| Popis: |
BACKGROUND Mobile apps and IoT-enabled smartphones technologies facilitate collecting, sharing, and inferring from a vast amount of data about individuals’ location, health conditions, mobility status, and other factors. The use of such technology highlights the importance of understanding individuals’ privacy concerns to design applications that integrate their privacy expectations and requirements. OBJECTIVE This paper explores, assesses, and predicts individuals’ privacy concerns in relation to collecting and disclosing data on mobile health apps. METHODS We designed a questionnaire to identify participants’ privacy concerns pertaining to a set of 432 mobile apps’ data collection and sharing scenarios. Participants were presented with 27 scenarios that varied across three categorical factors: (1) type of data collected (e.g. health, demographic, behavioral, and location); (2) data sharing (e.g., whether it is shared, and for what purpose); and, (3) retention rate (e.g., forever, until the purpose is satisfied, unspecified, week, or year). RESULTS Our findings show that type of data, data sharing, and retention rate are all factors that affect individuals’ privacy concerns. However, specific factors such as collecting and disclosing health data to a third-party tracker play a larger role than other factors in triggering privacy concerns. CONCLUSIONS Our findings suggest that it is possible to predict privacy concerns based on these three factors. We propose design approaches that can improve users’ awareness and control of their data on mobile applications |
