“Wearable devices” are pieces of technology that are worn in clothes or accessories, and they often have biometric functionality – they can measure and record heart rates, steps taken, temperature, or sleep habits. Numerous tech companies have begun manufacturing and marketing such devices, which are part of a larger movement often referred to as the “quantified self” – where data about one’s life is meticulously gathered and recorded. Only 1% to 2% of Americans have used a wearable device, but annual sales are projected to increase to more than $50 billion by 2018.
Health and fitness apps are also proliferating, from software that maps where you run or provides a digital workout community, to programs that count calories or suggest how to improve your sleep. But what’s the real impact for people’s health?
Earlier this month, a report from the Journal of the American Medical Association called into question the idea that wearable devices will effect population-scale changes in health. There is a big gap, the authors claim, between recording health information and changing health behavior, and little evidence suggests that this gap is being bridged. Wearable devices might be seen as facilitating change, but not driving it. and colleagues wrote:
Ultimately, it is the engagement strategies—the combinations of individual encouragement, social competition and collaboration, and effective feedback loops—that connect with human behavior.
The difficulty of population health is that changes have to be sustained to have meaningful effects, and that is quite difficult. The authors identify four steps that must be taken to bridge this gap towards sustained change.
First, devices must be accessible. Currently, two barriers to entry are their prices and the need to learn unfamiliar technology, which means that most devices are used by young, affluent people; ironically, this is the population that probably needs them the least. Perhaps devices that are proven effective could be subsidized by employers or insurance, or financed similarly to prescription drugs.
Second, devices must be used. This requires users to add them to their daily routine, and to remember to charge them. Many health technologies must be integrated with a phone or computer, and their software must be kept up to date, all of which requires a high level of technological literacy. This could be ameliorated if health technology is incorporated more into smartphones, which many people already own, charge, and remember to carry around.
The technology must also work. Accelerometers have been well studied for tracking steps, but newer technologies that measure sleep or heart rate have not been rigorously tested. Devices need to give information when it is going to make a difference – when the user is able to act on the information immediately, or when it helps him or her understand and better use other health equipment. An example the authors use is that a pill bottle might glow red when a dose has been missed, but the user might not see it. This is less likely if a smartphone glows red in such a situation, which would be particularly helpful if it glows when the user is near the bottle.
Lastly, the information must be part of a social context that encourages users to act on it. Theories from behavioral economics could be very useful here: Lottery-style rewards are more motivating than consistent rewards, and goals are taken most seriously when framed in terms of “anticipated regret” if they are not met. Also, individual-oriented programs tend to reward those who are already excellent at a certain behavior. For example, workplaces could promote healthy offices by selecting teams at random and rewarding those whose members all walk more than 7,000 steps per day, rather than acknowledging those already-fit individuals who walk the most steps.
“The successful use and potential health benefits related to these devices depend more on the design of the engagement strategies than on the features of their technology,” the authors concluded.
Image by Leo Blanchette