Read the good news.
Now there may be another approach, based on the same logic that maintains order at traffic intersections around the world: people respond to color. A new study published Aug. 6 in the American Journal of Preventative Medicine suggests that when it comes to nutrition, people may pay more attention to simple color-coded warnings: Green for healthy, yellow for less so, and red for calorie bombs.
Yeah. Simply add color to your warning label and it works. Why?
In part, Levy said, it’s that many people just aren’t very good at math. “One of the reasons why we’re interested in doing it this way is that the data out there on numeracy and literacy shows that people, even with high literacy and numeracy, don’t necessarily understand nutritional labeling particularly well,” he said. “And certainly folks with lower numeracy and literacy would have more difficulty putting calorie numbers into context.”
Gee. Who knew you had to take off your shoes when dining? Turns out you gotta know math to eat correctly. And color coded math warning labels allow people who aren’t good with numbers to find the right food.
Math. That sounds like Counting the Change, doesn’t it? Let’s count the Change here.
Start with the intervention.
The labeling intervention began in March 2010. During 1 weekend, all food and beverages were labeled red, yellow, or green on the menu board located either directly over the individual food station, directly over the shelf where the food was located, or directly on the packaging. The labeling intervention was advertised as the Massachusetts General Hospital Choose Well, Eat Well program, and the message to cafeteria patrons focused on making a better choice. We posted new signage to describe the labeling on a wall in the cafeteria as well as on 2 large columns in the middle of the cafeteria. This signage highlighted that green meant “consume often,” yellow meant “consume less often,” and red meant “there is a better choice in green or yellow.” Rather than tell patrons to stop for red items, we used a positive yet clear message to redirect patrons toward a better choice. During the first 2 weeks, a dietician was available in the cafeteria to answer questions about the labels. Throughout both phases 1 and 2, we supplied the cafeteria with pocket-sized pamphlets containing information about the labeling as well as the specific amount of calories and fat in all items.
This is a flat out information persuasion campaign in a large health center cafeteria. You are providing Arguments, information that bears on the central merits of the attitude object, in this case, food, and its nutritional content. The color coding simplifies all the information in a Cue-based fashion and if the Other Guys trust the source of information, They don’t have to check each food item to make sure the color code is properly applied or even get into a food fight over whether that Yellow should be a Red because it is genetically modified.
So, this is a nice setup by my lights. You’re running on the Central Route with lots of information about nutrition plus you layer a simple, familiar kind of Cue with that Red Yellow Green color coding that accurately reflects all the math in your Arguments. Kind of a Ding-Donged Central Route play, right? Ding-dong the Color with the Math so that people can easily and quickly associate complex nutritional information with reliable and honest Cues that simplify choice and action right at the point of TACT.
But, wait. There’s more.
Phase 2: Choice architecture intervention. In June 2010, we began the choice architecture intervention. We made the changes for this phase over a weekend and did not advertise them. The main target items for phase 2 were cold beverages, premade sandwiches, and chips. We chose cold beverages because they represented a large portion of cafeteria sales (20% of overall sales), and we hypothesized that location and convenience would influence beverage purchases. We also hypothesized that location and convenience would influence the sales of chips and premade sandwiches because cafeteria patrons who do not have a lot of time to spend in the cafeteria are likely to purchase these items.
The Nudge hits the cafeteria! Through the strategic arrangement of choice, you Change the Other Guys. Here’s the Nudge detailed.
We rearranged all 5 beverage refrigerators so that the green beverages (including water, diet beverages, and low-fat dairy products) were located at eye level and yellow and red beverages were located below eye level. We defined eye level as a height between 5 and 6 feet. During baseline and phase 1, bottled water was available in 2 refrigerators that were not centrally located in the cafeteria, similar to the cafeteria layout before the study started (Figure 1). During phase 2, we added bottled water to the other 3 beverage refrigerators and added 5 baskets of bottled water throughout the cafeteria near the food stations (Figure 1). We rearranged the premade sandwich refrigerator so that the green sandwiches were located at eye level and the yellow and red sandwiches were below or above eye level. Chips were located on 2 adjacent racks, and we placed the yellow chips on the higher eye level racks and the red chips on the bottom (no chips were rated green).
Well, you can call that a choice architecture, but you’re just moving the cookie jar where the kid or the dog or the spouse can’t easily find it. I have a little trouble when you call Hiding It something like Choice Architecture. You’re not Nudging here in the sense of doing something that pushes or pulls the Other Guy ever so slightly. You’re putting up barriers, obstacles, and costs to frustrate, confuse, or distract a behavior. For me, calling this Choice Architecture suggests a different Other Guy for persuasion: Me or you, but not those folks in line at the cafeteria.
But, let’s not quibble over mere words, definitions, and concepts. We know what everyone is doing. Phase 1 is a Central Route Argument plus that layered Ding-Dong color Cue. Phase 2 is . . . a Nudge.
And all this makes a difference as we know from the news reports. Do we really need to Count the Change? Mark Bittman doesn’t! Heck. Since we’re all propeller-head, bean-counters, here, how about a little data . . .
. . . which takes us to a nice feature about this intervention: How they Count. Employees of the health center have Dining Cards they present at checkout. The researchers therefore have the same kind of information Big Food and Big Marketers collect on you in the grocery store. They know to the penny what you bought and who you are in that Anonymized Data way. The researchers got all cafeteria sales data for 3 months before the intervention and collected the same data during and after. It would be nice to have another similar work site as a control and nicer still to execute this on a hundred cafeterias randomly assigned to treatment or control, but this is still a strong data design. You’ve got pre-post data that is about as good a Count as you can get with this TACT.
Click to enlarge.
The reporting is a bit confusing. If you navigate merely by statistical significance (those p values), it looks like nothing worked because you don’t see a bunch of “p < .05″ or smaller indications. If you read the fine print, you learn that all numbers in boldface are p < .05 which means something happened. Roughly speaking the Phase 1 Central Route intervention produced about a 11% decrease (Small Windowpane) in Red food items and about a 7% increase (half a Small Windowpane) in Green food items. The Phase 2 Nudge produced another 4% decrease in Red food items and, this isn’t good, a 2% decrease in Green food items. Clearly very Small Windowpanes here, but statistically significant because you have over 4,000 cases in a repeated measures design which provides power out the wazoo.
Now, the researchers also present analysis from a segment on Beverage purchases and finds better effects. Those show Small+ Windowpanes consistently across all Phases. I discount the importance of this finding because nothing in the intervention was aimed at producing more Change in beverage purchase compared to other items. It’s all about Red, Yellow, or Green regardless of food category. When you start grabbing the best findings from the total, you will always see larger effects but that’s because you are cherry picking. Believe me, if sales of a different category like sandwiches or soups had popped larger effect sizes, you’d be reading all about that instead.
And, you can partition these sales data however you wish. The authors make a big deal about ethnicity and job classification differences with concerns of education and literacy. And, you can see some variation there, but for me it’s just Gertrude Stein’s Oakland with not much there, there (except for the glory days of Da Raiders).
And, in fact, the intervention taken as a whole doesn’t make much Change. The main point for me is a Small Windowpane effect on Red items. The minor point is that the Nudge clearly had costs that hurt the minimal gains. Hiding the cookie jar clearly had some Reactance type effects as it decreased purchase of Green items. Sure, you can find something special with the Left Handed Gay Armenian segment, but the intervention is aimed at everybody seated at the Table of Brother and Sister Hood.
Now, the pop press takes this as a New New Thing in the Global War Against Food Terrorism when the data suggest a rather weak intervention that is a standard public health education in a health center cafeteria. In other words, you’re doing an Old Old Thing in the most favorable circumstance you can find, rather like preaching in the soup kitchen. You’ll get a lot of Amen, Brother, but lose the soup and you lose the congregation.
And you get a Small effect for all the nagging, oops, the education on the Central Route. Imagine doing this on a food truck that hits construction work sites. Guys would buy carrots just to throw them at the signs. And imagine Hiding The Cookie Jar under these conditions. You’d earn combat pay for playing interventionist on that battlefield. And, you’d probably lose the war and most of the battles, too.
I appreciate the effort and concern here, but I disagree with the Change and its Count. The numbers clearly show the Nudge had negative effects along with its small benefits (which is consistent with the Nudge literature if you actually read the Methods and Results section). The small overall changes flow from a standard public health education model as implemented in a congenial public health setting, a health center. Nothing in this report is exaggerated or manipulated the way you see in Tooth Fairy Tales and everything is exactly and precisely correct. It just doesn’t Count for much Change.
P.S. Choice Architecture Nudge? Do this. Stand in front of a bunch of folks with low education and literacy who have trouble thinking for themselves about food and show and tell your Choice Architecture Nudge. After a few minutes, stop, look around the room, and feel the vibe. Maybe you’ll understand why Romney lost the election.
Douglas E. Levy, PhD, Jason Riis, PhD, Lillian M. Sonnenberg, DSc, RD, Susan J. Barraclough, MS, RD, Anne N. Thorndike, MD, MPH. (2012). Food Choices of Minority and Low-Income Employees: A Cafeteria Intervention. American Journal of Preventive Medicine, Volume 43, Issue 3, September 2012, Pages 240–248.
Thorndike, A. N., Sonnenberg, L., Riis, J., Barraclough, S., & Levy, D. E. (2012). A 2-Phase Labeling and Choice Architecture Intervention to Improve Healthy Food and Beverage Choices. American Journal Of Public Health, 102(3), 527-533.