Everyday Research Methods

Who's more likely to sexually harrass, and in what situations?

Photo: Sundry Photography/Shutterstock

Psychological researchers can study important and contemporary issues, including an issue that came to the forefront in 2017--sexual misconduct by people in power.  This article in the Washington Post summarizes several examples of research on sexual harassment. The journalist wrote about studies that identified which people are more likely to harass, and also which situations are more likely to cause people to sexually harass. 

The journalist first described a self-report scale designed to identify men who are more likely to sexually harass women. Read about the scale's format: 

As one of the pioneers in the study of sexual harassment, Pryor developed a test in 1987 to measure a man’s tendency to harass. Called the “Likelihood to Sexually Harass” scale, Pryor’s test has become a cornerstone of research on sexual harassers.

His test consists of 10 scenarios. Imagine that you are an executive hiring a new secretary, one scenario starts out. A female candidate explains she desperately needs the job and looks at you in a way that possibly conveys she is attracted to you. How likely are you to give her the job? Offer the job in exchange for sexual favors? Ask her to go to dinner to discuss the job?

(There's a video mockup of the scale associated with the journalist's article) 

In Chapter 5, you learned about how a self-report measure should, ideally, be investigated for its reliability and validity. A self-report scale of tendency to sexually harass should be shown to be reliable and valid.

a) Which forms of measurement reliability are probalby most relevant for this scale: Internal, inter-rater, or test-retest? 

Next, read what the journalist writes about the sexual harassment scale:

Over the years, Pryor — a psychologist at Illinois State University — and others have used socially engineered situations in laboratories to study how well the test predicts people's behavior. 

b) Reflect on what the self-report scale is supposed to measure. Now, consider what kind of "socially engineered situations in laboratories" would show that this self-report scale has criterion validity? That is, what kinds of behaviors should high scores on the self-report scale be correlated with? 

Next, consider this finding from Pryor's research with the self-report scale of propensity to sexually harass:  

And over time, they’ve identified these factors as the most distinctive in harassers: a lack of empathy, a belief in traditional gender sex roles and a tendency toward dominance/authoritarianism.

c) Do the relationships (described above) count as convergent validity, discriminant validity, or neither? 

 

In addition to describing this self-report scale, the journalist also summarizes a second, separate line of research on sexual harassment; this one investigating the impact of holding a powerful position on perceptions of sexual interest. 

A particularly eye-opening 2011 study found that people in leadership often pick up phantom sexual signals from subordinates that aren’t really there.

The experiment designed by Jonathan Kunstman and Jon Maner took 78 adults and paired them with a member of the opposite sex. Those pairs were assigned a Lego-building project, with one person put in charge of the other. In private interviews at the end of the project, those who were appointed leaders were much more likely to have perceived sexual interest from their subordinates, even when the subordinate said in surveys that they had no sexual interest at all.

When researchers studied video of most pairs interacting, they found the leaders much more likely to act on that misperception, touching the subordinate's leg or engaging in eye gazing.

d) Consider the design of this study. Assuming that participants within each pair were randomly assigned to be leaders or subordinates in the Lego task, what kind of experiment was this? (posttest only? pretest/posttest? repeated measures? concurrent measures?)

e) Many experiments have more than one dependent variable (DV). What were the DVs in this study?  

f) Can the results support the claim that "Being in a leadership position during a Lego exercise caused people to misperceive sexual interest and to touch their subordinates' legs"? Apply the three causal criteria of covariance, temporal precedence, and internal validity. 

g) Comment on the external validity of the "leader/subordinate" Lego study. To what extent does this study extend to situations in the "real world", such as sexual harassment allegations against powerful people such as Harvey Weinstein or Matt Lauer? Do the researchers intend to have their study inform such situations? 

Are smartphones destroying a generation?

People in studies who spend more time socializing, rather than time on their phones, are generally happier. Photo: Maria Taglienti-Molinari/Getty Images

Are smartphones making young people lonely, anxious and depressed? Are teens spending time on phones instead of dating, driving, or drinking? That's the argument of a new data-based book by psychologist Jean Twenge.  

You can watch a video interview with Dr. Twenge on CNN here, complete with some of the graphs from Dr. Twenge's recent book on this topic, which reflects her research. There's also an article in The Atlantic here, which contains a condensed argument from the book. 

Several graphs presented in the CNN interview depict patterns of teenage behavior over time, from nationally representative surveys of youth. The graphs show how various healthy activities such as "hanging out with friends" dropped  starting in 2012. Twenge's explanation is that 2012 is the first year that more than 50% of Americans owned smartphones. Twenge argues that instead of going out with friends, driving, or being independent, today's teenagers are staying home and connecting with friends only via Snapchat and Instagram. 

a) The graph in the CNN story (see minute 1:50 to  2:05; and also here) shows several trends over time. These figures come from a study that is quasi-experimental. Which type of quasi-experiment does this seem to be?  

b) Take a look at the "More likely to feel lonely" figure, at minute 2:02. (again, you can also see it here, by scrolling down) The change in loneliness after 2007 has been described as "dramatic" and "precipitous". What do you think? Specifically, look at the y-axis of the graph. How dramatic would the data look if the axis ranged from, say, 0 to 100? 

c) Twenge's argument is that the advent of cell phones in 2012 is responsible for decreased social contact and increased loneliness, anxiety, and depression of youth. What might be some plausible alternative explanations for the pattern, other than cell phones? (that is, what are some internal validity threats?)

 

The data above are longitudinal data, collected over time. Twenge's research has also included correlational studies collected in one group of teenagers at a single point in time. This report in the Washington Post presents the results of an empirical study that found, among other things, that teens who spent more time doing Internet, texting, computer games, or social media were lower in happiness. 

 

d) Scroll down to the graph created by the Washington Post, which is titled "What makes teens happy?" You'll see that each bar represents a correlation between one use of time and teen happiness. What does a gray bar, or negative correlation mean (For example, what does the -0.11 correlation mean for Internet? Sketch a little scatterplot of this correlation. 

e) In the same graph, what does a blue bar, or positive correlation mean (For example, what does the 0.14 correlation mean for Sports or exercise?) Sketch a little scatterplot of this correlation. 

f) Select the correlation mentioned in d.Does this correlation, on its own, allow us to conclude that time on the Internet causes lower levels of happiness? What third variables might be responsible for this negative correlation? What about temporal precedence of the two variables? 

g) How might you describe the effect size of these correlations--are they weak, moderate or strong? How do you know?

h) Consider both the longitudinal data (in Questions a, b, and c) and the correlational data (in questions d-g). Both types of studies support the same conclusion, which make them an example of "Pattern and Parsimony." Explain why this is the case, in your own words. 

 

Instructors: You and your students might also be interested in a curvilinear relationship described in the same Post piece: 

The report’s findings were not all dire: Teenagers who get a small amount of exposure to screen time, between one and five hours a week, are happier than those who get none at all. The least happy ones were those who used screens for 20 or more hours a week.