I think of the Intro Psych course as an owner’s manual for being human. Throughout the course, we explore the multitude of ways we are influenced to think, feel, or behave a certain way that happens without our conscious awareness. Here’s one such example we can use to give our students some experimental design practice. It’s suitable for the methods chapter or, if you cover drugs, in that chapter after discussing caffeine. Caffeine, as a stimulant, increases arousal. It’s plausible that consumers who are physiologically aroused engage in more impulsive shopping and, thus, spend more money than their uncaffeinated counterparts. Give students this hypothesis: If shoppers consume caffeine immediately before shopping, then they will spend more money. Ask students to take a couple minutes thinking about how they would design this study, and then invite students to share their ideas in pairs or small groups. Ask the groups to identify their independent variable (including experimental and control conditions) and their dependent variable. If you cover operational definitions, ask for those, too. Invite groups to share their designs with the class. Emphasize that there is no one right way to conduct a study. Each design will have its flaws, so using different designs to test the same hypothesis will give us greater confidence in the hypothesis. Share with students the first two of five experiments reported in the Journal of Marketing (Biswas et al., 2022). In study 1, researchers set up a free espresso station just inside the front door of a store. As shoppers entered, they were offered a cup of espresso. The experiment was conducted at different times of day over several days. At certain times, shoppers were offered a caffeinated espresso. At other times, they were offered a decaffeinated espresso. As the espresso drinkers left the store after having completed their shopping, researchers asked if they could see their receipts. Everyone said yes. Researchers recorded the number of items purchased and the total purchase amount. (Ask students to identify the independent and dependent variables.) As hypothesized, the caffeinated shoppers purchased more items (2.16 vs. 1.45) and spent more money (€27.48 vs. €14.82) than the decaffeinated shoppers. Note that participants knew whether they were consuming a caffeinated or decaffeinated beverage, but did not know when they accepted that they were participating in a study. There are a few ethical questions about study 1 worth exploring with your students. First, this study lacked informed consent. Participants were not aware that they were participating in a study when they accepted the free espresso. As participants were leaving, it became clear to them that they were participating in a study. Given the norm of reciprocity, did participants see not handing over their receipts as a viable option? Lastly, the researchers expected that caffeine would increase consumer spending. In fact, it nearly doubled it. Was it ethical for the researchers to put unwitting shoppers in a position to spend more money than they had intended? In study 2, students from a marketing research class “in exchange for course credit” were asked to recruit family or friends to participate. The volunteers, who were told that this was a study about their shopping experience, were randomly assigned to an espresso or water condition which were consumed in a cafeteria next to a department store. After consuming their beverages, the volunteers were escorted to the department store and were asked to spend two hours in the store “shopping or looking around.” As in study 1, caffeinated shoppers spent nearly twice as much money (€69.91 vs. €39.63). Again, we have the ethical question of putting unwitting shoppers in the position to spend more money than they would have. We also have the ethical question of students recruiting friends and family to participate as course requirement. And then from a design perspective, how certain can we be that the students didn’t share the hypothesis with their family and friends? Is it possible that some of the students thought that if the study’s results didn’t support the hypothesis, their grade would be affected? As a final ethics question, what should we do with the knowledge that we are likely to spend (much) more money when shopping when we are caffeinated? As a shopper, it’s easy. I’m not going stop on the coffee shop on my way to the store. For a store manager whose job it is to maximize, it’s also easy. Give away cups of coffee as shoppers enter the store. The amount of money it costs to staff a station and serve coffee will more than pay for itself in shopper spending. Here’s the bigger problem. Is it okay to manipulate shoppers in this way for financial gain? Advertising and other persuasive strategies do this all the time. Is free caffeine any different? Or should coffee cups carry warning labels? To close this discussion, ask students in what other places or situations can impulsive behavior encouraged by being caffeinated be problematic. Casinos come readily to my mind. Are caffeinated people likely to bet more? Would that study be ethical to conduct?   Reference Biswas, D., Hartmann, P., Eisend, M., Szocs, C., Jochims, B., Apaolaza, V., Hermann, E., López, C. M., & Borges, A. (2022). Caffeine’s Effects on Consumer Spending. Journal of Marketing, 002224292211092. https://doi.org/10.1177/00222429221109247   ... View more

In the June 2022 edition of the APA Monitor on Psychology is an excellent article on the psychology of traffic safety. The article features David Strayer’s “four horsemen of death”: speed, impairment, fatigue, and distraction. Given the number and breadth of psychological concepts covered, this article provides fodder for a good end-of-term assignment. It may also save the lives of your students. Note that the journalist uses the term “crash” rather than “accident.” “Crash” is the preferred term by U.S. government agencies, such as the CDC and the National Highway Traffic Safety Administration (NHTSA). The word “accident” implies an incident that could not be avoided. The word “crash” does not carry that connotation. Giving the causes of traffic fatalities are due to driver decision-making, whether it be the driver of the vehicle or the driver of another vehicle, “crash” is a better descriptor than “accident.”   Ask students to read the article “Improving Traffic Safety” (Pappas, 2022), and then answer the following questions. How many people died on U.S. roadways in 2020? Speed. What percentage of the 2020 traffic fatalities were estimated to be caused by excessive speed? The article describes three ways that our environment can contribute to unsafe driving. Take a photo of a road in your area that illustrates one or more of these environmental hazards. Explain. The article also describes three ways that our environment can contribute to safe driving. Take a photo of a road in your area that illustrates one or more of these environmental benefits. Explain. In a survey of drivers at the beginning of the pandemic, researchers “saw an increase in respondents saying they were more likely to break the law because they knew they were less likely to be caught.” Explain this finding in terms of operant conditioning. With fewer people on the roads during the pandemic shut-down, researchers speculate that street racing may have increased. What Ontario law led to a reduction in street racing? Explain this effect in terms of operant conditioning. If you are primarily a driver, what can you do to reduce your chances of dying in a car crash due to speed? If you primarily a passenger, what can you do to reduce your chances of dying in a car crash due to speed? Impairment. What percentage of the 2020 traffic fatalities were estimated to be caused by impaired driving? Based on your reading of the article, describe the relationship between stress, alcohol, and driving while impaired. What Big Five personality trait is associated with a history of driving while impaired and reckless driving? Given your knowledge of this trait, why might that association exist? Fatigue. What percentage of the 2020 traffic fatalities were estimated to be caused by fatigue? Why might this number be an underestimation? Summarize what you learned in this course about the effects of sleep deprivation. Choose five effects, and for each, briefly explain how it could negatively effect driving.   According to the article, what have Australian highway authorities done to combat boredom on empty stretches of highway? Distraction. What percentage of the 2020 traffic fatalities were estimated to be caused by distracted driving? Explain how stress may contribute to distracted driving. Explain how the design of cars may contribute to distracted driving. Give at least one example. Conclusion. What was the most surprising thing you learned in this article? Explain. Identify at least one concept you learned in this course that could apply to speed, impairment, fatigue, or distraction but was not discussed in the article. Briefly describe the concept, and then explain how it could be a contributor to car crashes.   Reference Pappas, S. (2022, June). Improving traffic safety. Monitor on Psychology, 53(4), 46–55.       ... View more

In 2017, I wrote a blog post about an activity designed to help students see how the number of drug overdose deaths have changed since 1968 using this interactive article from the New York Times. Carolyn Brown Kramer, via the Society for the Teaching of Psychology Facebook group, asked for updated drug overdose statistics. After having your students complete the activity from that initial blog post, provide students with the most current drug overdose death data presented below. The Centers for Disease Control and Prevention (CDC) provides a “Drug Overdose Deaths” statistics dashboard that is updated monthly based on the best available data. Keep in mind that the best available data are several months old. As I write this in March 2021, the latest data are for July 2020. Line graph Each data point in the line graph is a 12-month rolling total. For example, the number of drug overdose deaths reported for July 2020 are the number of drug overdose deaths that occurred between August 1, 2019 and July 31, 2020. The number of such deaths reported for June 2020 occurred between July 1, 2019 and June 30, 2020. Mouse over a data point to see the numbers. In the line graph you will see both “predicted” data (circles) and “reported” data (solid line). As they explain on the dashboard page, “Drug overdose deaths often require lengthy investigations, and death certificates may be initially filed with a manner of death ‘pending investigation’ and/or with a preliminary or unknown cause of death.” For “reported” data, the investigation is complete. The “predicted” data include deaths that are “pending investigation.” Both reported and predicted data will change as those investigations are completed. Ask your students to predict how the number of drug overdose deaths have changed in your state or District of Columbia, then change the jurisdiction to your location to show students the data. Map For easy visual comparisons between states/District of Columbia, the map displays data by location based on the number of drug overdose deaths for the most recent month for which data are available compared to the data from a year earlier. At the time of this writing, the comparison is between July 2019 and July 2020. The colors depict percentage change between those two months. North Dakota and North Carolina were the only two states with a decrease in the number of reported drug overdose deaths, down 2.3% and 1.7%, respectively. Alaska reported no change. All other states reported an increase. The District of Columbia had the biggest change during that time period with an increase of 56.8% in number of reported drug overdose deaths (308 to 483). Data Tables Sortable data tables of the line graph data and the map data are available directly below the map. Whatever you have selected as the jurisdiction for the line graph, those are the data that will be displayed in the first data table. A word of caution As you cover this very important topic with your students, remember that some—perhaps many—of your students has had someone they know die from a drug overdose. Or perhaps some of your students themselves came close to dying from a drug overdose. Always remembering that I’m talking about experiences my students have had helps me use language that is sensitive to the people behind the statistics. ... View more