Everyday Research Methods

Lion attacks on cattle: A field experiment

Researchers painted eyes like these on some of the cattle in each herd. Credit: Cameron Radford

Here's an example of a field experiment that took place in actual fields. The empirical article appeared in Nature Communications, and the authors of the research wrote their own summary for a popular audience in The Conversation. The quotes below come from their popular audience summary. 

In this study, the authors worked with cattle ranchers in Botswana who were trying to reduce the number of lions and leopards who attacked their herds.

The introduction outlines the theory the researchers were testing:

Many big cats – including lions, leopards, and tigers – are ambush predators. This means that they rely on stalking their prey and retaining the element of surprise. In some cases, being seen by their prey can lead them to abandon the hunt. We tested whether we could hack into this response to reduce livestock losses to lions and leopards in Botswana’s Okavango delta region.

Below are some details of the method of their study. It sounds like an experiment: Can you see why?

Working with Botswana Predator Conservation and local herders, we painted cattle from 14 herds that had recently suffered lion attacks. Over four years, a total of 2,061 cattle were involved in the study.

Before release from their overnight enclosure, we painted about one-third of each herd with an artificial eye-spot design on the rump, one-third with simple cross-marks, and left the remaining third of the herd unmarked. We carried out 49 painting sessions and each of these lasted for 24 days.

The cattle were also collared and all foraged in the same area and moved similarly, suggesting they were exposed to similar risk. However the individuals painted with artificial eye-spots were significantly more likely to survive than unpainted or cross-painted control cattle within the same herd.

In fact, none of the 683 painted “eye-cows” were killed by ambush predators during the four-year study, while 15 (of 835) unpainted, and 4 (of 543) cross-painted cattle were killed.

Questions

a) What were the independent and dependent variables in this study? What were the levels of each variable?

b) What kind of experiment was this: Posttest-only? Prettest-posttest? Repeated measures? Or concurrent measures? (Challenge question: How might your answer change if you take the predator's perspective, as compared to the cattle's perspective?)

c) Sketch a bar graph of the results of the study. (Later you can compare your sketch to the figures in the Nature article).

d) The authors don't seem to specify here whether or not they used random assignment to the three painting conditions. Why would random assignment be important?

e) Ask a question about the external validity of this study. (Which term will your answer involve: random assignment or random sampling?) 

At the end of their popular press summary, the authors raise two important limitations:

First, it is important to realise that, in our experimental design, there were always unmarked cattle in the herd. Consequently, it is unclear whether painting would still be effective if these proverbial “sacrificial lambs” were not still on the menu. Further research could uncover this, but in the meantime applying artificial marks to the highest-value individuals within the herd may be most pragmatic.

Second, it is important to consider habituation, meaning that predators may get used to and eventually ignore the deterrent. This is a fundamental issue for nearly all non-lethal approaches. Whether the technique remains effective in the longer term is not yet known in this case.

f) How might you design a study to test the first limitation? That is, how could you manipulate the eye-paintings variable in order to test if this intervention still works if there are no "sacrificial lambs" in the herd? What would your different conditions look like?

g) How might the authors test the second limitation? What can they change about, or add to, their study to test whether "the technique remains effective in the longer term"?

 

 

 

Does "virtue signaling" change minds?

If a lot of us send virtue signals, it can communicate to others that norms are changing. Credit: SEEphotos7171/Shutterstock"

Among people fighting for racial justice, "virtue signaling" may sometimes be derided as empty action. "Virtue signals" are public messages of support for a social justice cause. They could take the form of a yard sign, a t-shirt, or a social media post. Critics sometimes argue that such messages are easy and cheap. It's easy for a company to put a message on their home page that supports Black Lives Matter. It's not hard to wear a t-shirt that supports a social justice cause. But are these expressions of support all talk and no action?

An article in Time magazine argues that virtue signaling can be more powerful than we think. The authors, psychological scientists Jamil Zaki and Mina Cikara, integrate several studies to make their argument. Here's part of their introduction: 

It’s critical to question people whose most radical act is temporarily changing their profile picture. It’s critical they follow their words with action; the time for talk has passed. But focusing solely on virtue signalers obscures their most important role. Like radio waves, the signals they send are received by someone, and those receivers matter, too.

Zaki and Cikara argue that virtue signaling is an important way of influencing others. If a lot of people change their profile pictures to support BLM, for example, more people will start to believe that this movement is popular and they may adopt it, too:

Opinions can work this way: when a particular viewpoint gets a lot of attention, people assume it’s popular, and shift towards it. We receive signals, and are changed by them.

What studies support their argument? Here's one that the authors summarize: 

As social norms shift, individuals shift with them: adopting popular opinions and behaviors, and dropping ones that fall out of style. Norms are especially powerful as they gain steam. In one set of studies, Gregg Sparkman and Greg Walton presented diners in a cafeteria [either] with evidence that 30% of the U.S. population was vegetarian, or that 30% of the population was newly vegetarian. People who learned about this second, “dynamic social norm” were twice as likely to order a meatless lunch themselves. They saw not just where the crowd was, but where it was going, and didn’t want to be left behind.

Here are some questions about the study summarized above:

a) Was this an experiment or a correlational study? How do you know? (If it's an experiment, what kind of study is it?)

b) What were the key variables in the study? Were they manipulated or measured? 

c) Sketch a small graph of the results being described. Would a bar graph or a scatterplot make more sense?

Here's another study Zaki and Cikara introduce:

Signaling and conformity are not inherently positive. In 2016, the U.S. elected a president whose campaign was jammed with racist talking points. Prejudice subsequently increased, specifically toward groups he targeted (e.g., Muslims, immigrants). 

d) This summary doesn't really help you figure out how the study was designed. But here's a chance to think carefully: What kind of study would we need to conduct in order to test the claim that "prejudice subsequently increased, specifically toward groups he targeted (e.g., Muslims, immigrants)."?  There are three variables you would need to include in your study. What are they? 

 

Suggested answers to selected questions

a) This was probably a posttest-only experiment, because it sounds like they manipulated the message about vegetarianism and measured what foods people took in the cafeteria. Here is a link to the original empirical article. 

d) The key dependent variable in this study is prejudice levels, so that's the first variable. Then, in order to establish that "prejudice increased", you'd need to measure prejudice both before and after the election, so that's another variable. Finally, in order to show that it increased specifically toward groups he targeted, you'd need to measure different types of groups (Muslims, immigrants, as well as other potential groups that Trump did not deride in his campaign). You can review the Crandall article here. Do their results really support what Zaki and Cikara are saying about it? (Pay attention to the difference between people's actual prejudice and the normativity of prejudice.) 

 

 

 

 

Saturated fat can impair concentration

Breakfast of (concentration) champions? Maybe not....Photo credit: Kyndall Ramirez/Unsplash

A headline at Psych Central reads, "High fat meal may impair concentration." Does the study behind the headline support that causal claim?

At first, you might assume that this came from a correlational study on diet and concentration. However, it turns out the research summarized in the article was experimental: It manipulated the saturated fat content of one specific meal. In the study, researchers created two versions of a breakfast--one made with saturated fat and the other made with sunflower oil, which is also high in dietary fat but is not the saturated type. 

The journalist describes the method of the study this way: 

Women in the study [n = 52] completed a baseline assessment of their attention during a morning visit to the lab. The tool, called a continuous performance test, is a measure of sustained attention, concentration and reaction time based on 10 minutes of computer-based activities.

The high-fat meal followed: eggs, biscuits, turkey sausage and gravy containing 60 grams of fat, either a palmitic acid-based oil high in saturated fat or the lower-saturated-fat sunflower oil. Both meals totaled 930 calories and were designed to mimic the contents of various fast-food meals such as a Burger King double whopper with cheese or a McDonald’s Big Mac and medium fries.

Five hours later, the women took the continuous performance test again.

Between one and four weeks later, they repeated these steps, eating the opposite meal of what they had eaten on the first visit.

After eating the meal high in saturated fat, all of the participating women were, on average, 11 percent less able to detect target stimuli in the attention assessment.

(The original empirical journal article is here; it might be paywalled)

Questions:

a) What was the independent variable (IV) in this study and what were its levels?

b) What was the dependent variable?

c) Was the IV manipulated as independent groups or within-groups?

d) This design is difficult to classify because it has a pretest and posttest, but the women also experienced both levels of the IV. Therefore it shares features with two of the four designs in Chapter 10. What are those two designs it shares features with? (Note to students: As you can see in this example, the four designs you learned about in Chapter 10 are not the only types of experiments there are, and this study provides an example of alternative designs.) 

e) Sketch the results of this study--using "reduction in concentration" (i.e., a difference score) as the dependent variable. 

Next let's work through the four big validities. 

f) Here's some text related to external validity of this study:

For this work, Madison [the lead author] conducted a secondary analysis of data from Kiecolt-Glaser’s study assessing whether high-fat meals increased fatigue and inflammation among cancer survivors.

and

[the experimental meals]  were designed to mimic the contents of various fast-food meals such as a Burger King double whopper with cheese or a McDonald’s Big Mac and medium fries.

Given the information above, to what kinds of people and what kinds of situations might this research be generalized? How do you know? 

g) The researchers found an 11 percent drop in concentration after the meal high in saturated-fat. What further information would you like to know in order to evaluate the study's statistical conclusions? 

h) Can this study support the causal claim that "A high-fat meal may impair concentration"? Apply the three criteria to the study: Covariance (what did the results show?), temporal precedence (did the method ensure that the meal came before the drop in concentration?), and internal validity (What potential confounds did they control for in the study?) 

i) Here's some information about the study's construct validity: 

Women in the study completed a baseline assessment of their attention during a morning visit to the lab. The tool, called a continuous performance test, is a measure of sustained attention, concentration and reaction time based on 10 minutes of computer-based activities.

What questions would you need to ask to determine if this test is a good measure of people's ability to concentrate? 

Instructors: If you teach Chapter 12, you can also use this example as a mixed factorial design, because the study also included a participant variable of endotoxemia, a condition called "leaky gut." From the journalist's summary: 

After eating the meal high in saturated fat, all of the participating women were, on average, 11 percent less able to detect target stimuli in the attention assessment. Concentration lapses were also apparent in the women with signs of leaky gut: Their response times were more erratic and they were less able to sustain their attention during the 10-minute test.

“If the women had high levels of endotoxemia, it also wiped out the between-meal differences. They were performing poorly no matter what type of fat they ate,” Madison said.

Students could identify the IV, PV, and DV and practice graphing the results described above. 

Thanks to my colleague Stephen Chew, who shared this example.

Teaching with 100 Humans

In 2020, Netflix released an 8-episode series called "100 Humans" in which 100 (American) humans from a variety of ages and social groups participate in a series of studies. It's a gold mine of examples for critical thinking in research methods. You'll find examples of posttest-only, pretest-posttest designs, HARKing, ethics, and more. Most of the studies have flaws, but that makes them more fun to critique. 

I've cataloged ways you can use the series in your teaching: www.tinyurl.com/teachingwith100humans.

Reach out if you use it! Let me know how it works for you. 

 

Evidence-based tips for well-being during a pandemic

Dr. Santos provides evidence-based ways to enhance well-being during this pandemic. Credit: Yale University

How can people enhance their wellbeing during the Coronovirus pandemic? 

Dr. Laurie Santos (pictured) has been meeting with several news outlets, sharing evidence-based tips from her psychology of well-being class at Yale University. A version of the course is also offered on Coursera.

In the Twitter-embedded video here, produced by the World Economic Forum, Dr. Santos covers five tips for coping during the pandemic. In this space, I'm going to quote moments from the video, and you can practice classifying the claims and describing how the studies would have been conducted. The first three of these tips are also covered in this story from the World Economic Forum.

Tip 1: Keep social, even when socially distancing

Dr. Santos states in her segment that "Happy people spend more time with other people in general. They also prioritize time with their friends and family members"

a) What kind of claim is it to say that "happy people spend more time with other people in general"--frequency, association, or cause?  What are the variables in this claim? 

b) What kind of study was likely conducted to support this claim--correlational or experimental? 

c) Sketch a scatterplot with well-labeled axes that could depict this result.

Tip 2: Help others

To explain this tip, Dr. Santos mentions, "The research shows that doing random acts of kindness...can be incredibly powerful." For example, happy people are giving money to charity and volunteering in their communities. 

d) What kind of claim is it to say that "doing random acts of kindness...can make you happy"--frequency, association, or cause?  What are the variables in this claim? 

e) What kind of study would need to be conducted to support this claim--correlational or experimental? 

f) Can you imagine how you  might manipulate the variable, "doing random acts of kindness?"

Tip 3: Move--even if you can't leave your house

In this section, she says, "Exercise and moving your body is really correlated with improved well-being"

g) The verb, "correlated" gives this one away: It's an association claim. Dr. Santos specifies that they are "really correlated," which seems to suggest a strong effect size. What factors do we consider when we're trying to decide if a correlation (an effect size) is strong versus weak?

Tip 4: Savor everyday pleasures

"Research suggests that happy people tend to be more mindful. They tend to savor the present moment; they tend to be in the present moment"  Here Dr. Santos also strongly recommends taking deep breaths to calm the vagus nerve and connect to the present. 

h) How might you design an experiment to test the hypothesis that deep breathing can improve people's well-being during quarantine? Whom might you recruit for such a study? How would you operationalize each of the two variables? What results would you expect to find? 

Tip 5: Think about how you want to look back on this time

Finally, she shares one of my favorite tips for emotional regulation, psychological distancing: "Psychological distancing is the idea that if we think about ourselves and how we will have dealt with this crisis in the future...Think about how you want to tell your grandkids you lived through COVID-19, you don't want to be like, 'I panicked-bought and hoarded toilet paper..no, you want the story to be positive...'"

Experimental research has supported the causal claim that self-distancing--seeing yourself as though you are a fly on the wall, or even imagining looking back on yourself from the future--is associated with improved emotional regulation. It helps us take a cooler, less impulsive view of our emotions and process them instead of ruminating. For example, self-distancing helps people manage feelings of anger in constructive ways (here's a nice summary). 

i) Review the term translational research in your textbook (Ch 1) and explain how we might conduct translational research on psychological distancing during the pandemic. What is the basic research it is based on? What is the real-world context it's being translated to? And what kind of study could translate--that is, bridge the gap--between the two? 

 

 

 

 

 

 

Does this font make me look conservative?

Of these three candidates, Yang is considered more liberal than Klobuchar. Do the fonts used in their posters convey that? Photo credit: Kevin McGovern/Shutterstock

Here's something I never considered--different fonts lean conservative or liberal. 

Serif fonts have little curves and edges (like the "Amy" in the green poster here). Sans-serif fonts are cleaner, without these extra flourishes. 

A study showed multiple fonts to a sample of people and found that people rated the serif fonts as looking more conservative and sans-serif fonts as more liberal.

This research was covered by CNN.com. They summarized the results like this: 

For example, study participants saw Times New Roman as more conservative than Gill Sans. Blackletter, which looks like it belongs on a newspaper masthead, was seen as the most conservative font, while Sunrise, a cartoonish-looking script, was seen as the most liberal.

When they interviewed the researcher, she suggested, 

"If you think about serifs being used in more formal types of print or communications, maybe they're viewed as more traditional and sans serifs are viewed as more modern," Katherine Haenschen, an assistant professor of communications at Virginia Tech and the lead author of the study, told CNN. "There's a small but significant difference in how people perceive these fonts."

The researchers showed each font using a simple sentence, "The quick brown fox jumped over the lazy dog" and asked online participants to rate the font's conservative (vs. liberal) nature. For example:

The quick brown fox jumped over the lazy dog

The quick brown fox jumped over the lazy dog

The quick brown fox jumped over the lazy dog

a) In this study, what was the independent variable (IV)? What were its levels? What was the dependent variable? 

Here is CNN's description:

...987 participants were shown the phrase "The quick brown fox jumped over the lazy dog" in one of six fonts and styles: Times New Roman regular, Times New Roman bold, Times New Roman italic, Gill Sans regular, Gill Sans bold or Gill Sans italic.

b) Based on this description, was the IV manipulated as independent groups or within-groups? 

c) You could do the study either way. What are the advantages and disadvantages of manipulating the font variable as independent groups?What are the advantages and disadvantages of manipulating the font variable as within-groups?

d) What does it mean when the author says "There's a small but significant difference in how people perceive these fonts."? 

At the end of the story, the CNN journalist wrote about the potential applications: 

For example, if Bernie Sanders changed the font on his campaign materials, there probably wouldn't be much of a difference in how people see him because he's already a widely known figure.

The choice of font could, however, make a difference for a new candidate, like someone running for school board, town council or state legislature, Haenschen said. While researchers don't know for sure whether a font would change people's perceptions of a candidate, that's another question that could be explored in the future.

e) How might you conduct an experimental test of the journalist's speculation, above? 

You can see the empirical journal article here. Their Figure 1 shows ratings of conservatism and the 95% CIs for six fonts. 

 

 

Research on Native American mascots

The College of William and Mary has phased out its Indian-themed mascot over the years. In 2010, the College replaced its former mascot with "Griffin", above. Photo: Mitchell Layton/Getty Images

Since 2005, the NCAA has required colleges and universities to reflect upon, and if necessary, change sports team mascots that feature depictions of Native-Americans.  Now a team of psychology researchers have published an investigation about support for such mascots among different groups of people. The set of studies  includes both correlational and experimental designs, including one testing whether the mascots can affect people's donations to the universities. 

The lead researcher, Dr. Michael Kraus, told a journalist what led to his interest in the research question. 

“I was at the University of Illinois at the time, and despite their Native American mascot being officially discontinued in 2007, it was surprising to see the mascot on campus in 2013. The continued presence said something about the norms on campus, and what kinds of students feel safe and welcome there,” Kraus said.

The journalist summarized two studies conducted by Kraus and his team. Here's the first:

In a survey of 201 students, the researchers found that those with lower levels of explicit prejudice toward Native Americans reported lower levels of belonging at the University of Illinois.

In other words, students who disagreed with statements such as “It is now unnecessary for the U.S. government to honor their treaty obligations to Native tribes” also tended to disagree with statements such as “I identify with the university” and “I show school spirit regularly.”

In addition, students with higher levels of explicit prejudice, as well as white students, were more likely to have positive views of the retired “Chief” mascot.

Questions

a) This is a bivariate correlational study. What are its two main variables?

b) The journalist gives some clues about how each of these two variables was measured. What kinds of measurements were used--self-report? physiological? observational? What do you think of the items? 

c) Sketch a scatterplot of the results that are described. Label your axes carefully.

d) Can this study support the causal claim? Why or why not? (Apply the three causal criteria; when you come to internal validity, specify at least one third variable that might be associated with both measured variables.)

The empirical article contains several studies on this topic. One of them tested the impact of  the University of Illinois' retired mascot, Fighting Illini, on donations to the school. 

The experiments showed that stereotypic Native American imagery “reduced actual donations to the institution by 5.5%, and was particularly likely to decrease (increase) donations among those low (high) in prejudice,” the researchers wrote.

In the study, researchers had online participants read about different universities, one of which was the University of Illinois. Some participants  were randomly assigned to see the Native American mascot, Chief Illini, next to the school name, while some did not.  Then participants had the chance to distribute $2 in donations to the four universities. When people had been exposed to the  Native American mascot, donations to the University of Illinois decreased. 

But like all research, the study includes some caveats. “Probably the biggest one is that we really only studied these dynamics at the University of Illinois, but we expect these norms to operate similarly everywhere. Someone, maybe us, needs to do that additional work,” Kraus said.

More Questions

e) Is the donation study an experiment or a correlational study? What are its two main variables?

f) When Kraus states that "we expect these norms to operate similarly everywhere," to which of the four big validities is he referring?

You can access the empirical research here.

Instructors: The complete package of studies is a complete set with a frequency claim (via an observational study of mascot use on campus) , a correlational study, and an experimental study.

 

 

 

 

Interested students might learn from Dr. Stephanie Fryberg's work, showing how American Indian high school students respond to being reminded of professional sports mascots that feature American Indians.

Fidget spinners seem to cause worse memory and attention

The fidget spinner IV was manipulated as independent groups in the first study and as within groups in the second. Photo: Marcel Jancovic/Shutterstock

Fidget spinners were extremely popular a couple of years ago. When people promoted them, they often suggested that the toys could help people with ADHD focus and learn more. At the time, such claims were not scrutinized empirically (here's a nice summary of this lack of evidence). It takes time for empirical research to be conducted, analyzed, peer-reviewed, and published, and even though fidget spinners were hot in 2017, we now have a study that tested the effect of using a fidget spinner during a learning task. At least one press outlet covered this study. Here's their summary:

In the first experiment, 98 undergraduate students watched a 15-minute educational video lecture on baking bread while either using a fidget spinner or not using a fidget spinner [randomly assigned]. In addition, half of the participants not using a fidget spinner were randomly assigned to watch the lecture while sitting near someone using a fidget spinner.

A fill-in-the blank memory test showed that participants who used fidget spinners answered significantly fewer questions correctly about the material covered in the video. Participants who used fidget spinners were also more likely to report “zoning out” and having difficulty staying on task while watching the video.

Participants who were sitting near someone using a fidget spinner, however, did not appear to be affected.

Questions

a) This was an experiment. How do you know?

b) What were the IV and DV? How many levels were in the IV and what were they? Was the IV manipulated as independent groups or within groups? 

c) Which of the four simple experiments is this: postttest-only? Pretest-posttest? Repeated-measures? Concurrent measures? 

d) The journalist attached a causal claim to these results, saying "study finds using a fidget spinner can impair memory and attention." Apply the three criteria for causation to this claim to explain why the causal claim is probably valid. How does random assignment assist this study's internal validity?

e) Ask one question each about the study's statistical, construct, and external validities. 

The researchers replicated the effect in a second study. The wondered if fidget spinners might only work among people who believed in their powers: 

The researchers then conducted the experiment again. However, this time around they specifically recruited 48 undergraduates who believed that fidget spinners could help them focus in class.

But the results were the same.

According to the empirical journal article, the second study on 48 students was conducted as a repeated measures design, using two videos. Students used a fidget spinner during one video and no spinner during the other one. Students were tested on their recall for the videos after each one.

f) What are the IV and DV in the second study? How many levels were there in the IV?

g) How do you think the researchers used counterbalancing in this second study?  Why would that have been important? 

You can access the original empirical article here, though you may need to log in via your university library. 

 

 

 

 

 

Racial stereotypes behind how we explain school shootings

Participants and newspapers were more likely to blame video games when a school shooter was white than when he was black. Photo: Richard Levine / Alamy Stock Photo

What causes mass shootings? Of course, we have no experimental evidence on this question. Correlational evidence (both within the U.S. and evidence that compares the U.S. to other countries) is consistent with the argument that gun availability is a factor. 

However, this post isn't about what really causes school shootings. It's about what people think causes them. And it turns out that the race of a school shooter influences what people believe about the shooter. 

After some school shootings (a subset of mass shootings), people have sometimes looked for answers not in the availability of guns, but in video games. Now, there is actually no evidence linking video games to mass shootings. However, this ABC news story talks about when people are more likely to think that video games are responsible: 

There's little evidence showing a relationship between violent video games and school shootings, but video games are often blamed for overall violence in our communities. A recent study published in the Psychology of Popular Media Culture set out to find if we look for an external explanation for violence by whites more often than we do for African Americans.

"We try harder to make excuses for white perpetrators," said investigator Dr. James Ivory, a professor in the Department of Communications at Virginia Tech, in an interview with ABC News.

The first study gave people a mock news story about a school shooting. When asked what caused the shooting, people were more likely to blame video games if the shooter was white than if the shooter was black.

It turns out that in the original study (linked here;  if it's paywalled you may be able to access via your university library), participants read the mock news story and were randomly assigned to one of two photos of the perpetrator--a mugshot showing either a Black or a White man. 

a)  There were two variables in this study. Name each one. For each, was it manipulated or measured?

b) What kind of study is this, correlational or experimental?

c) Sketch a graph of the results of this study. What will you put on the y-axis? 

d) In the study above, what role does random assignment play? Why did the researchers randomly assign people to see either a Black or White perpetrator?  

 

Here is how ABC news described the second study:

The second study looked at thousands of news articles -- video games were mentioned more often in stories of white shooters [compared to black shooters]. 

e) What are the variables in the study above? Name each one; for each, was it manipulated or measured?

f) What kind of study is this, correlational or experimental?

g) Sketch a graph of the results of this study.

h) In the study above, the researchers could not randomly assign news article authors to write about a black vs. a white perpetrator. How does that change the impact of this study? 

i) Which of the two studies do you think provides the strongest evidence that race influences people's willingness to think video games are a cause of the shooting?

 

Suggested answers

a) One variable is race of the perpetrator (levels are Black or White), this was manipulated. The other variable is "likelihood to blame video games". This was measured.

b) This was an experiment because one variable was manipulated. 

d) Random assignment contributes to the study's internal validity. They can be sure that the same kinds of participants were in each group (reading about Black vs. White perpetrators). Therefore, people who play a lot of video games themselves were equally likely to be in the two groups. You might be interested to know that in the original study, the researchers also pretested the Black and White photos they used to be sure that the faces differed on race but not on perceived attractiveness or dangerousness. This pretesting also contributed to the experiment's internal validity.

e) The first variable was race of the perpetrator in the article (Black or White), which was measured. The second variable was whether or not the article mentioned video games (yes or no).

f) This was a correlational study because all variables were measured. 

h) Because this study used naturally-occurring crimes, the researchers may have an internal validity problem. It is possible that the Black and White perpetrated shootings differed not just on race but also on number of victims, age of victims, geography, or some other variable. This introduces an alternative explanation for the result--perhaps people blamed video games for White perpetrated shootings because they had more victims, had older victims, and so on.

i) You might have selected the first study as the strongest because it was an experiment and allows us to make a causal inference. Or you might have selected the second study because it was conducted on "real world" stimuli such as news stories--therefore it appears to have good ecological validity or external validity. 

Thanks to Marianne Lloyd for this idea!

Can Probiotics Actually Treat Obesity?

 

Should you be suspicious of a study conducted by a company that produces probiotics products? Photo: Science History Images / Alamy Stock Photo

Guest post by Dr. Dina Gohar, University of Michigan

 

Hippocrates, considered to be the Father of Medicine, reportedly said, “all disease begins in the gut. ” It took doctors centuries to start studying the connection between our gut microbiota and our health, which is now well-supported by research. We can improve the health and diversity of our gut microbiota with active strategies, such as exercising regularly, eating a healthy diet, and getting enough sleep. We might also be able to improve our gut microbiota by simply consuming live “good” bacteria and microorganisms called probiotics. Probiotics are now sold as capsules, pills, and powders, added to fruit juices, granola bars, and candy, and even put into cosmetics. Fermented foods, such as cultured yogurt, sauerkraut, and kombucha, contain them too. A cloud of hype and hope surrounds probiotics, which have been touted as a treatment (and means of prevention) for everything from intestinal disorders, mood and anxiety disorders, belly fat and obesity-related disorders. 

A recent article in the New York Times suggested that a probiotic of heat-killed bacteria can treat metabolic disorders like obesity. This suggestion was based on a study in Nature Medicine.The  New York Times journalist summarized the study as follows:

Researchers tested the bacterium, Akkermansia muciniphila, in 32 men and women who met the criteria for metabolic syndrome by having at least three of five conditions: high fasting blood sugar, high blood pressure, high triglycerides, low HDL (the “good” cholesterol) or excessive waist circumference.

…In a three-month trial, volunteers were randomized to one of three groups: daily tablets containing live bacteria, pasteurized bacteria [A. muciniphila] or a placebo. Compared with the placebo group, those who took pasteurized A. muciniphila had significantly improved insulin sensitivity and total cholesterol, and decreases in several blood markers of inflammation and liver dysfunction. They also had decreased body weight, fat mass and waist circumference, though those differences were not statistically significant. The live bacteria were largely ineffective.

1. This study was an experiment. What is the independent variable (IV) and what are its levels? What are the dependent variables (DV)? What do you think of the outcome measures chosen for this study?
   
   
2. How was the independent variable manipulated:  between or within groups? Which of the four basic experiments is it probably an example of: Pretest/postttest design? Posttest-only? Repeated measures? or Concurrent measures?
   
   
3. Can the results of this study be used to support the causal claim that “Taking pasteurized bacteria can improve people’s insulin sensitivity and total cholesterol?” Why or why not? (Apply the three criteria for causality.)
4. Look at the sample size of this study; do you think it’s a problem? Why or why not? Which of the four big validities does the sample size best fit into? 
5. Do the results above support the claim that probiotics like A. muciniphila can treat obesity? Why or why not? (Is internal validity relevant here? What about construct validity?) Can you conclude that probiotics can help you lose weight? Why or why not?
6. The New York Times article critically failed to mention that the researchers who conducted this study have a patent on the probiotic treatment and even started a company based on it. What do you think about this potential conflict of interest? 
7. Do you think it matters that this study’s somewhat promising findings were only with dead bacteria, whereas probiotics are generally defined as being live bacteria? Why or why not? (Which of the four big validities is being asked about in this question, if any?)
   
   

You might agree that the probiotic study described by this journalist has a few serious problems. For an example of probiotic research done right, check out this NPR news story on a current clinical trial examining if a specific probiotic could eliminate specific GI problems in children on antibiotics (courtesy of Dr. Jess Hartnett’s statistics blog).