Today I am proud to announce that another paper of my former colleagues from Heilbronn University and me was published in one of the journals with the highest impact factor for Medical Informatics research called JMIR mHealth and uHealth. There is a reason why we published in this journal besides its informatics focus. The journal is an open access journal. That means that readers are not charged on a pay-per-view basis or other business models to access the full text of the paper. In return, the authors need to pay publication fees. In my opinion restricting access to academic research is not a way to go. I think this isn’t a thing we see in the security community often anyway. But this is and was the standard in academia for years.
Some of you already know that I have a medical informatics background. A few of you know that I am still researching in the special interest group Consumer Health Informatics (CHI) of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS) which deals with information technologies that allow individuals to shape and manage their own health. The group focuses its research on individuals as primary users, who want to understand, evaluate and change and make decisions about his or her health, together with doctors or therapists. The goal is to maintain good health, treat illnesses and improve the quality of life.
In 2016 and 2017, we conducted two field studies at a local marathon event in Heilbronn, the so-called Heilbronner Trollinger Marathon: for the newly published JMIR paper and its predecessor a year before. Of course, this marathon is named after the world-wide well-known red wine grape variety Trollinger 🍇 that is almost exclusively cultivated on steep, sunny vineyards in the Württemberg wine region of Heilbronn.
The field study in 2016 was motivated by the fact that many runners use wearable technology such as GPS-enabled sport watches to track and optimize their training activities, for example, when participating in a road race event. An increasing amount of low-priced, consumer-oriented wearable devices are available. Yet, it is unclear which devices are used by active, healthy citizens and whether they can provide accurate tracking results in a diverse study population. No published literature has previously assessed the dissemination of wearable technology in such a group of people and related influencing factors so this was a huge motivation for us to conduct the first results on this.
The first study – Accuracy and Adoption of Wearable Technology
Our field study was divided in two parts, a pre-race survey and a post-race survey. The pre-race survey was applied to assess which wearable technology was predominantly used by runners of different age, sex, and fitness level. The post-race survey was conducted to determine the accuracy of the devices that tracked the running course. A total of 898 pre-race and 262 post-race surveys were completed with the great help of ten medical informatics students who volunteered to interview runners before and after the race in the blazing sun for a whole weekend (You are the best!).
Pobiruchin M, Suleder J, Zowalla R, Wiesner M. Accuracy and Adoption of Wearable Technology Used by Active Citizens: A Marathon Event Field Study. JMIR mHealth and uHealth. JMIR Publications Inc.; 2017. doi: 10.2196/mhealth.6395
The results of the assessment show that most of the participants (approximately 75%) used wearable technology for training optimization and distance recording. Females and runners in higher age groups were less likely to use wearables. The mean of the track distances recorded by mobile phones with combined app (mean absolute error, MAE=0.35 km) and GPS-enabled sport watches (MAE=0.12 km) was significantly different for the half-marathon event. A great variety of vendors (n=36) and devices (n=156) were identified. Under real-world conditions, GPS-enabled devices, especially sport watches and mobile phones, were found to be accurate in terms of recorded course distances. The feedback from some runners with and without smartwatches lead us to the research question for our second investigation.
The second study – Technology Adoption, Motivational Aspects of and Privacy Concerns on Wearables
Despite a great variety of consumer-oriented wearable devices, perceived usefulness, user satisfaction and privacy concerns are less investigated factors in the field of wearable applications. It was unclear why healthy, active citizens equip themselves with wearable technology for running activities, and what privacy and data sharing aspects might influence their individual decisions. Think of for example: People may be willing to give their fitness data to health insurance funds to get bonuses in return.
Wiesner M, Zowalla R, Suleder J, Westers M, Pobiruchin M. Technology Adoption, Motivational Aspects, and Privacy Concerns of Wearables in the German Running Community: Field Study. JMIR mHealth and uHealth. JMIR Publications Inc.; 2018. doi: 10.2196/mhealth.9623
For this reason, the primary aim of the study was to shed light on motivational and privacy aspects of wearable technology used by healthy, active citizens.
A questionnaire was designed to assess which wearable technology is used by runners of different age and sex. Moreover, data on motivational factors were included. The actual survey was conducted again at the Trollinger Marathon in May 2017. The demographic parameters of the cohort were compared with the official starter list of the regional event. In addition, the validation included demographic parameters of the largest German running events in Berlin, Hamburg and Frankfurt/Main. We used binary logistic regression analysis to investigate whether age, sex or course distance are influencing factors on device use, whether a runner’s age is a determinant for privacy concerns, openness to voluntary data sharing, and trust in body feedback of runners not using wearables.
In total, we collected 845 questionnaires. The key results: Technology for activity monitoring during events or training is prevalent (approx. 73%) in the running community. Male long-distance runners and runners of younger age groups are more likely to use tracking devices than runners of age 50+, with 16-29y as reference group (OR=1). A total of 136 distinct devices by 23 vendors and 17 running apps were identified. As expected, runners use wearable technology primarily for personal exercise control (90%). The second most prevalent reason is self-motivation (34%) which is more important for younger runners. External incentives or recommendations are of marginal importance (< 1%).
Three out of four participants (76.8%, 474/617) stated that they always trust the data. A fifth of the participants (127/617) considers the visualized data as ‘partly’ valid, whereas 1.8% (11/617) do not trust gathered data at all.
Users of smart technology were asked about their views and opinions on non-voluntary sharing of training or exercise data. In particular, this question included health insurance companies or device vendors which could share such data for commercial or other purposes. Two out of five runners (42.0%, 259/617) stated that they wouldn’t be concerned if data was shared in such a manner. By contrast, 35.0% (216/617) said that they would not accept if a vendor would share data without their consent. 102 out of 617 (16.5%) have a neutral perspective (“Doesn’t matter”) and only a small fraction of runners (6.5%, 40/617) were undecided (“Don’t know”). A detailed analysis revealed that runners of higher age groups consider ‘privacy’ a more important aspect than younger users of activity monitoring technology.
Two out of five runners (42%) explained that they aren’t concerned in case data collected by their device would be shared without explicit consent. By contrast, 35% said that they would not accept a vendor sharing data with third parties for commercial purposes. Runners of higher age groups consider ‘privacy’ a more important aspect than younger users.
In case of voluntary data sharing, runners prefer to give it to friends (52%), family members (43%) or a physician (32%), whereas only a small fraction (< 2%) was open to give these data to their employer. A substantial amount (68%) of runners not using technology stated that they prefer to trust in the feedback of their own body (50-69y). Approximately 11% answered that they experienced technical barriers when using such wearables for sport activities.
One aim of the study was to gain insights into the motivational factors for and privacy concerns of healthy active citizens. The literature gave an unclear picture whether privacy is a concern for using tracking technology. The results in this paper confirmed the heterogeneity of opinions on data privacy and voluntary sharing aspects present in a heterogeneous population. Nevertheless, each user of fitness trackers and wearable technology should be at least aware of the sensitivity of the data his/her device is collecting every day/minute/second and what it could tell about you and your habits. Still, users’ preferences on wearables and beliefs of how such technology works, trust in data or devices, and related implications offer great potential for further research.