Everyday Research Methods

Claim: Mothers' friendships are good for babies' brains

The study showed that moms with larger social support networks had kids with higher cognitive test scores. Photo: Noriko Cooper / Alamy Stock Photo

The  Washington Post headline reads, "Mothers' friendships may be good for babies' brains."  The story is about an empirical study on mothers' social networks. Although it says "babies' brains", the study measured the babies' cognitive skill (there were no baby brain scans). The empirical article came out in JAMA Network Open. Does the original study support the claim? Let's find out.Before reading on, answer these questions:

 

a) What are the two variables in the Washington Post headline claim? What makes the claim a causal one? 

b) Of course, we need to conduct an experiment to definitively support a causal claim. Would an experiment be possible in this particular case?  

Here are some details about the study, as summarized by the journalist (not the researcher):

For the current study, researchers examined data on 1,082 mother-child pairs. They questioned women about their family structure, friendships and relationships in their communities and also looked at test results from cognitive assessments done when children were 2 years old.

Overall, mothers had an average of 3.5 friends in their social support networks. The kids of mothers with more than that tended to have higher cognitive test scores than the kids of those who had fewer, suggesting “network conditions were significantly associated with early cognitive development in children,” the study authors wrote.

c) Sketch a  simple scatterplot of the result described above. What will you put on the two axes? How many dots should your scatterplot have? What does one dot represent? 

Read the following details if you've studied Chapter 9: 

The researchers accounted for some factors that might influence child cognitive development, including mother’s age and IQ, father’s education level, and the child’s birth weight. 

In addition, "researchers also accounted for poverty levels"

d) The paragraph above is describing a multiple regression analysis. What would be the dependent (criterion variable) in this analysis? What are the predictor variables? (Hint: There are six predictor variables).

e) Imagine that someone proposes income as a possible internal validity problem. Given what you know about the study, can we say that "Perhaps friendship network size and child cognitive skills are correlated because of the third variable of income: That is, higher-income mothers may have more friends and more cognitively skilled children"?  Would this criticism be reasonable? Why or why not?

f) The journalist writes: "...they did not have data to assess other personal differences, such as history of depression, between mothers with large networks of friends and those with fewer."
This means history of depression could be a possible third variable explaining the relationship. How could the researchers rule out this third variable? 

The journalist writes: 

All of the families in the study lived in the area around Memphis. It is possible that results might be different elsewhere.

g) Which big validity is the journalist addressing in the statement above? 

h) Do you think the correlation between friendship and cognitive test scores would actually come out differently in a different city or country? Why or why not? 

 

Suggested answers:

a) The two variables are Amount of mothers' friendships and Level of health of babies' brains. The language of "may be good for" makes this a causal headline (remember we ignore adverbs such as "may" when classifying claims). 

b) Probably not; you'd have to randomly assign some mothers to have more friends and others to have fewer friends.

c)  One axis should have "number of friends" and the other should have "cognitive test score". There should be about 1082 dots on the scatterplot (better count your dots now...), and each dot represents a mother-child dyad.

d) The criterion variable is cognitive test score. The predictor variables are number of friends, poverty levels, mother’s age, mother's IQ, father’s education level and the child’s birth weight. 

e) Since the researchers did control for poverty levels, we can actually rule out wealth as a possible third variable. 

f) the researchers could obtain history of depression data on each mother and then add this variable as a predictor variable to the regression analysis. If the beta associated with "number of friends" is still significantly predicting cognitive test score, then we can rule out this possible confound (/third variable/ internal validity problem).

g) external validity

h) In my opinion, it seems unlikely that such a relationship is limited only to Memphis residents. 

Note: You can read the original empirical article in JAMA, here. Note to savvy instructors: The p-curve on the results in this paper suggests that there may be little evidentiary value. 

More butter, happier citizenry

What internal validity problems prevent us from claiming that butter leads to happiness? Photo: Fatty's place/Shutterstock

A writer for the Big Think wrote about how "Butter supply and life-satisfaction are linked".  It's a dairy interesting story with perfect scatterplots for practicing correlational designs.

Writer Frank Jacobs used the following bullet-points to open his story: 

• Haiti and other countries with low butter supply report low life satisfaction.
• The reverse is true for countries such as Germany, which score high in both categories.
• As the graph below shows, a curious pattern emerges across the globe. But is it causation or correlation?

You should click on the story and scroll down to the first scatterplot. 

a) What does one dot represent on this scatterplot?

b) What kind of correlation is being represented here: positive, negative, or zero?

c) Find your own home country. Is your country above the median or below the median on butter supply? Is your country above the median or below the median on life satisfaction? 

d) What would happen to the scatterplot if it were drawn with butter supply on the y-axis and happiness on the x-axis? Would it have the same shape and slope? 

The writer states:

Yet as the map shows, an abundance of butter does make people happy. Or could it be a case of correlation instead of causation? In that case, something else influences both life satisfaction and the availability of butter to go up and down together. 

d) In the curious paragraph above, the writer makes a clear causal claim. What is it?

e) After making the causal claim, the writer backs off, stating that "something else" could be associated with both life satisfaction and the availability of butter. He's talking about third variables here--or internal validity. What possible third variables might plausibly be correlated with both butter supply and life satisfaction in the world's countries? 

To help you consider possible third variables, zoom in on the countries that are in the lower left and upper right quadrants of the butter scatterplot. What dimension seems to separate the countries in those two quadrants? 

f) Take a look back at the column in Big Think. Is this data (and scatterplot result) from a published, peer reviewed study in an empirical journal? 

I butter thank Sue Frantz of Highline College for sharing this story with me.