch screens, voice commands, writing pads, heads-up displays on windshields and mirrors and 3-D computer-generated images (Lowy, 2017). In an attempt to save lives, I have been hammering pretty hard on our inability to multi-task in my Intro Psych course. While this topic comes up in greater detail when I cover consciousness, I also embed examples of attention research in my coverage of research methods. Correlation example After I introduce the concept of correlations, I give my students 5 correlations, and ask them to identify the correlation as positive, negative, or no correlation. One of those correlations comes from a 2009 Stanford study reported by NBC News: people who multitask the most are the worst at it (“memory, ability to switch from one task to another, and being able to focus on a task”) (“Multitaskers, pay attention -- if you can,” 2009). Experiment example In talking about experimental design, I discuss David Strayer’s driving simulation research at the University of Utah. His lab’s research is easy for students to understand and the results carry a punch. I give this description to my students and ask them to identify the independent variable and the dependent variables. In an experiment, "[p]articipants drove in a simulator while either talking or not talking on a hands-free cell phone." Those who were talking on a cell phone made more driving errors, such as swerving off the road or into the wrong lane, running a stoplight or stop sign, not stopping for a pedestrian in a crosswalk, than those who were not talking on a cell phone. Even more interestingly, those who were talking on a cellphone rated their driving in the simulator as safer as compared to those who weren't talking on a cellphone. In other words, those talking on the cellphone were less likely to be aware of the driving errors they were making (Sanbonmatsu, Strayer, Biondi, Behrends, & Moore, 2016).   Class demo When Yana Weinstein of LearningScientists.org posted a link to a blog she wrote on a task switching demo (Weinstein, 2017) to the Society for the Teaching of Psychology Facebook page, I thought, “Now this is what my research methods lecture was missing!” I encourage you to read Weinstein’s original demo once you’re done reading mine.   I randomly divided my class into two groups. To do that I used a random team generator for Excel, but use whatever system you’d like. Weinstein does this demo with a within subjects design which, frankly, makes more sense than my between subjects design, but in my defense I’m also using this demo to help students understand the value of random assignment.   One group of students recited numbers and letters sequentially (1 to 10 and then A to J). The other group recited them interleaved (1 A 2 B 3 C, etc.). In your instructions, be clear that students cannot write down the numbers/letters and just read them. That’s a different task! Students worked in small groups. While one student recited, another student timed them with a cellphone stopwatch app. (You don’t have to know anything about cellphone stopwatch apps. Your students can handle it.) I didn’t bother dividing students into groups by task. In one group, there might have been three students who recited sequentially and a fourth student who recited interleaved. I asked students to write down their times, and then I came around to each group and asked for those times. I just wrote the times on a piece of paper, and displayed the results using a doc camera. Almost everyone in the sequential condition recited the numbers/letters in under 6 seconds. Almost everyone in the interleaved condition took over 13 seconds. In addition to talking about the independent variable (and experimental and control conditions) and the dependent variable, we talked about the value of random assignment. I had no idea who could do these tasks quickly or slowly. If 20% of them could do these tasks quickly, then random assignment would likely create two groups where the percentage of fast-task participants would be the same in each group. Is it possible that all of the fast-task participants ended up in the sequential task condition? Yep. And that’s one reason replication is important. Oh. And when you’re studying or writing a paper, students, this is why you should keep your phone on silent and out of sight. If you keep looking at your phone for social media or text notifications, it’s going to take you a lot longer to finish your studying or finish writing your paper. Perhaps even twice as long. And driving? As you switch back and forth from driving to phone (or from driving to Built-in Automotive Driving Distraction Systems TM ), it’s not going to take you twice as long to get to your destination. You’re traveling at the same speed, but you’re working with half the attention. That increases the chances that you will not get to your destination at all.   A lot of what we cover in Intro Psych is important to the quality of students’ lives. Helping students see our inability to multitask is important in helping our students – and the people they are near them when they drive – stay alive.   References Lowy, J. (2017, October 5). Technology crammed into cars worsens driver distraction. The Seattle Times. Seattle. Retrieved from https://www.seattletimes.com/nation-world/new-cars-increasingly-crammed-with-distracting-technology-2  Multitaskers, pay attention -- if you can. (2009). Retrieved from http://www.nbcnews.com/id/32541721/ns/health-mental_health Sanbonmatsu, D. M., Strayer, D. L., Biondi, F., Behrends, A. A., & Moore, S. M. (2016). Cell-phone use diminishes self-awareness of impaired driving. Psychonomic Bulletin & Review, 23(2), 617–623. https://doi.org/10.3758/s13423-015-0922-4 Weinstein, Y. (2017). The cost of task switching: A simple yet very powerful demonstration. Retrieved from http://www.learningscientists.org/blog/2017/7/28-1  ... View more

On rare occasion, I have reported startling findings that challenge current wisdom: Brain training games do NOT boost intelligence. Traumatic experiences are NOT often repressed. Seasonal affective disorder (wintertime blues) is NOT widespread.   The just-arrived lectures from the 2016 Bial Symposium on Placebo Effects, Healing and Meditation, offers another shocker: In an update on his meta-analyses, Irving Kirsch concludes that antidepressant drug effects are close to nil.   Here’s Kirsch’s gist: Many, many studies, including unpublished drug trials made available by the FDA, consistently show that Antidepressants work. They produce clinically significant benefits (using a standard depression scale). Placebos work, too. In two large meta-analyses, placebos produced 82 percent of the antidepressant effect. Moreover, “the difference between drug and placebo is . . . so small that clinicians cannot detect it.” Side effects can “unblind” a drug. The statistically (but not clinically) detectable drug effect may be attributable to antidepressants’ detectable side effects. The FDA only counts “successful trials.” Kirsch reports that despite meager evidence of antidepressant efficacy, the drugs gain approval because of a stunning FDA policy—which ignores trials that find no drug effect and reports only successful trials. “All antidepressant drugs seem to be equally effective.” As one would expect from a placebo effect, the benefits of various antidepressant drugs are “exactly the same regardless of type of drug.” Various serotonin-increasing drugs relieve depression, but so does a drug that decreases serotonin! “What do you call pills, the effects of which are independent of their chemical composition?,” asks Kirsch. “I call them ‘placebos.’”   Given that antidepressants work, even if they are hardly more than active placebos, what’s a clinician to recommend? Kirsch notes three considerations: Antidepressants have side effects, which can include sexual dysfunction, weight gain, insomnia, and diarrhea. Antidepressant use increases the risk of relapse after recovery. Cognitive behavioral therapy, acupuncture, and physical exercise also effectively treat depression. Ergo, “When different treatments are equally effective, choice should be based on risk and harm, and of all of these treatments, antidepressant drugs are the riskiest and most harmful. If they are to be used at all, it should be as a last resort.” But surely this is not the last word. Stay tuned for more findings and debate. ... View more

The Lancet reports that 15.3 percent of all humans are daily smokers. Yet smoking varies enormously, from: 25 percent among men to 5 percent among women, and from 43 percent among Greenlanders to 1 percent among Sudanese. Even the gender difference varies dramatically, from: nonexistent among Icelanders, where 14.4 percent of women and 14.5 percent of men smoke, to huge among Armenians, where nearly half (43.5 percent) of men and virtually no women (1.5 percent) are smokers. A question: What else do we know about all humanity (apart from our shared physiology)? Here is my short list. Do you know of more? If so I’d love to hear from you.  Human life expectancy: 71 years but with huge variation—from 39 years in Sierra Leone to 84 years in Japan. Humans overweight: 37 percent of men and 38 percent of women but with huge variation—from 3 percent in Timor-Leste to 85 percent in Tonga. Human religiosity: 68 percent say “Religion is important in my daily life” but with huge variation—from 16 percent in Estonia to 100 percent in Niger. Humans employed full time by an employer: 26 percent  but with huge variation—from 19 percent of women to 33 percent of men, and with child-free women varying from 11 percent employed in North Africa to 67 percent in Russia. The bottom line: We humans are kin. But how we differ!   Caiaimage/Robert Daly/OJO+/Getty Images ... View more

After covering experiments or as a research methods boost when covering attractiveness, pose this hypothesis to your students: Tattoos on men influence how others perceive the men’s health and attractiveness. Ask students to design an experiment to test this hypothesis, identifying the independent variable (including experimental and control conditions) and the dependent variables. In the design of the experiment, how would students eliminate any potential confounding variables? Circulate among groups as students work through the design. As discussion dies down, ask volunteers to share their experimental designs. Now share with students the experiment conducted by Andrzej Galbarczyk and Anna Ziomkiewicz (2017) using over 2,500 Polish participants recruited through Facebook; all participants self-identified as heterosexual. Researchers used nine non-tattooed male models, photographed from the waist up and without shirts for the control condition. “A professional photographer digitally modified the pictures by adding a black arm tattoo with an abstract, neutral design” for the experimental condition. This means that the only difference in the conditions was the tattoo. Participants were randomly assigned to see one photo for each model pair, and in the nine photos seen, each participant saw at least one tattooed model and one non-tattooed model. The dependent variables were ratings of attractiveness, health, dominance, aggression, fitness as a partner, and fitness as a father. Data were analyzed separately for male and female research participants. Before revealing the results, ask students to predict how the participants responded. Using clickers or a show of hands, ask students: Who did women rate as healthier? Tattooed men Non-tattooed men No difference [Women rated the tattooed men as healthier] Who did men rate as healthier? Tattooed men Non-tattooed men No difference [Men didn’t see a health difference between tattooed and non-tattooed men.] Who did women rate as more attractive? Tattooed men Non-tattooed men No difference [Women didn’t see a difference in attractiveness between tattooed and non-tattooed men.] Who did men rate as more attractive? Tattooed men Non-tattooed men No difference [Men rated the tattooed men as more attractive.] Who did men and women rate as more masculine, dominant, and aggressive? Tattooed men Non-tattooed men No difference [Tattooed men.] Who did women rate “as worse potential partners and parents”? Tattooed men Non-tattooed men No difference [Tattooed men.] Who did men rate “as worse potential partners and parents”? Tattooed men Non-tattooed men No difference [No difference.] Ask students to volunteer guesses as to why women would see tattooed men as healthier than non-tattooed men. And why men would see tattooed men as more attractive than non-tattooed men. The article’s authors offer a number of possible explanations, all worthy of further research.    REFERENCE Galbarczyk, A., & Ziomkiewicz, A. (2017). Tattooed men: Healthy bad boys and good-looking competitors. Personality and Individual Differences, 106, 122-125. doi:10.1016/j.paid.2016.10.051 ... View more

After introducing correlations, I share a number of examples with students. Here are couple new ones that going into my pool. Young adults (age 19-32) who spend their time on a lot (7 to 11) of different social media platforms are more likely (than those who spend their time on 0 to 2 different social media platforms) to report symptoms of depression. That same relationship exists between the number of different social media platforms and anxiety (Primack, et.al., 2017). Ask students if these represent a positive, negative, or zero correlation (clicker question, show of hands, shout out). (Both correlations are positive.) If students say negative, they may be caught in the trap of thinking that this is a “bad thing,” so it’s negative. Remind students that that is not what positive and negative mean in this context. It can help students in identifying correlations to first note what the two variables are (“number of social media platforms used” and “depression”; “number of social media platforms used” and “anxiety”) and then sort out whether those variables are moving in the same direction (positive) or opposite directions (negative). Next, to help students see that correlations don’t mean causation, ask students to consider the causes, why anxiety and depression may be related to the number of social media platforms used. In think-pair-share, give students a couple minutes to jot down their thoughts, then give students a couple minutes to share their ideas with one or two classroom neighbors, then ask for volunteers to share their thoughts. Students may surmise that jumping from one social media platform to another may cause depression or anxiety. The authors note three possibilities here: “participation in many different social media platforms may lead to multitasking between platforms, which is known to be related to poor cognitive and mental health outcomes;” since each platform has its own rules and customs “as the number of platforms used increases, individuals may experience difficulty navigating these multiple different worlds successfully, leading to potentially negative mood and emotions;” and the more social media platforms you are on you run an “increased risk of damaging gaffes.” Students may also surmise that those who are depressed or anxious may choose to jump from one social media platform to another. The authors suggest “[t]his may be because these individuals tend to search multiple avenues for a setting that feels most comfortable and in which they feel most accepted.”  A third possibility is that something else, a third variable, could be affecting both social media use and depression/anxiety, perhaps loneliness. Those who are more isolated may be more likely to seek out community in social media and being more isolated may contribute to depression/anxiety. Remind students that the value in correlations comes from revealing a relationship between two variables. Students identified a number of possible reasons as to why there is a relationship between those variables. The next step is to do more research on which of those possibilities are right -- and it may be one, some, or all of them.  Side note. Even though their research is clearly correlational, the article's authors are comfortable suggesting that it’s the social media use that’s causing or at least contributing to depression/anxiety. They write “it may not be too soon to suggest that individuals with depressive and/or anxiety symptoms, and who use a high number of different social media platforms may wish to decrease the number of platforms used.” Ask students if this is a fair statement for the authors to make.    Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among U.S. young adults. Computers in Human Behavior, 69, 1-9. doi:10.1016/j.chb.2016.11.013 ... View more

A political science grad student, Kevin Munger (2016a, b), decided to conduct an experiment on Twitter. His goal was to reduce the amount of hate speech posted to that media platform. To that end, he searched Twitter for a particular racial slur and sent every writer of such a tweet the same message: “@[subject] Hey man, just remember that there are real people who are hurt when you harass them with that kind of language.” But that’s not all. Munger reasoned that the impact of the message on future use of racial slurs likely depends on the communicator of that message, such as the perceived race and status of the person who is sending the reminder of the impact of language. Munger created four Twitter accounts: “High Follower/White; Low Follower/White; High Follower/Black; and Low Follower/Black.” The high followers had over 500 followers whereas the low followers had two followers. The White accounts displayed a White avatar and had a more stereotypically White-sounding name, Greg. The Black accounts displayed a Black avatar and had a more stereotypically Black-sounding name, Rasheed. Following Munger’s be-nice tweet, Munger tracked daily use of the racial slur over the next two months. The results. When Munger’s twitter account was High Follower/White, the number of racial slurs dropped .3 per day, the highest of any group. High status ingroup members do have power to influence. With about an equal, but smaller, decrease in daily use of racial slurs where the High Follower/Black and Low Follower/White avatars, although these differences disappeared within a few weeks (Munger, 2016b). Ingroup membership and high status both have an immediate, but not lasting impact, all on their own. What about Low Follower/Black? No Impact. In Intro Psych, you can give your students a little practice with experimental design by using this article at the beginning of the course when you cover research methods or as a research methods refresher later in the course when you cover social psychology. Ask students to identify the independent variables and dependent variable. The response to Munger’s missive wasn’t uniform; reponses differered by the anonymity of the Twitter user who received Munger’s message. Munger looked at the profiles of the Twitter users in his experiment. Of those users who were not anonymous, Munger reports that the High Follower/White Twitter account had no impact on the ensuing use of racial slurs. But the Low Follower/Black Twitter account “actually caused an increase (emphasis in original) in the use of racist slurs.” These were largely directed at Munger’s Twitter account that sent the be-nice message. Shout out to Danae Hudson (Missouri State University) for finding this article and suggesting this activity!   References Munger, K. (2016a, November 17). This researcher programmed bots to fight racism on Twitter. It worked. Retrieved from https://www.washingtonpost.com/news/monkey-cage/wp/2016/11/17/this-researcher-programmed-bots-to-fight-racism-on-twitter-it-worked Munger, K. (2016b). Tweetment effects on the tweeted: Experimentally reducing racist harassment. Political Behavior. doi:10.1007/s11109-016-9373-5 ... View more

Authors of Discovering the Scientist Within: Research Methods in Psychology, Gary Lewandowski, Natalie Ciarocco and David Strohmetz are all active researchers and committed teachers at Monmouth University. They’re excited to engage in a conversation about the Research Methods course, why it is so important, and talk about how they solve challenges in their own classrooms. Check out their Facebook live video from 11/4! Please feel free to leave any questions below or directly on the Facebook video and the authors will respond! ... View more