Paul Cohen

This post was adapted from my recent presentations at the 2017 Behavioral Science & Policy Association Annual Conference and the 2017 Ford Research and Innovation Center Behavioral Analytics Workshop. You can view other conferences I’ve spoken at here.

 

Three cognitive biases make health hard:

 

1. Present Bias

We are overly focused on present rewards at the cost of our long-term intentions. While it is rational to value the present over the future, we discount the future inconsistently — i.e., hyperbolically instead of exponentially. (There’s a bunch of nuance and debate here, including the role of subadditivity, but I’ll leave that for another time.)

 

In the context of health, present bias shows up when we discount the future too steeply, which leads us to favor small near-term rewards (e.g., eating chocolate cake) over big long-term rewards (e.g., reducing your likelihood of heart disease by exercising every week). Sitting on your couch and watching TV today is always going to be better than preventing heart disease in 30 years. As a result, present bias makes it hard for people to invest in long-term prevention or chronic disease management.

 

 

2. Default & Status Quo Bias

We tend to stick with the defaults in our environment. We don’t order a cheeseburger. We order a cheeseburger with a coke and fries — that’s the default option. We tend to do what we have done in the past, but many of our habits were created by other people.

 

Few defaults in our environment promote health. You have to opt-in to most health behaviors.

 

 

3. Optimism Bias

We tend to think we have a lower risk of a bad outcome and a higher risk of a good outcome — i.e., we are unrealistically optimistic. We smoke cigarettes but believe we have a lower lung cancer risk than other smokers. It won’t happen to me!

 

By making us think that bad outcomes are less likely than they really are, unrealistic optimism psychologically dampens the rational factors that should motivate us to change our behavior.

 

 

These biases are extremely difficult to tackle. In fact, it would be unwise to challenge them directly (e.g., by pointing out one’s statistical risk of lung cancer or their family history of heart attacks). Fortunately, we don’t have to fix our innate biases to improve health. In fact, we can leverage other cognitive biases to mitigate these biases through counternudging.

 

I typically tap into five key biases to act as counternudges. I’ll briefly review each bias and provide examples of how I would leverage them in an email (or secure message) designed to nudge patients who were overdue for a FIT test that they previously agreed to complete. (For the unanointed, a FIT or FOBT test is a stool-based swab used to screen for colon cancer. It is fairly easy and painless, and can be completed at home when you use the bathroom.)

 

1. Consistency

We like to be consistent with ourselves. We want to be the people we think we are. You’ll find some excellent examples of how companies use this effect in the Consistency entry in my Behavior Library.

 

You might use the following consistency frame in an email: “It looks like you said you’d complete a FIT test to screen for colon cancer, but we haven’t received your results.”

 

This tactic works because we remind you that you committed to a particular course of action (without using an accusatory tone), we remind you why it is important, and we give you an “out” if you already did it.

 

 

2. Social Norms

We like doing what everyone else is doing. As with consistency, social norms feature prominently in product design (see the Social Norm entry in my Behavior Library).

 

In an email, you might simply state: “Most people return their kit within 2-3 days.”

 

What’s nice about this example is that it implies a level of ease (“oh, I can do this quickly”) while also providing social cues.

 

A word of caution: social norms done wrong are counterproductive. For example, overspecifying a social comparison (e.g., “91% of my patients return their kit within 2-3 days”), can break voice and make a personalized message feel like a mass email.

 

 

3. Goal Acceleration (AKA Goal Gradient Effects)

We put more effort into actions as we move toward goal achievement. You might have experienced this effect in the context of loyalty programs, which are typically initialized above zero in order to make you feel that you are already making progress toward your reward (see the Goal Acceleration entry in my Behavior Library). When a restaurant starts your loyalty card with two hole punches instead of one, you are perceptually closer to the goal. The closer you are to the finish line, the more you visit the restaurant.

 

You can make patients more likely to act by making them feel perceptually closer to their goal. In the FIT test example, you might tell patients: “You’re almost done. You’ve already decided to do the test, and we sent it to your home yesterday. Now all you have to do is mail it back.” This language can help shrink the gap to the finish line, and accelerate progress as a result.

 

 

4. Implementation Suggestions

An implementation suggestion is a variant of an implementation prompt. In an implementation prompt, you ask someone how they are going to do something. For example, you might give a patient a flyer listing dates and times for a flu vaccine clinic, and ask them to circle the time they plan on attending.

 

An implementation suggestion is a unidirectional implementation prompt. Instead of asking patients to tell you how they are going to implement their intention, you instead give them a helpful suggestion on how to best do it. These suggestions should help patients overcome common behavioral barriers.

 

For example, patients sometimes fail to complete their FIT test because they forget to put it in their bathroom. The following implementation suggestion offers a helpful tactic: “I’d recommend putting the kit on your toilet seat to remind you to complete it the next time you use the bathroom.”

 

 

5. Identifiability

We are more likely to do things for individuals than for groups. We might donate money to save a particular child’s life (“Uma, age 4”), but we are less likely to help an unknown person in a village 3,000 miles away.

 

This simple effect suggests that leveraging the identity of a familiar individual might help patients more readily act on their intentions. For example, emails sent from Dr. Welby (my PCP) will likely prompt more action than those sent from other medical staff or the impersonal “no-reply” sender. When direct emails are not possible, reiterating connections to someone the patient knows can be helpful. For example, a team member might introduce herself in an email as “Sally, a nurse practitioner who works closely with Dr. Welby.”

 

Incorporating a photo of the trusted health provider is another way to leverage identifiability. A headshot of your PCP set as the contact photo or embedded in the signature line of the personalized message increases the salience of the relationship and motivates action. 

 

 

These tactics work. Deploying counternudges has enabled us to achieve rates of preventive cancer screenings and vaccinations in the top 10% in the country — while simultaneously delighting our patients.