Everyday Research Methods

Evidence-based tips for procrastination

What do the studies suggest about why people procrastinate? Photo credit: Timothy Hodgkinson/Shutterstock

The BBC magazine, Science Focus, collected a set of studies on procrastination that might help students at the beginning of a new school year.  The journalist opens with a couple of simple frequency claims. 

[If you procrastinate,] you’re not alone: an estimated 20 per cent of adults (and above 50 per cent of students) regularly procrastinate.

Then the article addresses three topics: 1. Is procrastination a sign of poor time management? 2. Is procrastination unhealthy? 3. How can we stop? Let's take each topic and apply some research methods content as we go.

1. Is procrastination a sign of poor time management?

The journalist quoted psychologist Fuschia Sirois, who explained that contrary to what many people believe, procrastinators aren't more likely to be bad at time management. Instead, she explains, it's about emotion regulation:

“At its core, procrastination is about not being able to manage your moods and emotions. Although many think impulsivity and self-control are the problems – and they do play a factor – underneath is a poor emotional response.”

As Sirois explains, every person faces stressful situations, demanding tasks that trigger brain activity that involves a brain region known amygdala. And it’s the amygdala that processes emotions and signals threats, capable of prompting a ‘fight or flight’ response linked to procrastination.

“Interestingly, people who say they are chronic procrastinators tend to have larger grey matter volume in the amygdala,” says Sirois.

“This means they will also be more sensitive to the potential negative consequences of their actions, leading to more negative emotions and procrastination.”

a) What were the variables in the amygdala study? Was this study correlational or experimental? 

b) Sketch a scatterplot (or bar graph) of the results Dr. Sirois describes here.

 

2. Is procrastination "bad for your health"?

The journalist implies causality with this headline, and with lines like these: 

...procrastination can cause a lot more problems than missed deadlines. Over decades Sirois has examined the impact of chronic procrastinating on a person’s health, her findings worrying at best – and downright terrifying at worst.

Let's see if the evidence can support these causal claims. He quotes Dr. Sirois again, who stated, 

“People who chronically procrastinate – people who make it a habit – have higher levels of stress and a greater number of acute health problems. They are more likely to have headaches or insomnia or digestive issues. And they’re more susceptible to the flu and colds.”

Even more alarming, Sirois has found that procrastination is a factor that can lead to hypertension and cardiovascular disease, with chronic procrastinators more likely to put off healthy behaviour such as exercise.

c) Is Dr. Sirois describing correlational or experimental evidence here? (Explain your answer by specifying the variables she mentions).

d) Why can't the evidence described by Dr. Sirois support the journalist's assertions about "the impact of chronic procrastinating"? Specify the temporal precedence problem and the internal validity problems here (when you discuss internal validity, specify a particular third, or "C" variable that might correlate with both A and B). 

3. How can we stop procrastinating?

In this section, the journalist describes some intervention studies targeting procrastination.

For example, one compelling Psychological Science paper described how downsizing larger metrics of time (think 48 hours instead of 2 days, or 10,950 days instead of 30 years) can make events seem more immediate, prompting people to engage in upcoming tasks.

You can follow the underlined link in the quoted text (above) to see that this paper described several experiments (for example, the abstract states, "we manipulated time metric".

e) Given the journalist's description (and the empirical study's abstract), name the independent variable in this experiment and name its levels.

f) Name the dependent variable in this experiment.

g) Sketch a bar graph of the study's result, as described by the journalist. 

h). Because this study was an experiment, it is more likely to support causation.
Think about something you have to do in the near future. How can you apply the results from the Lewis and Oyserman study in Psychological Science to that task, to prevent yourself from procrastinating on it? 

 

Selected Answers

a) One variable was "saying you are a chronic procrastinator or not" and the other was "volume of grey matter in the amygdala". Both variables must have been measured, so this was a correlational study.  

b) One axis should have "grey matter volume in amygdala" and the other should have "level of chronic procrastination"; the scatterplot should have a positive slope, but you don't have information on how strong the relationship was, so you can't really know how spread out the dots should be. 

c) This is likely correlational evidence. They are measuring (not manipulating) people's procrastination habits. They are measuring (one cannot manipulate) people's acute health problems, susceptibility to the flu, hypertension, and cardiovascular disease. 

d) We can take acute health problems as an example. Even if there is an association between chronic procrastination (A) and acute health problems (B), we still don't know if the procrastination led to the health problems (A to B), or if the health problems lead to more procrastination (B to A). In addition, there could be some outside variable such as life stressors or poverty (C) that is associated with both procrastination (A) and health problems (B). 

e) The independent variable is apparently "time metric" and the levels were hours vs. days, or perhaps days versus years. 

f) The dependent variable seems to be "how immediate events seem to be"

g) The x-axis should have hours and days, and the y-axis should indicate "how immediate events seem to be". The bar for "hours" should be higher than the bar for "days". 
This study seems to suggest that if you have homework due in two days, you might be more likely to get started on it if you say to yourself, "My homework is due in 48 hours." 

 

Cat-in-the-box

Pancetta the cat sitting in Kanizsa square. Photo and research by Gabriella Smith, M.A.

I've shared several examples of research on pet dogs on this blog, so it's about time I present an example of research on pet cats.

If you own a cat yourself, you've probably noticed that they enjoy climbing into 3-dimensional boxes, baskets, and other containers. You might also know that cats also seem to prefer "climbing" into 2-dimensional boxes--that is, they are likely to sit in a simple square that has been masking-taped onto the floor. A recent study took a closer look at this adorable behavior as part of a test of whether cats are susceptible to a phenomenon known as the Kanisza contour illusion.

As illustrated in the photo of Pancetta that accompanies this post, the Kanisza contour illusion consists of four Pac-Man-like shapes that, when arranged just so, are usually interpreted by humans as a square. Researcher Gabriella Smith wondered if cats, too, would fall for the illusion, so she created an experiment to test it. 

An interesting aspect of Smith's study was that the cats participated in their own homes, an approach called "citizen science." In other words, the researchers  "let volunteers test their own cats at home in a standardized way and then send in the results".

Here's a description of the research study, as covered by NPR's All Things Considered.(The original empirical study was published in a journal published  by Elsevier, which means it's very difficult to obtain, even through universities.):

Participants received booklets with instructions on how to print out and cut up paper shapes that could be taped to the floor to create three options: the Kanizsa illusion, the actual outline of a square, and a control that had the Pac-Man shapes facing outward. The volunteers were instructed to videotape their cats as they encountered these stimuli in short tests over six days, while the volunteers wore sunglasses to avoid inadvertently giving the cats any signals with their eyes.

Their results? That the cats chose to sit in the illusory square as often as they did the actual outline of a square — and more than the non-square arrangement.

Here are some questions about the study.

a) This was an experiment. What was the independent variable (IV) and what were its levels?

b) What was the dependent variable (DV)?

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

d) Which of the four basic experiments does this study seem to have used--Posttest only? Prettest-posttest? Repeated measures? or Concurrent measures?

e) Sketch a graph of the results that were described (hint--put the three IV groups on the x-axis).

f) In the empirical article, the researchers mention that the presentation of the different IV levels was fully counterbalanced, which means that cats in the study were exposed to multiple trials. Why was counterbalancing necessary, and what might counterbalancing have looked like? 

g) The story mentions that "the volunteers wore sunglasses to avoid inadvertently giving the cats any signals with their eyes.". Which internal validity threat was this designed to prevent?

Now here's a detail about the citizen science aspect of the study:

While hundreds of people signed up for the experiment, in the end the researchers got complete data on only 30 cats..... [Smith] notes the number of people who dropped out of this study and says future efforts along these lines may need to be even shorter and easier to ensure that volunteers are able to complete all the required tasks....This latest study, [in contrast to past work on cats] has the advantage of testing untrained cats in a.... natural setting, 

h) Given this outcome, summarize the pros and cons of the citizen science approach to animal research, perhaps adding some of your own.

i) You might be alarmed that the sample size for this study dropped from hundreds of people to only 30, and you might be tempted to think this study has an attrition threat to internal validity. But attrition isn't an issue for internal validity here--can you explain why? 

 

 

An empirical reason to say "Thanks"

Senders of gratitude letters benefit from writing them, and recipients "feel great" when receiving them. Photo credit: Rawpixel/Deposit Photos

This example comes from the subfield of positive psychology, and the study of gratitude. One technique studied by positive psychologists is the practice of writing a gratitude letter to a person who has influenced you.  According to this summary, "There are two excellent reasons for writing a gratitude letter: It will make you feel really good, and it will make the recipient feel great"

The concept is simple: Write a letter to a person whom you'd like to thank. Gratitude letters can be handwritten or typed, emailed or snail-mailed. The important thing is to send them. Gratitude letters can help both the writers and the recipients. 

First, here's the journalist's description of a study about the benefits of writing these letters:

Scientists randomly assigned the 293 participants to three groups: Those receiving psychotherapy, those receiving psychotherapy and participating in expressive writing, or those receiving psychotherapy and participating in gratitude-letter writing. Even in the small study, participants in the gratitude group reported significantly better mental health than the other two groups, even three months after the trial ended.

a) What is the independent variable (IV) in the study above?  What are its levels?

b) What is the dependent variable? 

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

d) What kind of experiment was this? Posttest only? Pretest-posttest? Repeated measures? or Concurrent measures? 

e) What role do you think the "expressive writing" group played in this study? Use the term "design confound" or "control variable" in your response. 

f) Can this study support the claim that "writing gratitude letters (in addition to psychotherapy) improves mental health"? Apply the three causal criteria. 

g) Ask two questions about the construct validity of the study--one about the IV and one about the DV.

h) Ask a question about the statistical validity of the study. To what populations might we be able to generalize? 

 

What about the recipients? It turns out that people aren't really sure if they should send their gratitude letters. They might feel awkward about it, perhaps surmising that the recipient may not really care about such a thing anyway. But here's a quote about research on receiving these letters: 

On the receiving end, opening a gratitude letter feels even better than you might imagine. Amit Kumar, a social scientist at the University of Texas at Austin, studies the reactions of gratitude-letter recipients.

“It’s not like it makes some people feel great and some people feel just OK and some people feel kind of weird,” he said of his research findings. “Almost everybody is saying that they feel really, really great.”

i) Most psychology studies have at least two variables (because they are testing association or causal claims). But, at least according to the journalist's description above, the study by Dr. Kumar had only one variable. What was it? 

j When Dr. Kumar said “Almost everybody is saying that they feel really, really great.”, he was saying something about the mean of this variable as well as its standard error. What can you infer about these two statistics, based on his quote? 

k) This study can support a frequency claim, because it's about the level of one variable. In your own words, write the frequency claim it can support. 

(Dr. Kumar's study on gratitude letter recipients can be previewed here. You'll see that in addition to asking recipients how they felt after receiving a gratitude letter, they also asked senders to predict how the recipients would feel. The main finding was that recipients felt much better than senders predicted they would feel.)

Make a face

Should you smile, grimace, or neither when you get your COVID jab? Photo credit: Gregory Johnston/Shutterstock

Have you gotten a COVID vaccination yet? If not,  grab a chopstick and read this article before you go. Here's a link to a journalist's summary of a study on the effect of making a face (such as a smile or a grimace) on the pain of an injection. 

The background for the research is the "facial feedback hypothesis:" If you've read Chapter 14 already, you'll recognize this line of work. 

The idea that manipulating our facial expressions can affect our emotions has a long and storied history. There are many advocates of [this] hypothesis, and many critics, too. Indeed, one of the classic findings in the field — that people find cartoons funnier if they hold a pen between their teeth, inducing a smile — recently failed to replicate. This mixed research background was well known to Sarah D. Pressman and Amanda M. Acevedo at the University of California, Irvine, who led the new work, published in Emotion.

Here is some detail about the study: 

The team randomised 231 student participants to hold either a neutral expression, a regular smile (which involves the cheek muscles), a Duchenne smile (which also recruits muscles by the eyes, resulting in creasing around the eyes) or a grimace (which recruits both these sets of muscles, plus those which allow us to wrinkle our brows.

In the study they manipulated the facial expressions unobtrusively, by asking participants to hold a chopstick in different ways:

To induce these expressions, the participants (who thought they were taking part in an investigation of multi-tasking) were given chopsticks to hold in one of four positions between their teeth, and asked to imitate an example photo. Each participant then held their assigned facial position while they received an injection of saline solution into the upper arm, designed to mimic a flu jab. Their heart rates and skin conductance were measured throughout [before, during, and after the jab], as objective markers of their stress levels, and they also reported on levels of pain (anticipated and then actual) and other emotions, such as being jittery or relaxed.

This study was an experiment. Before we get to the results, let's identify some of its features.

a) What was the independent variable (IV) here? How many levels in this IV, and what were they? 

b) Was the IV manipulated as independent groups or within groups? 

c) The journalist writes, "The team randomised 231 student participants to hold either....". Is the word "randomized" here referring to random assignment or random sampling? 

d) There are several dependent variables (DVs) reported here. Name three of them. 

e) Which type of experiment was this? posttest only? pretest-posttest? repeated measures? or concurrent measures?

Now for the results. The researchers collected multiple DVs and the patterns were not the same across all DVs. I will summarize the results for only one DV, self-rated pain:

The Duchenne smiling and grimacing groups gave lower pain ratings than the neutral group while waiting for the injection, during the injection, and immediately after it. The regular smiling group fell somewhere in between.

f) Sketch a graph of this result (placing the DV on the y-axis, as usual).

g) Now a big challenge: Apply Chapter 11's twelve internal validity threats to this example. How does the study's design help rule these threats out? I've done a few of these for you. You'll find Table 11.1 helpful here!

Design confound
Selection effect
Order effect
Maturation	This was a pretest-posttest design that took place in a single session. The single session helps rule out maturation. We can also rule out maturation because all four groups had the same opportunity to "mature."
History
Regression to the mean
Attrition
Testing	All groups were tested multiple times, which means this potential threat was held constant in all groups, ruling it out as an internal validity threat.
Instrumentation
Observer bias
Demand characteristic	The independent-groups design and cover story about multitasking can probably help disguise the true nature of the experiment.
Placebo effect

 

Replication: "Don't ditch the laptop just yet"

A mini meta-analysis found that the average effect size comparing laptop to handwritten notes was negligible. Credit: insta_photos/Shutterstock

One of the major empirical examples in Chapter 10 (in the 3rd and 4th editions of the textbook) is a study that tested whether laptop or handwritten notes are better for people's learning from a video lecture. As you may recall, the study (Mueller & Oppenheimer, 2014) found that people who took notes by hand generally remembered more--they scored better on conceptual questions (though not better on factual questions) about a TED talk they had watched. 

Last month, a replication study was published in the journal Psychological Science--the same journal that published the original Mueller and Oppenheimer study. The replication was lead by Dr. Heather Urry of Tufts University. The coauthors on the paper are her entire research methods class, who conducted the work as a class project (How cool is that? Shout out to Dr. Urry's students!). 

The work is an excellent example of a replication study. It was covered in a few media outlets . Here is one summary, as reported by the APS website:

But although previous work suggested that students who write notes by hand may retain information better than those who type them out on a laptop, attempts to replicate this research indicate that taking notes longhand may offer no measurable benefit. 

“We found only small, statistically nonsignificant differences in quiz performance as a function of note-taking medium,” whether students used a laptop or pen, wrote APS Fellow Heather L. Urry (Tufts University) and colleagues in Psychological Science. 

Here's some coverage of the same study, in a blog post by Dr. Regan Gurung, on Psychology Today:

There was no difference in how well the students performed on the factual recall questions as a function of how they took notes. This was similar to the 2014 study. The difference, and failure to replicate, came when Urry et al. analyzed performance on the applied questions. Again, there was no difference in scores based on note-taking style.

In the APS summary, it is reported:

Urry and colleagues reached this conclusion through a direct replication of a 2014 study by Pam A. Mueller (Princeton University) and APS Fellow Daniel M. Oppenheimer (University of California, Los Angeles), in addition to a mini meta-analysis of eight related studies. 

a) As a review, what were the IV (and its levels) and DVs in the original study? (hint: There are two DVs)

b) What does the term "direct replication" mean in the previous quote?

c) How does direct replication compare to a conceptual replication? (You'll find these terms in Chapter 14)

 

Now let's talk about the term "mini meta-analysis" in the quote, "...in addition to a mini meta-analysis of eight related studies."   Here's a summary from the Psychology Today blog:

Urry et al. (2021) also found 8 similar studies, that also aimed to replicate the 2014 results.  The studies compared also used similar methodologies with slight variations. The effect of taking notes longhand was not statistically significant.

d) Do you think the eight studies  in the mini meta-analysis were direct replications or conceptual replications? How can you tell? 

e) Now explain, in your own words, how they might have done the mini meta-analysis? What would the authors have done, once they found the eight studies? (Why do you think it was called "mini"?)

f) Dr. Urry's team preregistered their replication study--what does preregistration mean in this context? 

g) While the original Mueller and Oppenheimer study was covered by multiple popular press outlets (such as here, here, and here), the replication study has, so far, not really broken through to the popular press. Why do you think that is? 

You should check out forest plots of the mini meta-analysis!  Here's the link to the journal article. If you're locked out, you can access a preprint of the replication study here. 

People believe claims of sexual harassment more when women are attractive

The coded stereotypicality of the drawing was a dependent variable in one of the studies. Photo: Courtesy of Dr. Jin Goh. Citation: Goh, J. X., Bandt-Law, B., Cheek, N. N., Sinclair, S., & Kaiser, C. R. (2021). Narrow prototypes and neglected victims: Understanding perceptions of sexual harassment. Journal of Personality and Social Psychology. Advance online publication. https://doi.org/10.1037/pspi0000260

Sexual harassment (unwelcome and inappropriate sexual remarks or physical contact) harms people in schools and workplaces. One potential problem with sexual harassment is whether people who report it are taken seriously. Unfortunately, when people report sexual harassment, their claims are not always believed, which means perpetrators can go uninvestigated and victims' harassment might continue. 

The press recently covered an important series of studies that investigated the role that physical appearance plays in the reporting (and believing) process. One of the summaries appeared in the Seattle Times; another  appeared on the APA website.  The Seattle Times journalist summed up the studies like this: 

The study found people are more apt to believe sexual harassment claims by women who are young, “conventionally attractive,” and appear and act feminine. Women who don’t fit that prototype not only are less likely to be believed, but also are presumed to be unharmed by harassing behavior, the study said. 

The APA website does a better job detailing the methods:

The researchers conducted a series of 11 multimethod experiments, involving more than 4,000 total participants, designed to investigate the effect a victim’s fit to the concept of a typical woman had on participants’ view of sexual harassment and the consequences of that mental association.

In five of the experiments, participants read scenarios in which women either did or did not experience sexual harassment. Participants then assessed the extent to which these women fit with the idealized image of women, either by drawing what they thought the woman might look like or selecting from a series of photos. Across all the experiments, participants perceived the targets of sexual harassment as more stereotypical than those who did not experience harassment.

The details above describe a set of experiments (do you know why they are experiments?)

a) What was the main independent variable (IV) in the five studies above? What were its levels? 

b) What was the main dependent variable (DV) in the five studies? What do you think its levels were? 

c) The image (with the two drawings, above) that goes with this post came from the first study (Study 1), in which participants read a scenario in which " women either did or did not experience sexual harassment" and made a "drawing what they thought the woman might look like". Which drawing do you think came from each condition? 

d) The drawings from Study 1 had to be coded for stereotypical femininity. Since this variable required coding, inter-rater reliability would have been important. How do you think the researchers established inter-rater reliability for their coders? (Hint: you can find relevant information in Chapter 5.)

e) Sketch a small bar graph depicting the results of these studies, based on the journalist's description. 

Now here's some more description from the APA website:

In the next four experiments, participants [read] ambiguous sexual harassment scenarios, such as a boss inquiring about a woman’s dating life. These scenarios were paired with descriptions or photos of women who were either stereotypical or not. The participants then rated the likelihood that the incident constituted sexual harassment.

f) What was the main independent variable (IV) in these four studies? What were its levels? 

g) What was the main dependent variable (DV) in the four studies? What do its levels seem to have been? 

h) Sketch a small bar graph depicting the results based on the journalist's description. 

i) Assess the plausibility of this claim: "Being more stereotypically feminine causes people to think a woman's sexual harassment claim is true"  Apply the three causal criteria (covariance, temporal precedence, and internal validity). 

Instructors: Students are likely to enjoy reading the studies in the original journal article, which appears on my list of journal articles that are student-friendly.

Interrogating Buzzfeed: Does Instagram really have "huge effects" on our psychology?

Do the studies really support cause and effect? And are those effects "huge"? Photo: Julia_Tim/Deposit Photos

This Buzzfeed headline is eyecatching and dramatic: Instagram Has Some Pretty Huge Effects On Our Psychology. Here's Everything We Know So Far.

I see two important issues to interrogate in this headline. First, it's a causal claim ("Instagram has some...effects on our psychology"). Second, it's making an argument about effect size ("pretty huge effects"). Let's see if they pan out. 

The article focuses on body image and mental health. Here's an example:

The research into how Instagram affects our psychology is relatively new, but there is a growing body of evidence to say that it has a profound effect on the way we perceive ourselves and the world around us.

Does the research support such a causal claim? Here's one study that the journalist summarized: 

Earlier this year, the UK's Royal Society for Public Health (RSPH) and the Young Health Movement published a report that looked at the impact of different social media platforms on mental health.

The report was based on a survey of over 1,400 British 14-to-24-year-olds that asked about the positive and negative implications of each social media platform for health and wellbeing.Instagram scored well on its ability for self-expression, but it was linked with some of the worst scores for sleep loss, body image concerns, and FOMO.

It's not completely clear from this summary what questions were included on this survey. However, a survey is unlikely to have manipulated exposure to Instagram, so it can't support the claim that "Instagram has implications for how people perceive themselves and the world around them."

What about the effect size of the associations? The journalist didn't report the data from the study, so we can't evaluate whether or not the effect was really "huge" or "profound." We'd have to search out the original paper for that. 

How about this other study, summarized later in the article: 

In a study published last year, Cohen and her co-authors found that it wasn’t so much social media use itself that impacted how people perceived their bodies but rather how they were using it.

Following body- and appearance-focused accounts on Instagram — as opposed to neutral accounts dedicated to things such as travel — was associated with idealizing thin bodies, obsessive surveillance of one’s own body, and striving for thinness.

a) Four variables are listed in the study above (Following body-....) What are they?

b) Were these variables measured or manipulated, do you think?  (Check your hunches here, by reading the abstract of the Cohen study.)

c) Why can't this study support a claim such as "following body-focused accounts impacts how people perceive their bodies"? Apply the three criteria for causation. 

d) Does the journalist provide any indication of the effect size of this association? If not, what data might have helped you decide if the link was "huge"?

Let's read a bit further in the journalist's article to see if we can find some experimental evidence. How about this one:

However, Cohen is hopeful that the positive body movements emerging on the platform will have far-reaching benefits for how women reflect on their own physiques.

She has recently submitted a paper for publication demonstrating that among 195 young women exposed to “body-positive” images, mood, body satisfaction, and body appreciation were all improved significantly.

The wording in the example above suggests that there was a manipulated variable, because it reads "among 195 young women exposed to 'body-positive' images'". When I read that, I picture that some people were exposed to these images, and some were not. 

e) Imagine you were going to conduct a conceptual replication of this experiment. What was the independent variable? What would its levels be? 

f) What would the dependent variable(s) be? (Hint: The journalist mentions three).

g Sketch a little bar graph of the results of your experiment--picking one of the DVs to graph. In your view, how far apart would the means and error bars have to be for you to be convinced that the effect is "huge"?

h) Would this experiment have the potential to support a causal claim? What confounds would you need to control for? 

Suggested answers to selected questions

c) Covariance: Yes--apparently this questionnaire study found a link between following more body-focused accounts and idealizing thin bodies more. 

Temporal precedence: Nope--this was a questionnaire study that measured both variables at the same time. We can't know if the IG accounts came first, or if people who idealize thin bodies more are more likely to want to follow body-focused accounts.

Internal validity: Also nope. In this correlational study we can't rule out every possible third variable. For example, maybe people with a history of eating disorders are both more likely to follow body-focused accounts and are more likely to idealize thin bodies.

d) No correlation was reported here--too bad! It would be nice if the journalist had given us some benchmarks indicating how much more likely people were to idealize thin bodies....perhaps a percentage change or a correlation coefficient, and a 95% CI for that change or coefficient. 

 

Thanks to UD student Emily Hogan for suggesting this article for the blog!

 

 

Don't believe it?

Macadamia nuts are in the same evolutionary family as peaches. (or are they?) Credit: gresey/Deposit photos

People's tendency to believe, share, and act upon disinformation (fake news) is a serious threat to civic engagement. Psychologists are studying what makes people more or less likely to believe false claims. Here are some excerpts from a brief article published in Buzzfeed, which summarized a few studies about people's willingness to believe what they read.

"What we find in our research really robustly is that we can push around people's feelings of truth using things like photographs and audio quality, and even the ease of pronouncing someone's name," said [researcher] Newman.

Here's an example of a study on how perceptions of "truthiness" can be influenced:

In 2012 Newman co-authored another paper with studies that found photographs can inflate the sense of "truthiness" that people get from reading a statement.

The sort of photographs that the researchers used for this research were "non-probative", meaning that they didn't actually contain any information about the claims being made.

One study ...found that if participants were given a trivia statement such as "Macadamia nuts are in the same evolutionary family as peaches", they were more likely to believe the statement was true if a photograph of macadamias simply appeared alongside the sentence [compared to no photo].

Bonus: Stephen Colbert (who coined the term "truthiness") also summarizes it in this clip. 

Questions about the first example:

a) What are the two variables in the macadamia nuts study? Name each variable, its apparent levels, and indicate if it is measured or manipulated.

b) Do you think the "photo appearance" variable was manipulated as between-groups or within-groups? Explain your reasoning.

c) Sketch a small bar graph depicting the results of this study, as described by the journalist. 

d) Ask three questions about the statistical validity of the macadamia nut study--your three questions should address effect size, precision, and replication. (Note--the answers to your questions might be present in the original empirical article.)

 Here's a second example:

A study published in March found that people were less likely to believe an academic researcher on the radio if the audio quality of the recording was poor or glitchy.

The study involved 97 participants, who were instructed to listen to recordings of different pieces of science news and assess the quality of the research and the researcher who was reporting it.

Half of the audio recordings were edited to sound as though they were recorded on a bad phone line. The listeners who heard these recordings rated the credibility of the researcher and the studies they were discussing as significantly less favourable than recordings with higher audio quality.

Questions about the second example:

e) What are the two variables in the audio quality study? Name each variable, and indicate if it is measured or manipulated.

f) Do you think the "audio quality" variable was manipulated as between-groups or within-groups? Explain your reasoning.

g) Sketch a small bar graph depicting the results of this study, as described by the journalist. 

h) Ask three questions about the statistical validity of the audio quality study--your three questions should address effect size, precision, and replication. (Note--the answers to your questions might be present in the original empirical article.)

i) Now consider the internal validity of the audio quality study: Why would random assignment be important in this study? 

Selected answers (use these answers as models to help answer the audio quality questions, if needed)

a) One variable is the appearance of a photo; its levels are "photo or no photo." It is manipulated.
A second variable is "level of belief in the trivia statement" or "rated truthiness." Its levels probably range from "low belief" to "high belief". It is measured. 

b) For a single fact, the presence of a photo would have to be manipulated as between groups--people would have to see the fact either with or without the photo. If they were exposed to both levels of the variable (a within-groups design), people might wonder why they are being asked to rate the same fact two times.  However, in the study itself, participants were exposed to multiple facts, some of which were accompanied by a photo and some of which were not....so that makes the variable within-subjects when you consider all of the facts together. 

c) Sketch a small bar graph depicting the results of this study, as described by the journalist. 

d) Ask three questions about the statistical validity of the macadamia nut study--your three questions should address effect size, precision, and replication. (Note--the answers to your questions might be present in the original empirical article.)

For effect size, you could ask questions such as, "how far apart were the truthiness ratings?" "How big is the difference between the photo and no-photo group?" or "What is the d? (or other effect size)"
For precision you could ask, "what is the 95% CI of the effect size estimate?"
For replication you could ask, "has this effect been replicated in other studies? What do those other studies say?"

I would like to thank my student Emily Hogan for sharing this example and Buzzfeed story with me!

 

Will an "awe walk" do wonders for your well-being?

The study asked all volunteers to go on a daily walk, but randomly assigned only some of them to seek out experiences of awe.  Credit: Studio Grand Web/Shutterstock

A recent headline reads, "An 'awe walk' might do wonders for your well-being."  Here is the journalist's summary of an empirical journal article.

The journalist starts by explaining that psychological researchers already know that exercise can improve mood. And we also already know that a feeling of awe can improve mental health. The journalist introduces the concept:

A somewhat nebulous emotion, awe generally is defined as the sense that you are in the presence of something larger and more consequential than yourself and that this something is mysterious and ineffable. 

In the study,

They concentrated on people in their 60s, 70s and 80s, an age when some people can face heightened risks for declining mental health.

Read the journalist's description of the study, identifying the study's independent variable, dependent variables (there are more than one DV), and control variable(s):

The scientists asked 52 of the study volunteers if they would mind adding a weekly 15-minute walk to their normal schedules. ...Fresh, baseline studies of their mental health showed they were psychologically well-adjusted as well, with little anxiety or depression.

The scientists randomly divided these volunteers into two groups. One, as a control group, was asked to start walking, at least once a week, for 15 minutes, preferably outside, but given few other mandates.

The members of the other group likewise were asked to walk once a week, but also were instructed in how to cultivate awe as they walked.

Not surprisingly, they found that the awe walkers seemed to have become adept at discovering and amplifying awe. One volunteer reported focusing now on “the beautiful fall colors and the absence of them among the evergreen forest.” A control walker, in contrast, said she spent much of a recent walk fretting about an upcoming vacation and “all the things I had to do before we leave.”

The researchers also found small but significant differences in the groups’ sense of well-being. Over all, the awe walkers felt happier, less upset and more socially connected than the men and women in the control group. The volunteers in the control group reported some improvements in mood, but their gains were slighter.

Questions

a) What was this study's IV? What were its levels? Was the IV manipulated as independent groups or within groups? 

b) Name three distinct DVs from this study, based on the journalist's description.

c) Which type of experiment is this? Posttest only? prettest-posttest? repeated measures? concurrent measures?

d)  Pick one of the DVs you listed in (b). Sketch a bar graph of this DVs. (Hint: you are going to need to plot four data points--do you see why?).

e) Construct validity question: What's going on in the paragraph that starts, "Not surprisingly, they found that the awe walkers seemed to have become adept at discovering and amplifying awe."? Use the term "manipulation check" in your response, and explain why a manipulation check is relevant to construct validity.

f) Statistical validity question: The journalist describes "small but significant differences". What does this phrase mean? Use the term "effect size" in your answer. 

g) External validity question: Can we generalize from this sample, or is generalization unknown? defend your answer (but please don't refer to sample size!)

h) Internal validity question: What role did random assignment play in this study? What if somebody says, "some people just like going for walks"--would you consider this to be a threat to internal validity? Why or why not? 

The journalist also mentions another DV. The researchers asked people to take a couple of selfies during their walks:

Over the course of the eight weeks, the size of awe walkers’ countenances shrank in relation to the scenery around them. Their faces grew smaller, the world larger. Nothing similar occurred in the photos from the control group.

i) It sounds like the researchers did not preregister prediction about the selfie content. Is lack of preregistration a potential problem?

 

 

 

Podcast: WOOP, WOOP!

 

Wish, Outcome, Obstacle, Plan: An evidence-based app. Photo courtesy of Dr. Oettingen/Woopmylife.

Here's another podcast-based post. NPR's Hidden Brain podcast frequently uses psychological research to illuminate a variety of psychological topics. Today's post is based on a Hidden Brain episode called You 2.0: WOOP, WOOP!

 

The episode asks,"is there a methodical way to achieve your dreams?"

The episode starts off with the suggestion that maybe positive thinking alone isn't the best way to achieve your dreams. Of course, in the United States, we are encouraged to "dream big" and shoot for the stars. But as host Shankar Vedantam interviews researcher Dr. Gabriele Oettingen, we learn that positive thinking--by itself--may not be very helpful. 

At minute 1:40,  you hear how Dr. Oettingen first started getting interested in positive thinking--it stems from a cultural difference she observed between Germany (her home country) and the U.S.  Then Dr. Oettingen lays out the theory. She explains that positive thinking feels good, but...

(2:45)...these positive fantasies--they seduce us to feel already accomplished, and they take our energy away.

Dr. Oettingen describes a series of correlational findings:

(3:00) We found that, for example, the more positively women enrolled in a weight reduction program fantasized about their success in the program, the fewer pounds they lost--three months later, one year later, two years later.

Or the more positively university graduates fantasized about an easy transition into work life, the fewer dollars they earned two years later, the fewer job offers they had gotten, and the fewer job applications they had sent out.

a) Consider the dieting study above. Sketch a well-labeled scatterplot of the correlation she describes (one axis should have "level of fantasizing" on it, and pick one of the weight loss variables for the other axis).

b) Does this study, by itself, show that fantasizing caused these women to lose less weight? (Apply the three causal criteria).

c) Now consider the work life study above. Sketch a well-labeled scatterplot of the correlation she describes (one axis should have "level of fantasizing" on it, and you should pick only one of the job-related outcomes for the other axis).

d) Does this study, by itself, show that fantasizing caused these graduates to do worse on the job market? (Apply the three causal criteria).

In the podcast, Dr. Oettingen shared two other examples: One study on surgery patients and another study on people who had a crush on another person. [Instructors, you could consider having four different groups of students graph each of the four studies.]

e) What are the advantages of doing this same correlational study in four samples (dieters, graduates on the job market, surgery patients, and people with a crush?) Use the term "external validity" in your answer. 

Now let's move on to the rest of the theory. Dr. Oettingen's theory proposes that fantasizing by itself makes people relax--"because mentally, they're already there"--they've achieved the goal. It's better, she argues, to pair your fantasies with thoughts about obstacles. Starting at minute 9:00, Oettingen introduces the term mental contrasting, in which people follow their fantasies with thoughts about the potential obstacles, asking the question: "What is it in you that stands in the way?" 

Listen from minutes 9:00 to 15:30, as Oettingen walks through the WOOP process of activating wishes, fantasizing about the outcome, anticipating obstacles, and making a plan. (WOOP stands for Wish, Outcome, Obstacle, Plan.) 

Oettingen and her team are well aware of the limitations of correlational evidence like that introduced above.  So, although it's not described in the podcast, her team has also conducted experimental studies. In her experimental work, Oettingen and her team have randomly assigned people to engage in WOOP and others to engage in the activities in a different order (perhaps Obstacle, Wish, Outcome). They find that people in the WOOP conditions are more likely to achieve their goals.

f) If you were designing a study for people in a weight loss program, how would you design an experimental study to test if WOOP thinking would lead to more successful weight loss? 

i) What would the IV be (What would its levels be)? What would the DV be?
ii) How would you assign people to the conditions? 
iii) How would you eliminate internal validity threats? 
iv) Sketch a bar graph of your predicted outcome. 

Are you interested in trying WOOP out on your own goals and wishes? The phone app is free, and you can also access it online: www.woopmylife.org.