Do Wearables Affect Behaviour?

Buy granny a pedometer but otherwise the benefits of wearable "health" technologies are hype and, cynically, an opportunity for large companies* to gather and sell data on your behaviour, location and health. 

In PLOS Medicine, Lucasz Piwek and colleagues argue that there is great potential for wearables to inform health management, but we need manufacturers to standardise the technology and engage with medical research. Until that is achieved, don't put too much trust in your smartphone app or wearable technology.

Fig 1. What can consumer wearables do?  Heart rate can be measured with an oximeter built into a ring [ 3 ], muscle activity with an electromyographic sensor embedded into clothing [ 4 ], stress with an electodermal sensor incorporated into a wristband [ 5 ], and physical activity or sleep patterns via an accelerometer in a watch [ 6 , 7 ]. In addition, a female’s most fertile period can be identified with detailed body temperature tracking [ 8 ], while levels of mental attention can be monitored with a small number of non-gelled electroencephalogram (EEG) electrodes [ 9 ]. Levels of social interaction (also known to affect general well-being) can be monitored using proximity detections to others with Bluetooth- or Wi-Fi-enabled devices [ 10 ]. Consumer wearables can deliver personalised, immediate, and goal-oriented feedback based on specific tracking data obtained via sensors and provide long lasting functionality without requiring continual recharging. Their small form factor makes them easier to wear continuously. While smartphones are still required to process the incoming data for most consumer wearables, it is conceivable that in the near future all processing functionality will be self contained. doi:10.1371/journal.pmed.1001953.g001

Fig 1. What can consumer wearables do?

Heart rate can be measured with an oximeter built into a ring [3], muscle activity with an electromyographic sensor embedded into clothing [4], stress with an electodermal sensor incorporated into a wristband [5], and physical activity or sleep patterns via an accelerometer in a watch [6,7]. In addition, a female’s most fertile period can be identified with detailed body temperature tracking [8], while levels of mental attention can be monitored with a small number of non-gelled electroencephalogram (EEG) electrodes [9]. Levels of social interaction (also known to affect general well-being) can be monitored using proximity detections to others with Bluetooth- or Wi-Fi-enabled devices [10]. Consumer wearables can deliver personalised, immediate, and goal-oriented feedback based on specific tracking data obtained via sensors and provide long lasting functionality without requiring continual recharging. Their small form factor makes them easier to wear continuously. While smartphones are still required to process the incoming data for most consumer wearables, it is conceivable that in the near future all processing functionality will be self contained. doi:10.1371/journal.pmed.1001953.g001

The Rise of Consumer Health Wearables: Promises and Barriers

By Lukasz Piwek , David A. Ellis, Sally Andrews, Adam Joinson

Healthy Individuals

At present, wearables are more likely to be purchased by individuals who already lead a healthy lifestyle and want to quantify their progress [2]. The majority of wearable manufacturers (e.g., Fitbit, Jawbone, and Nike) stress the potential of their devices to become an “all-in-one" platform for improving physical performance and positive habit formation. Wearable manufacturers utilise a range of digital persuasive techniques and social influence strategies to increase user engagement, including the gamification of activity with competitions and challenges. There is also a small, but growing, population of wearable users specifically interested in the concept of self-discovery via personal analytics—the Quantified Self (QS) movement [11]. A number of publications describe methods and techniques for using consumer wearables to improve sleep, manage stress, or increase productivity [12]. But do these interventions make people healthier?

Current empirical evidence is not supportive. Evidence for the effectiveness of QS methods comes from single-subject reports of users describing their experiences. Very few longitudinal, randomised controlled studies focus on the impact of wearable technology on healthy users’ behaviour. One exception found that pedometers (and consultations) increased physical activity among older people [13]. Recent surveys showed that 32% of users stop wearing these devices after six months, and 50% after one year [14]. They don’t add functional value and they require too much effort [15]. Poor implementation [16] stems from the rapid nature of development. There is a great distance between designing a product that appears to be associated with a healthy lifestyle and providing evidence to support this underlying assumption. Even the best experts are often unable to predict which interventions will show benefits when considered as part of a randomised trial [17].

Patients with a Defined Illness or Comorbidity

How useful are consumer wearables as a patient-driven, “secondary" diagnostic tool? For chronic conditions, wearables could effortlessly provide detailed longitudinal data in order to monitor patients’ progress without involving more sophisticated, uncomfortable, and expensive alternatives. For instance, it is possible to identify the severity of depressive symptoms based on the number of conversations, amount of physical activity, and sleep duration using a wearable wristband and smartphone app [18,19]. Sleep apnoea could be quickly diagnosed, and sleep quality improved, with a lightweight wearable that measures heart rate, breathing volume, and snoring (through tissue vibration) instead of a heavy polysomnograph [20]. Wearables could also feed into a broader system of “predictive preventive diagnosis." For example, a microanalysis of body movement data can be used to detect early symptoms of Parkinson disease [21]. Wearables could provide a platform for at-home management of long-term chronic conditions. Stationary computerised solutions such as web-based services, electronic self-reports, and feedback via emails already facilitate positive behaviour change for such medical issues as obesity [22], anxiety [23], panic disorders [24], post-traumatic stress disorder (PTSD) [25], and asthma [26]. However, those stationary computerised solutions already appear out of date and are almost impossible to use by patients when they are away from their home computer. Despite their widespread use, these solutions result in a high level of patient attrition [27], which might be a result of requiring patients to delay self-report until they are next able to use their home computer [28]. Wearables could address some of the limitations of other interventions by providing instant feedback and offer an individualistic approach while remaining practical [11,15].

In spite of these promises, the actual use of consumer wearables within a clinical population remains limited. Clinical studies to date that have a closer resemblance to consumer wearables involve (1) pedometers and smartphone apps to tackle a sedentary lifestyle and obesity and (2) home telemonitoring solutions for patients with pulmonary conditions, diabetes, hypertension, and cardiovascular diseases.

The use of pedometers has been associated with significant increases in physical activity and significant decreases in body mass index and blood pressure [29]. Smartphone apps have been shown to complement interventions supporting weight loss [28,30] and increase physical activity [31]. However, interventions involving pedometers and smartphone apps across clinical populations show no evidence of continued behavioural change beyond the duration of the original intervention [29]. There are also inconclusive results regarding home telemonitoring. Reviews illustrating the effects of telemonitoring on clinical outcomes (e.g., a decrease in emergency visits, hospital admissions, and average hospital stay) are more favourable in pulmonary and cardiac patients than in those suffering from diabetes and hypertension [32,33]. However, a number of trials report no beneficial effect of self-monitoring on blood glucose [34], and several demonstrate negative outcomes, including elevated levels of depression [35]. Aspects such as quality of life, acceptability, and cost benefits are infrequently or incompletely reported in telemonitoring trials [33,36], and existing reviews of remote monitoring have frequently been criticised for their poor methodology [37].

Into the Cloud: Is Wearable-Generated Data Safe, Reliable, and Secured?

The potential issue of harm is largely absent from the current literature. People may become over-reliant on automated systems that provide a false sense of security or fuel a self-driven misdiagnosis [38,39]. Patients could also suffer from negative consequences of excessive self-monitoring by finding it uncomfortable, intrusive, and unpleasant. For instance, several studies have observed that type 2 diabetics who self-monitored their own blood glucose concentration did not benefit from increased glycaemic control but rather found their disease more intrusive [35]. An individual’s personality is likely to play a key role in determining the perceived usefulness of a given device [40].

The reliability and validity of wearable devices is also concerning. Manufacturers provide no empirical evidence to support the effectiveness of their products. Recent comparisons between various wearables for tracking physical activity showed large variations in accuracy between different devices—with error margins of up to 25% [41,42]. Smartphone apps for melanoma detection have a 30% failure rate [43]. 

The privacy and security of personal data generated by consumer wearables remains problematic. Users who buy wearable devices today often do not “own” their data. Instead, data may be collected and stored by the device manufacturer. The user owns the device and is provided with a data summary, but they do not own the data. Some manufacturers charge users a monthly fee for access to their own raw data, which is regularly sold to third-party agencies. Other companies are also willing to share a user's location, age, sex, email, height, weight, or “anonymised” Global Positioning System (GPS)-tracked activities [44,45]. However, “anonymising” data via a simple distortion or removal of identifying features does not provide adequate levels of anonymity and is not sufficient to prevent identity fraud. Sophisticated algorithms can now cross-reference wearable-generated biometric data with other “digital traces” of users’ behaviour. “Digital traces” of behaviour such as time of activity and user location can reveal a person’s identity [46]. Research on “digital traces” from other sources (e.g., social media) demonstrates that these can be alarmingly accurate when it comes to predicting personality [47] and risk-taking behaviours [48], two very individual and personal traits. Furthermore, some wearable devices are easy to hack as a result of various communication technologies that aid the transfer of data between wearables and smartphones [49]. This resonates with similar problems observed in wireless digital pacemakers and glucose pumps, which were vulnerable to cyber-attacks in the past [50,51]. A well-coordinated cyber-attack could lead to patient health data being compromised, lost, or distorted.

Moving Forward: What’s to Come for Wearables in Health Care?

What can make affordable, wearable technology a real asset for health care? One option is to create a simple regulatory framework. Such an approach was recently discussed in The New England Journal of Medicine [52]. Authors pointed towards a risk-based classification (e.g., administrative apps, health management apps, and medical apps) that “promotes innovation, protects patient safety, and avoids regulatory duplication" (p. 375 of [52]). The National Health Service in the UK adopts such pathway with their regulatory framework for mobile apps, which can be classified as “medical devices” by the Medicines and Healthcare Products Regulatory Agency [53]. Applied to a health-oriented wearable device, such a solution could persuade the private sector to provide open access to their data collection practices, analysis methodologies, and measurement concerns. This would address issues of reliability, data storage and privacy. Apple has recently announced a development of a ResearchKit—an open-source software framework to create smartphone apps and to use wearables for medical research [54]. Combining such standardised solutions created by manufacturers with the correct regulatory framework has the potential to accelerate high-quality, large-scale randomised controlled trials that might lead to improvements in wearable safety and utility.


While many champion wearables as data-rich devices that will revolutionise 21st century medicine, it remains highly probable that, like many technological trends, these mass-marketed gadgets will drift into obscurity. However, given their continued popularity, health practitioners may need to prepare for consultations with patients who bring wearable data - data from devices that may be unreliable. Alternatively, if frameworks are in place allowing wearable devices to be integrated into health care systems, this could kick-start the development of validation programmes. Validated devices could become standardised, providing both individual and aggregated data for patients, governments, and health care providers. Wearable technology might yet become a valuable asset for health care in the 21st century.

Author Contributions

Wrote the first draft of the manuscript: LP DAE. Contributed to the writing of the manuscript: LP DAE SA AJ. Agree with the manuscript's results and conclusions: LP DAE SA AJ. All authors have read, and confirm that they meet, ICMJE criteria for authorship.


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                        This article has been republished and edited under Creative Commons Attribution Licence. The original is attributed:

                        Piwek L, Ellis DA, Andrews S, Joinson A (2016) The Rise of Consumer Health Wearables: Promises and Barriers. PLoS Med 13(2): e1001953. doi:10.1371/journal.pmed.1001953 Published: February 2, 2016 Copyright: © 2016 Piwek et al. 

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