Everyday Research Methods

The science behind sleep

The science on sleep suggests that most of us need more of it!
Photo: Carlos Caetano/Shutterstock

A Washington Post article recently proposed that lack of sleep might be a "public health crisis." The journalist's story covered several types of empirical studies and made a series of frequency, association, and causal claims. 

Here are a series of quotes from the article. As you read each quote, ask yourself, a) How many variables seem to be involved in this claim? b) What is/are the variable(s)?  and then c) Is this claim frequency, association, or cause? How do you know? (Note: the links in each claim take you to the empirical articles on which they are based.)

Quote 1:

"Preschoolers who skip naps are worse at a memory game than those who snooze."

Quote 2:

"...a single night of sleep deprivation boosts brain levels of the proteins that form toxic clumps in Alzheimer’s patients." 

Quote 3:

"In 2016, the Centers for Disease Control and Prevention reported that a third of adults fail to get the recommended seven hours."

Quote 4:

"...even modest sleep reductions are linked to increased feelings of social isolation and loneliness."

Quote 5:

"A small study presented at the Society for Neuroscience conference last year found early evidence that playing “pink” noise — similar to white noise but with different frequencies — in a specific pattern could increase the proportion of time people spent in restorative deep sleep."

Quote 6:

"Adults over 50 with lots of insomnia symptoms were more likely to fall than those without, according to one study.:

Quote 7

"Studies have linked pain to poor sleep.."

 

Suggested answers to odd-numbered quotes.

Quote 1.

1. There are two variables:
2. Skipping a nap (or not) and level of skill at a memory game
3. This is an association claim, because the verb “are” is simply linking one type of preschooler (those who skip naps) with having lower skill at the memory game.

 

Quote 3.

1. There is one variable:
2. Getting 7 hours of sleep a night (or not)
3. This is a frequency claim. There is one variable and the sentence is mainly describing the number of U.S. adults who get that amount of sleep.

 

Quote 5.

1. There are two variables:
2. Playing “pink” noise (or not) and amount of time spent in restorative sleep
3. This is a causal claim because the verb used was “increase”.

 

Quote 7.

1. There are two variables:
2. Level of pain and quality of sleep.
3. The verb, “linked” is a verb signaling an association claim.

Which comes first? Cross-lag study on depression and social media use

Which comes first, social media use or depression? Photo:Africa Studio/Shutterstock

We have seen multiple studies that have tried to estimate how strong the link is between social media use and depression among young adults. We've covered some of these studies on this blog, including the effect size of the correlation and even a brain imaging study that manipulated "likes."

One challenge with studying real-world links between social media use and depression is that most use correlational designs. Therefore, we can't be sure whether any link between social media use and depression means that social media leads to more depression, or if depression leads to more social media use. And of course, in correlational studies there may even be a third variable, such as age, which is associated with both variables and causing them to appear correlated. 

The latest study used a longitudinal, cross-lag panel design, such as those described in Chapter 9, to study this question. Here's a writeup of the study by a journalist at Earth.com.

First, here are some comments about the design: 

The researchers point out that previous studies that found links between depression and social media use among tweens are limited in their results because they only captured a snapshot of teen social media use.

“You have to follow the same people over time in order to draw the conclusion that social media use predicts greater depressive symptoms,” said Taylor Heffer, the lead author of the study. “By using two large longitudinal samples, we were able to empirically test that assumption.”

Here are some more details about the method. They actually used two longitudinal samples: 

For this study, the researchers conducted a two-year longitudinal study surveying 6th, 7th, and 8th graders in Canada. The team also surveyed a series of undergraduate students once a year for six years as they progressed through college.

What were the results? 

Higher depression symptoms predicted social media use among teen girls which indicates that unhealthy social media use may be a symptom depression, not a catalyst for it.

“This finding contrasts with the idea that people who use a lot of social media become more depressed over time. Instead, adolescent girls who are feeling down may turn to social media to try and make themselves feel better,” said Heffer.

Questions

a) In a cross-lag panel design, researchers measure the same two variables in the same sample of people over time. What are the two variables they focused on here?

b) Sketch a series of boxes depicting the design of the study, similar to the figures in Chapter 9's cross-lag panel section. How many time periods would you need to depict for the undergraduate sample? 

c) Focus only on the girls. What do you think the autocorrelations might have been in this design? Fill those in on your sketch.

d) Still focusing only on the girls, given the description of the results, estimate what the two cross-lag correlations might have been. Which correlation should be larger--the one from Time 1 depression to Time 2 social media, or the one from Time 1 social media to Time 2 depression?