Everyday Research Methods

Claim: "Going to museums and concerts helps you live longer"

Does the study's method support the claim that attending arts events makes you live longer? Photo credit: agefotostock/Alamy

We'll never run out of material in the "correlation is not causation" department. 

This time, a New York Times  journalist led with the headline, "Another benefit of going to museums? You may live longer." 

Let's check out the study behind this causal claim. 

According to the journalist's summary of the empirical article, 

Researchers in London who followed thousands of people 50 and older over a 14-year period discovered that those who went to a museum or attended a concert just once or twice a year were 14 percent less likely to die during that period than those who didn’t.

The chances of living longer only went up the more frequently people engaged with the arts, according to the study, which was published this month in The BMJ, formerly The British Medical Journal. People who went to a museum or the theater once a month or even every few months had a 31 percent reduced risk of dying in that period, according to the study.

a) Starting just from here--what are the two variables they've mentioned so far? Were they manipulated or measured? 

b) Based on what you've read so far, is this study correlational or experimental? 

c) Without reading further, think of a third variable (a "C") that is likely to be correlated with both A (going to museums or concerts) and B (being less likely to die). Any good ideas? 

OK! Time for more information about the study from the journalist:

The study controlled for socioeconomic factors like a participant’s income, education level and mobility, said Andrew Steptoe, a co-author of the study and the head of University College London’s research department of behavioral science and health.

“Even if you take those things into account, we still found that there is a difference in the survival of people who are involved in the arts,” Professor Steptoe said in an interview on Friday.

 

Sounds like multiple regression was used here.

d) What was the criterion (dependent) variable in this study now?

e) What were the predictor ("independent") variables? 

f) Sketch a little regression table similar to those in Chapter 9--put the criterion variable at the top and the predictors at the bottom. Which betas do you think were significant?

g) More importantly, was the "C" variable you thought about in c), above, controlled in their regression?

h) Even though the authors controlled for income, education, and mobility, there are likely to be additional third variables that were NOT controlled for. Think of at least one more alternative explanation. 

 

As you learn in Chapter 9, regression does not support causation because even though it can control for alternative explanations you can think of (such as income, education, or mobility), it doesn't control for everything. If you read the Time's summary, you'll see even more variables they seem to have controlled for , such as marital status and profession. But there could still be unmeasured variables that are responsible for the relationship. 

 

But that doesn't stop the authors from making causal speculations. In fact, here's a mediator hypothesis. i) Sketch this mediator following the diagrams at the end of Chapter 9:

 

The study also noted that engaging in the arts can reduce loneliness, promote empathy and emotional intelligence, and keep people from becoming sedentary — all factors that contribute to a longer life.

 

What kind of study would you need to conduct to test this proposed mediator?

 

 

 

 

 

 

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.