Wearable devices as facilitators, not drivers, of health behavior change.

Several large technology companies including Apple, Google, and Samsung are entering the expanding market of population health with the introduction of wearable devices. This technology, worn in clothing or accessories, is part of a larger movement often referred to as the “quantified self.” The notion is that by recording and reporting information about behaviors such as physical activity or sleep patterns, these devices can educate and motivate individuals toward better habits and better health. The gap between recording information and changing behavior is substantial, however, and while these devices are increasing in popularity, little evidence suggests that they are bridging that gap. Only 1% to 2% of individuals in the United States have used a wearable device, but annual sales are projected to increase to more than $50 billion by 2018.1 Some of these devices aim at individuals already motivated to change their health behaviors. Others are being considered by health care organizations, employers, insurers, and clinicians who see promise in using these devices to better engage less motivated individuals. Some of these devices may justify that promise, but less because of their technology and more because of the behavioral change strategies that can be designed around them. Most health-related behaviors such as eating well and exercising regularly could lead to meaningful improvements in population health only if they are sustained. If wearable devices are to be part of the solution, they either need to create enduring new habits, turning external motivations into internal ones (which is difficult), or they need to sustain their external motivation (which is also difficult). This requirement of sustained behavior change is a major challenge, but many mobile health applications have not yet leveraged principles from theories of health behavior.2 Feedback loops could be better designed around wearable devices to sustain engagement by using concepts from behavioral economics.3 Individuals are often motivated by the experience of past rewards and the prospect of future rewards. Lottery-based designs leverage the fact that individuals tend to assign undue weight to small probabilities and are more engaged by intermittent variable rewards than with constant reinforcement. Anticipated regret, an individual’s concern or anxiety over the reward he or she might not win, can have a significant effect on decision making. Feedback could be designed to use this concept by informing individuals what they would have won had they been adherent to the new behavior. Building new habits may be best facilitated by presenting frequent feedback with appropriate framing and by using a trigger that captures the individual’s attention at those moments when he or she is most likely to take action. Identifying and Addressing the Gaps Using wearable devices to effectively promote health behavior change is a complex, multistep process. First, a person must be motivated enough to want a device and be able to afford it; this is a challenge, because some devices can cost hundreds of dollars. Perhaps for these reasons, wearable devices seem to appeal to groups that might need them least. In a survey of wearable device users, 75% described themselves as “early adopters of technology,” 48% were younger than 35 years, and 29% reportedly earn more than $100 000  The individuals who might have the most to gain from these devices are likely to be older and less affluent. To better engage these individuals, wearable devices must be more affordable, or new funding mechanisms are needed. For example, employers and insurers might pay for a device that helps individuals better adhere to their medications, potentially yielding significant downstream health care savings. Or, devices that demonstrate effectiveness could be financed in a manner similar to that for prescription drugs. Second, once a device is acquired, a person needs to remember to wear it and occasionally recharge it— additional behaviors required from individuals who may have a difficult time already. Many wearable devices require data to be sent to a phone or computer, adding additional steps and more equipment. According to one survey (n = 6223), more than half of individuals who purchased a wearable device stop using it and, of these, onethird did so before 6  One potential solution might be to better leverage smartphones; most people with these phones carry them often. Ideally, using a smartphone does not require any effort beyond setup— like an app that gets its power from the phone that people are already accustomed to regularly charging. Because data can be transmitted passively via a cellular connection, there is no need for individuals to actively update their data. Although smartphones are expensive, many people already have them, and the reach of these devices is increasing. Third, the device must be able to accurately track its targeted behavior. Accelerometers, commonly found within wearable devices, have been well studied for tracking step counts. However, newer technologies, such as those that measure heart rate or sleep patterns, have not been well validated. Similar to mobile health applications, the increase in the availability and types of wearable devices has not been matched by appropriate testing or oversight to make sure they work.6 Wearable devices are unlikely to have the same capabilities as home devices that measure blood pressure or track medication adherence. However, a smartwatch may facilitate feedback from these devices, forming a better VIEWPOINT