Originally posted on October 18, 2016.  For both graduate students and instructors alike, there are many reasons to teach a research methods course. From demand for professors to the ability to harbor student skills, these pragmatic approaches to teaching an engaging course are beneficial for students and instructors. Read more about my approach to teaching research methods on TeachPsych: http://teachpsych.org/page-1784686/4311450 ... View more

When covering research methods or as a research methods boost in health psych in Intro, ask your students, “Do fitness trackers, like Fitbit, work? If you were a psychological scientist trying to answer this question, how would you do it?” Give students a couple minutes to think about this on their own. Next, ask students to work in pairs or small groups to design an experiment that would help answer this question. As you circulate among the groups, make sure the groups are answering the question “Do fitness trackers work… at doing what?” As discussion is winding down, bring the class back together and ask for groups willing to volunteer their experimental designs. There should be some sort of random assignment to wearing a fitness tracker or not. Ask students why? [Because if you compared existing users with existing non-users, the users may already be more motivated to engage in physical activity.] Ask students to identify the independent variable [fitness tracker usage] and the experimental condition [fitness tracker] and control condition [no fitness tracker]. How long did students think participants should use/not use a fitness tracker to ensure a fair test? Why that amount of time? Ask students to identify the dependent variable(s) [perhaps weight loss]. With class discussion on the design wrapping up, share with students the results of such a study (Jakicic, et.al., 2016). Participants (470 of them) were six months into a 2-year weight-loss study when they were randomly assigned to either wear a fitness tracker that included a website for monitoring diet or self-monitor exercise and diet via a website (74.5% completed the study; every six months, participants were given $100). Note that this study did not have a no-treatment control group. Ask students to predict the results by a show of hands or via an audience response system. A. Fitness-tracker users lost the most weight B. Self-monitors lost the most weight C. Fitness-tracker users and self-monitors lost about the same amount of weight. Ready for the results? Those assigned to wear fitness trackers lost 3.5 kg (7.7 lbs). Those assigned to self-monitor lost 5.9 kg (13 lbs). There were no differences in the groups at the 6-month mark, the point in the study where they were randomly assigned to wear the fitness tracker or self-monitor. But at the next three check-ins (12 months, 18 months, and 24 months), the self-monitoring group had always lost more weight. Did your students guess right? Were they surprised by the results? Some explanations for these results are offered in this NPR story. But before you share these with students, ask students to generate some hypotheses as to why the self-monitoring group lost more weight than the fitness-trackers. If time allows, give students a couple minutes to think on their own before sharing in pairs or small groups.  Ask student volunteers to report out their hypotheses. Write the hypotheses where students can see them. If you’d like to send students off with a take-home assignment, assign students to design an experiment (but not conduct it!) that would test one of the student-generated hypotheses. Students should identify their independent and dependent variables and anything else they would do that would eliminate confounding variables. You can either let students choose the hypothesis, or assign hypotheses by last name, e.g., “If you’re last name begins with A through F, you have hypothesis 1.” Students can submit as a written assignment, or if you have time at the beginning of the next class, give students an opportunity to share their designs with each other, and then take a few minutes to ask volunteers to share their designs.   Reference Jakicic, J. M., Davis, K. K., Rogers, R. J., King, W. C., Marcus, M. D., Helsel, D., . . . Belle, S. H. (2016, September 20). Effect of wearable technology combined with a lifestyle intervention on long-term weight loss: The IDEA randomized clinical trial. Retrieved from http://jama.jamanetwork.com/article.aspx?articleid=2553448 ... View more

Years ago, as a young instructor, I didn’t have the tools to help my struggling students who came to my office for studying advice. I had a clear idea of what “studying” was since I had done it for so long, but I don’t know if it’s that I couldn’t put words to what I did to study or if I assumed that everyone did the same thing when “studying,” and that if that didn’t work, I didn’t know what would. In any case, over time, I got better at my advice – test yourself, space out your studying, for example. One term I had a student who earned a perfect score on an exam. Students in the class knew somebody did, and they asked who it was. I said I couldn’t reveal the person’s name, but that person can if so desired. My perfect-score student immediately said, “I did! And I’m proud of it.” The other students began peppering her with some version of “How did you do it!” She explained that she spent time every day on the class. She read the textbook, took notes, merged her textbook notes with her class notes, thought of examples, tested herself over what she was learning. Students started exclaiming, “Oh! I don’t want to do all of that!” Her response? “Then you don’t get an A.” Learning is hard work. There’s no way around it. For students who are willing and able to put in the hard work, I want them to use effective, research-based study techniques. Unfortunately, students may not know what those research-based study techniques are. Some of the techniques students use may be a complete waste of time. Gurung, Weidert, and Jeske (2010) asked 120 students to complete a questionnaire on 35 different study behaviors. The behaviors that correlated positively with the students’ final exam scores: “attended every class,” “answered every question in the study guide,” “used practice exams to study,” and “was able to explain a problem or phenomenon using the material.” Behaviors that correlated negatively with exam scores: “after class, I looked over my notes to check for and fill in missing information,” “highlighted the most important information in each chapter to review later,” “reviewed the chapter after the lecture on that topic,” “asked… a classmate/friend to explain material I didn’t understand,” and “asked the professor or TAs for additional materials.” Interestingly, when they looked at just the top half of exam performers, only one correlation remained. Those who reported highlighting as a study strategy scored lower than those who did not. Highlighting is easy to do – it’s too easy to do. It doesn’t require deep processing; it’s a very shallow process. But at the end, with words highlighted, it’s easy to fool oneself into thinking studying was accomplished. Highlighting is really just coloring – and there are reasons coloring is relaxing: it takes little to no cognitive effort. Now, how about some advice on how to study? Yana Weinstein (UMass Lowell) and Megan Smith (Rhode Island College) of the LearningScientists.org blog have created a wonderful set of posters (slides and sticker templates) to help students learn how to study better. The strategies: spaced practice, retrieval practice, elaboration, interleaving, concrete examples, and dual coding. Side note: I love the use of the very specific word practice instead of the fuzzier word study. Elliott Hammer (2016) reports that “I’m also trying as of late to drop the word ‘study’ from my vocabulary in favor of ‘practice. It’s difficult to get students to be more active in their approach, and I want them to get beyond simply trying to read and call that studying. I don’t have data showing that the switch is working, but it feels more genuine.” To get your students to dive into these learning strategies, after covering the memory chapter, ask students to explain why each strategy is effective based on the concepts and research covered in their reading. This makes a nice out-of-class assignment, but it would also work well done in class with small groups. Give each small group the set of posters to explain the effectiveness of each. After discussion wanes, ask a group to report out on one of the posters; give other groups an opportunity to add to the conversation. Move onto another group, and ask them to report out on a different poster. Continue until all of the posters have been covered. If you use a classroom response system, ask students if they currently use the study strategy and whether they plan to use it in the future. Or you could do a jigsaw classroom. Divide the class into 6 groups of at least 6 members each (or 12 groups of at least 6 members or some other multiple of 6, depending on your class size) and give each group a different poster. (For smaller classes, use multiples of 3 and give each group 2 posters). After each group identifies why the strategy is effective (using the concepts learned in the memory chapter), break apart the groups so that at least one person from each group now forms a new group. Ask each new group member to share the strategy on their poster and explain why the strategy is effective. Bonus: Use the Gurung, et.al. (2010) study as examples when you cover correlations in the research methods chapter. Or use it here in the memory chapter to reinforce correlations. And then ask students which learning strategy is being used in the practice of learning correlations.   References Gurung, R. A., Weidert, J., & Jeske, A. (2010). Focusing on how students study. Journal of the Scholarship of Teaching and Learning, 10(1), 28-35. Hammer, E. (2016, July 31). I’m a member of STP and this is how I teach. Retrieved from http://teachpsych.org/page-1703896/4186852 ... View more

Originally posted on May 5, 2014. From an early age, I wanted to be an astronaut. I memorized Mercury astronaut missions. I dreamt of using a manned maneurvering unit to glide through space. I cried when the Challenger exploded. I still dream of going to space, but I know it’s a long shot. Still, space exploration captivates me. What will be the biggest obstacle to a successful Mars mission? It won’t be inadequate fuel, faulty aerodynamics, or clunky helmets. Social isolation is the greatest barrier to interplanetary travel. Don’t believe me? Think about the past 520 days of your life (about a year and five months). That’s how long it takes to travel to Mars and return. How many people did you see during that time? How many conversations did you have? Did you attend a sporting event? A play? A worship service? Maybe a loved one was born or passed away. Now wipe those experiences away. Instead, imagine that during this period of your life you lived in cramped quarters with only five other people, no fresh air, and no sunlight. This is not a mere thought experiment. The experiment happened, with funds from the Russian Academy of Sciences. What happened? Quite a bit. In research recently reported in the Proceedings of the National Academy of Sciences, the six volunteer marsonauts completed lots of tasks to keep their minds fresh. They also slept like babies without the daily rigmarole of daily work commutes, grocery shopping, or other daily drivel. Then the guys started sleeping like polar bears in hibernation. Then they started doing less, becoming even more sedentary amidst almost endless boredom. Space is only cool for so long. The good news? They all made it. There weren’t any major scuffles, and the guys probably formed lifelong friendships. They even showed signs of cognitive improvement. But the marsonaut volunteers each handled the prolonged social isolation differently. One of them shifted to a 25-hr sleep-wake schedule, which meant that he was alone (awake or asleep) 20% of the 520 day mock mission. As the researchers sift through their massive data set (to put it in perspective, they measured 4.396 million minutes of sleep!), I’m sure we’ll learn more about the psychological consequences of prolonged social isolation. For now, we can still look into the night sky, find the Red Planet, and dream of people visiting sometime in our generation. We know they’ll sleep well—and a lot. ... View more

Originally posted on May 16, 2014. Being around men increases stress. Do countries with more man than women have higher stress levels? In my last post, I promised to answer this question. But it’s a harder question than it seems. How do you measure a country’s level of stress? Some organizations, such as Gallup, do an excellent job surveying people around the world. I don’t work at Gallup, nor do I have access to their data. So I had to do the best I could. First, I gathered country gender composition data from our friends at the World Bank. I separated countries according to whether they had a majority of male or female citizens. The average was 50.77% women (standard deviation 1.19; Minimum: 48.19%, Maximum: 54.30%). Of the 74 countries for which data were available, 19 were male-majority and 55 were female-majority. Next, I searched for a good, comprehensive measure of country-level stress. Bloombergmade things easy. They computed a country’s stress score by combining seven factors: Annual Homicide Rate per 100,000 Gross Domestic Product (GDP) per capita Income inequality (Gini coefficient) Corruption (as measured by Transparency International) Unemployment rate Urban air pollution (micrograms per cubic meter) Life expectancy (years at birth) Finally, I compared country-level stress between male-majority and female-majority countries. This would give me an initial answer to my question. What were the results? Countries with more men than women, compared to their female-majority counterparts, had higher levels of stress. Three factors drove the effect: corruption, pollution, and life expectancy. In each case, more men than women equaled a more corrupt, polluted, and shorter lived society. A close fourth, which wasn’t quite statistically significant (p= .063), was Gross Domestic Product per capita. If a country had a male majority (vs. female majority), GDP was lower. These findings offer a novel extension to the finding that being around men, versus women, increases rodent stress. But unlike those careful laboratory experiments, people weren’t randomly assigned to live in male- or female-majority countries. We can’t infer cause and effect. All we can conclude is that when men are present, stress seems to rise instead of fall. ... View more

Originally posted on February 5, 2015. Even though the smartphone has only been around for the past seven or eight years, it’s sometimes difficult to remember what life was like before we had so much information at our fingertips. You could argue with a friend about what year “Back to the Future, Part 2” came out, or in what year the “future” was set. (It was released in 1989. The future, filled with flying cars and floating skateboards, was set in 2015.) Back then, you couldn’t resolve discussions by swiping a screen and touching a button. Siri wasn’t even a twinkle in Steve Jobs’s eye. If you got lost, you had to consult a map or stop and ask for directions, and if you got bored while waiting in line, you couldn’t pass the time by playing Candy Crush or perusing Instagram. Luddites argue that life was better before the smart phone, whereas others tout the benefits of instant communication and information. But one thing is certain: The smartphone has changed our lives. And our thumbs. Yes, when we spend time on smartphones using a touchscreen, it changes the way our thumbs and brains work together, according to a new study by researchers from the University of Zurich and ETH Zurich in Switzerland. Our obsession with smartphones presented the perfect opportunity to explore the everyday plasticity of our brains. With smartphones, we are using our fingertips—especially our thumbs—in a new way, and we do it a lot. And because our phones keep track of how we use them, they carry a wealth of information that can be studied. In the study, the research team used electroencephalography (EEG) to record brain response to the touch of the thumb, index finger, and middle fingerprints of touchscreen phone users compared to people who still use flip phones or other old-school devices. They found that the electrical activity in the brains of smartphone users was enhanced when all three fingertips were touched. The amount of activity in the brain’s cortex associated with the thumb and index fingertips was directly proportional to the amount of phone use. Repetitive movements over the touchscreen surface might reshape sensory processing from the hand. Cortical sensory processing in our brains is constantly shaped by personal digital technology. So, the next time you use your thumbs to tweet, answer email, or jot yourself a note, remember that you’re training your brain. Keep in mind, too, that excessive phone usage is linked with motor dysfunction and pain. Remember the so-called “BlackBerry thumb”? ... View more

Originally posted on April 3, 2014. My friend Ed Diener, the Jedi Master of happiness research, presented a wonderful keynote talk on “The Remarkable Progress of National Accounts of Subjective Well-Being” at the recent one-day “Happiness and Well-Being” conference.  He documented the social and health benefits of positive well-being, and celebrated the use of at least simple well-being measures by 41 nations as of 2013. In displaying the health accompaniments of positive emotions, Ed introduced me to a 2011 PNAS (Proceedings of the National Academy of Sciences) study by Andrew Steptoe and Jane Wardle that I’d somehow missed.  Steptoe and Wardle followed 3,853 fifty-two to seventy-nine year olds in England for 60 months.  This figure displays the number surviving, among those with high, medium, and low positive affect—which was assessed by averaging four mood reports across a single day at the study’s beginning.  Those with a “blue” mood that day were twice as likely as the good mood folks to die in the ensuing five years!{cke_protected_1}{cke_protected_2} ... View more

Originally posted on April 6, 2014. Consider Brett Pelham, Matthew Mirenberg, and John Jones’ 2002 report of wacky associations between people’s names and vocations.  Who would have guessed?  For example, in the United States, Jerry, Dennis, and Walter are equally popular names (0.42 percent of people carry each of these names). Yet America’s dentists have been almost twice as likely to be named Dennis as Jerry or Walter. Moreover, 2.5 times as many female dentists have been named Denise as the equally popular names Beverly and Tammy. And George or Geoffrey have been overrepresented among geoscientists (geologists, geophysicists, and geochemists). I thought of that playful research recently when reading some clever research on black bears’ quantitative competence, co-authored by Michael Beran.  Next up in my reading pile was creative work on crows’ problem solving led by Chris Bird.  Today I was appreciating interventions for lifting youth out of depression, pioneered by Sally Merry. That also took my delighted mind to the important books on animal behavior by Robin Fox and Lionel Tiger, and the Birds of North America volume by Chandler Robbins.  (One needn’t live in Giggleswick, England, to find humor in our good science.) The list goes on: billionaire Marc Rich, drummer Billy Drummond, cricketer Peter Bowler, and the Ronald Reagan Whitehouse spokesman Larry Speakes.  And as a person with hearing loss whose avocational passion is hearing advocacy, I should perhaps acknowledge the irony of my own name, which approximates My-ears. Internet sources offer lots more:  dentists named Dr. E. Z. Filler, Dr. Gargle, and Dr. Toothaker; the Oregon banking firm Cheatham and Steele; and the chorister Justin Tune.  But my Twitter feed this week offered a cautionary word about these reported names: “The problem with quotes on the Internet is that you never know if they’re true.”  ~ Abraham Lincoln Perhaps you, too, have some favorite name-vocation associations?  I think of my good friend who was anxiously bemused before meeting his oncologist, Dr. Bury.  (I am happy to report that, a decade later, he is robustly unburied and has not needed the services of the nearby Posthumus Funeral Home.) For Pelham and his colleagues there is a serious point to this fun:  We all tend to like what we associate with ourselves (a phenomenon they call “implicit egotism”). We like faces that have features of our own face morphed into them.  We like—and have some tendency to live in—cities and states whose names overlap with our own—as in the disproportionate number of people named Jack living in Jacksonville,of Philips in Philadelphia, and of people whose names begin with Tor in Toronto. Uri Simonsohn isn’t entirely convinced (see here and here, with Pelham’s reply here).  He replicated the associations between people’s names, occupations, and places, but argued that “reverse causality” sometimes is at work. For example, people sometimes live in places and on streets after which their ancestors were named. Implicit egotism research continues.  In the meantime, we can delight in the occasional playful creativity of psychological science. P.S.  Speaking of dentists (actual ones), my retired Hope College chemistry colleague Don Williams—a person of sparkling wit—offers these photos, taken by his own hand: And if you need a podiatrist to advise about your foot odor, Williams has found just the person: ... View more

Originally posted on April 18, 2014. “The Internet is one big field study,” observed Adam Kramer, a social psychologist and Facebook researcher, at the recent Society for Personality and Social Psychology (SPSP) presidential symposium on big data.  Some big data factoids, gleaned from the conference: There are, according to Eric Horvitz, Managing Director of Microsoft research, 6.6 degrees of separation between any two people on the Internet. Google has now digitized 6 percent of all published books, creating a huge archive of words that can be tracked over time at https://books.google.com/ngrams.  One can use this resource to answer interesting questions . . . such as: is it true that the term “homosexuality” hardly predates the 20th century, and that “sexual orientation” is a late 20th century concept?  It took me about a second to create this figure of the proportional frequency of these terms over time: On Facebook, Kramer reported Parents and children take an average 371 days to friend one another. Mothers use 10% more nurturing words when communicating with their children. In the 2010 congressional elections, people’s posting their having voted led to 340,000 additional voters among their friends and friends of friends. Positive emotion words in people’s posts are followed, in the ensuing three days, by increased positive emotion words in friend’s posts, and vice versa for negative emotions. A research team led by Blaine Landis at the University of Cambridge analyzed all 30.49 billion international Facebook friendships formed over four years, and reported (in an SPSP poster) that people tended to “friend up.”  Those from countries with lower economic status were more likely to solicit friendship with those in higher status countries than vice versa. ... View more

Originally posted on May 28, 2014. Climate change is upon us.  The recent National Climate Assessment, assembled by a large scientific panel, confirms that greenhouse gases continue to accumulate.  The planet is warming. The West Antarctic ice sheet is doomed. The seas have begun rising.  And more extreme weather will plague our future. Alas, most of the American public is not yet alarmed about this weapon of mass destruction.  The 31 percent who in 1998 thought “the seriousness of global warming is generally exaggerated” increased to 42 percent in 2014.  And the 34 percent of Americans who in 2014 told Gallup they worry “a great deal” about global warming was essentially the same as in 1989. Part of the problem is what psychologists and their students know as the availability heuristic. Our judgments get colored by mentally available events and images. And what’s more cognitively available than slow cli­mate change is our recently experienced local weather (see here and here).  Local recent temperature fluctuations tell us nothing about long-term planetary trends. (Our current weather is just weather.) Yet, given unusually hot local weather, people become more accepting of global climate warming, while a recent cold day reduces people’s concern about climate warming and overwhelms less memorable scientific data.  Snow in March?  “So much for global warming!” After Hurricane Sandy devastated New Jersey, its resi­dents’ vivid experience of extreme weather increased their environmentalism.  This suggests that a silver lining to the tragedy of more droughts, floods, heat waves, and other extreme weather may, in time, be increased public concern for climate change.  In the meantime, to offer a vivid depiction of climate change, Cal Tech scientists have created an interactive map of global temperatures over the last 120 years. ... View more

Originally posted on June 5, 2014. An amazingly comprehensive new Lancet study, with nearly 150 authors, tracks overweight and obesity rates across 188 countries from 1980 to 2013.  Some highlights: Worldwide, the proportion of overweight adults (BMI ≥ 25) increased from 29 to 37 percent among men and 30 to 38 percent among women. Over the last 33 years, no country has reduced its obesity rate. In 2010, “overweight and obesity were estimated to cause 3.4 million deaths.” National variations are huge, with the percentage overweight ranging 85 percent among adults in Tonga to 3 percent in Timor-Leste. The study is amazing not only in its global comprehensiveness, across time, but also in its public, interactive data archive available from the Institute for Health Metrics and Evaluation. As a screen shot example, I compared the U.S. increase in the overweight percentage (upper dark line) with the global increase (lower dark line).  All other countries are in light blue. ... View more

Originally posted on June 12, 2014. My last post—noting the new worldwide estimate that 37 percent of men and 38 percent of women are overweight—got me to wondering if we have other examples of all-humanity data. One is our species’ life expectancy, which has risen from 46.5 years in the early 1950s to 70 years today. What a gift—two dozen more years of life! And then we have new data from the Gallup World Poll which is surveying countries with more than 98 percent of the world’s population. Aggregating data from this resource, Ed Diener, Louis Tay, and I were able to answer (here) this simple question: Asked, “Is religion important in your daily life?,” what percent of humanity will respond “yes”? The answer: 68 percent. Two in three humans. When mentioning this answer in talks, I offer, with a smirk, the usual caveat on reporting survey data: We should be cautious about generalizing beyond the population sampled. (These data represent but one species on one planet, and may not represent the views of other life forms elsewhere in the universe.) What’s striking about each of these all-humanity measures is the extraordinary variation across countries—from 3 percent overweight adults in Timor-Leste to 85 percent in Tonga; from 49 year life expectancy in Chad to 89 in Monaco; from 16 percent for whom religion is important in Estonia to 100 percent in Bangladesh and Niger. We humans are all kin beneath the skin. Yet how we differ. [A note to our valued readers:  Nathan DeWall and I anticipate a more relaxed two-a-week pace of blogging this summer, and returning to our weekday postings at the summer’s end.] ... View more

Originally posted on September 3, 2014. Skimming Paul Taylor’s, The Next America: Boomers, Millennials, and the Looming Generational Showdown, a 2014 report of Pew Research Center data on U.S. social trends, brought to mind one of my pet peeves: the favoritism shown to seniors over today’s more economically challenged Millennials and their children. Since passing into AARP-eligible territory, I have often purchased fares or tickets at discounted prices, while the single parent in line behind me got hit with a higher price. One website offers 250,000+ discounts for folks over 50. A half-century and more ago it made sense to give price breaks to often-impoverished seniors wanting a night out at the movies, hungry for a restaurant meal, or needing to travel on buses and trains. Many seniors still struggle to make ends meet and afford housing.  But thanks to improved Social Security and retirement income and to decreased expenses for dependents and mortgages, their median net worth has been increasing—37 percent since 1984, Taylor shows, while those under 35 have seen their net worth plummet 44 percent. And consider who are today’s poor (from this figure available here as well as in Taylor’s excellent book). Among the predictors is not only race but age.  Compared to four decades ago, today’s under-35 generation experiences a nearly doubled risk of poverty, while their senior counterparts suffer one-third the poverty rate of their 1960s counterparts Ergo, in view of this historical change in poverty risk, should we adjust our social priorities? Might a more child-affirming culture consider discounts for card-carrying custodial parents? And could we not offer inflation adjustments not only to senior citizen Social Security stipends but also to minimum wages, tax exemptions for dependents, and family and food assistance? ... View more

Originally posted on September 15, 2014. Every once in a while I reread something that I've reported across editions of my texts, scratch my head, and ask myself: Is this really true? Such was the case as I reread my reporting that “With the help of 382 female and 312 male volunteers. . . Masters and Johnson monitored or filmed more than 10,000 ‘sexual cycles.’” Really? I wasn't just makin’ stuff up.  Masters and Johnson do report (on page 15 of Human Sexual Response) their “conservative estimate of 10,000 complete sexual response cycles” in their laboratory (some involving multiple female orgasms). But let’s do the numbers.  If they observed 10,000 complete sexual cycles over eight years[1] (from 1957 to 1965), then they averaged 1,250 sexual cycles observed per year.  Could we assume about an hour dedicated to each observation—including welcoming the participant(s), explaining the day’s tasks, attaching instruments, observing their behavior, debriefing them, and recording their observations?  And could we assume about 40 weeks a year of observation?  (Meanwhile, they were also running a sexual therapy clinic, writing, managing a lab, etc.) So . . . doing the numbers . . . that’s roughly 31 weekly hours observing sex . . . for eight years. It boggles the mind.  And one wonders: Wasn't there some point of diminishing returns from observing yet another 1000 hours of sex . . . assuming Masters and Johnson reported truthfully? I have no basis for doubting the accuracy and integrity of Masters and Johnson’s reporting.  But I do, in a spirit of curiosity, scratch my head. [1] In Human Sexual Response, they report gathering data over “eleven years” (pp. 9, 20).  But Johnson didn't join Masters until 1957, and Johnson biographer Genoa Ferguson reports that Johnson “began doing sexual function research 6 months into her research position.” Also, Masters and Johnson report (p. 10) that the first 20 months of the observations—presumably by Masters without Johnson—involved medical histories of 118 prostitutes, eleven of whom “were selected for anatomic and physiologic study.”  Ergo, although Masters and Johnson’s reporting leaves the exact study period ambiguous, it appears that the great majority, if not all, of the reported 10,000+ “complete sexual responses cycles” were observed during the seven or eight years after Johnson began her work with Masters. They also do not document the lab layout, or precisely how they observed their subjects. (As a point of contrast, Stanley Milgram’s similarly classic Obedience to Authority did precisely report on the participants, methods, and results of his various experiments, including drawings of the lab layout and equipment.) ... View more

Originally posted on December 23, 2014. The Centers for Disease Control and Prevention, drawing from its own continuing household interviews, offers new data​ on who in the U.S. is most likely to suffer depression, and how often.   Some noteworthy findings: Overall rate of depression: Some 3 percent of people age 12 and over were experiencing “severe depressive symptoms.” More people—7.6 percent—were experiencing “moderate or severe” symptoms, with people age 40 to 59 at greatest risk. Many more—78 percent—“had no depressive symptoms.” Gender and depression. Women experience nearly double (1.7 times) men’s rate of depression. Poverty and depression. People living below the poverty line are 2½ times more likely to be experiencing depression. (Does poverty increase depression? Does depression increases poverty? Or—mindful of both the stress of poverty and the CDC-documented impact of depression on work and home life—is it both?) Depression and treatment.  Only 35 percent of people with severe symptoms reported contact with a mental health professional in the prior year. ... View more