I believe in personalization.
Evidence has firmly established that more personalized behavior change programs are more effective. People perceive personalized information as more relevant, are more likely to remember it, and more likely to actually make changes as a result of it. That’s the entire premise that the startup I worked for, HealthMedia, was founded against, and the validity of the approach is why Johnson & Johnson acquired us and made that personalized behavior change capability part of their enterprise offerings. Continue reading Personalization: Good for Health Interventions, Maybe Not for Mattresses
Imagine it’s your first visit to a dentist, doctor, or health coach. They will usually start with a basic exam to establish your level of health. That begins the discussion of any changes or improvements you might want to make. Normally in the formal care system, that first visit is accompanied by the transfer of your historical records from previous providers so the new one can tell not just your current state, but your trajectory. That’s not necessarily so with coaches, and definitely not so with digital coaches. But that history is so important.
Continue reading Why Coaches Need to Think Longitudinally
Want someone to quit tobacco? Chances are your persuasive tactics to get them to stop smoking will include some cold hard facts about the damage that cigarettes can cause to your lungs and heart. Maybe you’ll use some photos that show the aging effects of smoking on skin and teeth. Or perhaps you can share statistics around the rates of disease for people who smoke compared to people who don’t. These approaches may make intuitive sense, but they rarely work to get someone to quit smoking. Knowledge alone doesn’t change behavior. Continue reading The Diminishing Returns of Education for Health Behavior Change
Back when I used to work on digital health coaching programs, one frequent question we got had to do with whether people self-reported their health data honestly. Could we count on someone with a health issue to tell the truth about lousy eating habits, sedentary lifestyles, or skipping prescriptions? Research suggests that people are at least somewhat truthful when self-reporting their health behaviors, and discrepancies are often the result of comprehension issues rather than deceitful intent. Still, in designing a program that measures “non-healthy” behaviors, there are ways to encourage people to be more truthful. Continue reading Forgiveness, Compassion, and Health Behavior Change
A cardinal rule of designing for behavior change is that you must actually specify and understand what you are asking your user to do before you can create an effective framework to influence the behavior. BJ Fogg’s Behavior Grid is a useful tool for defining the behaviors you want your users to do, and designing an intervention accordingly.
One of the challenges I’ve found in using this taxonomy to design behavior change interventions is that it’s very difficult to coach people into span or path behaviors. To assign someone a span, like “eat a low calorie diet for a few weeks until you see a weight loss,” or a path, like “stop smoking from now on,” actually consists of many smaller steps that are subsumed in the larger span/path goal. For an end user, the span or path still leaves a question mark as to what the component behaviors should be and how to cope with obstacles that arise. Continue reading From Dots to Spans: Stringing Together Simple Actions to Create Habits