Everyday Research Methods

Should scientists change out of pajamas?

Does the study's design support the causal claim the journalist attached to it?
Photo credit: R.O.M/Shutterstock

Some journalists simply cannot resist attaching a causal claim to a study where it doesn't belong. Here's an example from the trade magazine, Inside Higher Ed, which reprinted a piece from Times Higher Education. The headline reads, "Scientists urged to change out of pajamas." 

The first paragraph begins:

Academics who are tempted to remain in pajamas during the working day should think again, says an Australian study that has linked the practice to a deterioration in mental health.

 

a) There are actually two claim-like statements in the first paragraph. What are they? (Remember that advice is a form of causal claim). 

b) What seem to be the two variables in the association and causal claims above? 

The journalists summarizes the study this way: 

The study, which drew on 163 responses from staff at five medical institutes in Sydney, also delved into the reality of working at home for researchers. [...]

Some 28 percent of scientists said they wore pajamas at least once a week -- a cohort who were twice as likely to report worsened levels of mental health than those who dressed normally each day, according the study, by David Chapman and Cindy Thamrin [...]

Given the survey format of this study, we can assume that all the variables in this study were self-report. To learn more about this relatively simple study, you can visit the open-access original journal article here, and you can see the full, original text of the survey here. 

Let's work through the four big validities. 

c) Construct validity: Look through the original survey (here) and find the variables that measured pajama-wearing and mental health assessment. What do you think--how well do these variables seem to be measured? (Guess what? You're assessing face validity.) 

d) Construct validity: When you view the original text of the survey (still here)  you might be a bit surprised by the lighthearted tone of some the survey questions. For example, they ask about the "typical home working environment" they included the option, "hiding in the bathroom." When they asked people what they wear during remote meetings, one of the options was, "none of your business, camera turned off."  How might this casual tone affect the construct validity of the variables being measured? Do you think it will it affect the accuracy of self-reports?

e) External validity: The journalist refers to "scientists", so that seems to be the population of interest. The sample was described this way by the journalist:

The study, which drew on 163 responses from staff at five medical institutes in Sydney...

In the empirical article, there is more detail about the sample: 

An invitation to participate was emailed to all staff, students and affiliates of the Woolcock Institute of Medical Research, Sydney, and later extended to other medical research institutes in Sydney (Garvan Institute, Children’s Medical Research Institute, Centenary Institute, Brain and Mind Centre).

Can this study generalize from this sample to the population of interest? Why or why not? (Don't be tempted to focus on the size of the sample here. Remember that it's not the size that matters for external validity)

f) Statistical validity: Here is the effect size of the relationship between wearing pajamas and mental health: 

[people who wore pajamas at least once per week] were twice as likely to report worsened levels of mental health than those who dressed normally each day

In the empirical article, the rates of poorer mental health were described as 59% (for pajama-wearers) vs. 26% (for non-wearers). What do you think of the strength of this effect? What more information would you like that is relevant to statistical validity?

g)  Internal validity. Let's evaluate whether the study can support the causal claim, "wearing pajamas put the scientists at risk for poorer mental health?" In order to support a causal claim, we need to conduct an experiment. Was this an experiment or a correlational study?  Explain your answer. 

h) Internal validity: Now let's apply the three criteria for causation. 

The study does show covariance, because people who report working in pajamas did have twice the rate of mental health decline, compared to those who did not.

What about temporal precedence? Does the method establish which variable came first in time? 

What about internal validity? Can you think of a third variable (some "C" variable) that might be associated with both wearing pajamas and having worse mental health? 

Now make a conclusion--does the study support the advice to "change out of pajamas?"

i) How might you design a true experiment to study the potential causal effect of pajamas on mental health? What variable would you need to manipulate? What variable would you need to measure? 

 

 

 

Frequency claims: Fitter and better rested during lockdown

One of the positive changes people reported was being able to spend more time with family. Photo: Steve Skjold / Alamy Stock Photo

The first peer-reviewed studies about the COVID-19 pandemic  are starting to appear in journals, and journalists are starting to summarize them in the popular press.

Let's explore this summary of a survey study conducted in Scotland and summarized for a general audience by the scientist herself, in The Conversation. The scientist writes, 

 ... for some people lockdowns have provided an unexpected opportunity to make positive changes to their lives...

Here are some details: 

In May 2020, my colleagues and I surveyed over 3,000 people in Scotland to find out what positive changes people had made in their lives during the lockdown period. 

And some of the key results:

More than half the people we surveyed reported these changes for the better: being more appreciative of things usually taken for granted (reported by 83% of participants), having more time to do enjoyable things (by 67%), spending more time in nature or outdoors (by 65%), paying more attention to personal health (by 62%), doing more physical activity (by 54%) and spending more time with a partner or spouse (by 53%).

Each of the above results constitutes a frequency claim, because it talks about the level, or percentage, associated with one variable. Consider this one, for example: "doing more physical activity (by 54%)". The variable here is "doing more physical activity under the lockdown (or not)."

Now let's use the four big validities to systematically interrogate this frequency claim, "54% of people in this Scottish survey reported doing more physical activity during the lockdown." 

a) Construct validity: How do you think they measured the variable "doing more physical activity"? (Self-report? Observational? Physiological?) . What are your initial impressions of, or questions about, how well this variable was measured? 

b) Construct validity: Let's say you wanted to establish the criterion validity (See Ch 5) of the (presumably self-report) measure of "doing more physical activity".  What behavior should self-reports of this variable correlate with, if the self-report measure is valid? 

c) Statistical validity: The point estimate, 54%, is one element of statistical validity. What about the precision of this estimate? That is, what is the 95% CI, or margin of error of this estimate? It's not provided in the article, but you can visit this calculator to estimate the CI. Do that now. 

d) Statistical validity:  Replication is another aspect of statistical validity. The scientist-author cites at least one more, similar study that came to a similar conclusion: 

An Australian study (still in preprint, meaning its findings are yet to be reviewed by other scientists) also sought to find out similar information. In a survey of over 1,000 people, it found that 70% of participants reported having experienced at least one positive effect of the pandemic. 

e) External validity:  The sample for this survey was N =3000. Don't get distracted by the size of the sample (remember--it's not the sample size that helps establish external validity). Instead, what do you need to ask in order to decide whether the study's sample can generalize to their population of interest (Consult Ch 7)?

f) External validity: I visited the peer-reviewed article (here--open access) and found this information about their sampling technique.

The target population of the survey was adults, aged 18 years or older, currently residing in Scotland, who were interested in sharing their experience of positive change. Participants were primarily recruited through social media advertisements on Facebook and Twitter which directed participants to the online survey on Qualtrics. 

What kind of sampling did they apparently use in this study? (Name a sampling technique that is discussed in Chapter 7). 

What is their population of interest?

Does the sampling technique they used allow them to generalize from their sample to their population of interest? Why or why not? 

g) Internal validity: In a frequency claim, nobody is making a causal statement, so we don't actually need to interrogate internal validity.

h) Now that you've looked at all four validities, what do you think about the quality of this study? Make a nuanced comment about its strengths and weaknesses. 

 

P.S. Thanks to Marianne Lloyd for the reference!