Optimising cohort data in Europe

location accuracy around key locations (e.g. home) or by replacing identifiable information with abstracted profiles (e.g. Bluetooth nodes) (Berman et al., 2018). y y For digital data collection technology, it is extremely difficult to determine the extent to which participants can really give their informed consent. A possible solution is using the characteristics of communication technologies for ensuring participative consent. For instance, it is possible to implement technical capabilities for effortless and retroactive retraction of data (e.g. deleting sensing app from the phone) (Bhatia-Lin et al., 2019). In legal terms, researchers should be fully committed to inform participants about the content of privacy policy: participants should be aware that they own their data and that they have the right to take decisions on data sharing and use (Ambrosini et al., 2018). y y The varieties of data sources obtained through communication technologies may make us forget that the probability of consent does not depend on the types of online applications involved. On many occasions, participants may consent retrospectively without reading key conditions in order to benefit from the services provided by commercial applications. However, the probability of giving a truly informed consent depends on the perceived costs of doing so and the expected benefits (Di Matteo et al., 2018). In this sense, opt in and opt out options may identify the perceptions of these costs and benefits both for the participants and the researcher. 4. Best practices, solutions and implications for implementation 4.1. Mobile technology Mobile technology has the potential to become an integral part of the future of health care and biopharmaceutical development. The next generation of wireless connectivity (5G) promises faster connections, lower latency and improved security; however, 5G requires a paradigm shift in network architecture. By contrast, data privacy and consent will continue to be a significant barrier, as well as the consideration of potential security threats of WiFi, Bluetooth and cellular network. In relation to smartphones, the information could be used to identify individuals, but there are many opportunities, such as: y y Vendors can add features to turn devices into hubs for storing and interpreting health and medical data. y y In low and middle-income countries (LMIC), smartphones could become a cost effective way of collecting public health data. y y Possibility of analysing mobile data in real-time. y y Aggregated data can minimise privacy concerns while still being of great value for public health. y y Useful for public health surveillance (e.g. monitoring behaviours, outside clinical settings and without depending on self-report, thus overcoming potential issues, such as recall bias).