Science communication has traditionally been seen as a means of crossing the boundary of science: moving scientific knowledge into the public. This paper presents an alternative understanding. Drawing upon a particular case of social science communication in the form of an interactive installation about the social responsibility of science, it develops the concept of boundary space where phenomena can simultaneously belong to science and nonscience. In addition, the paper describes how the installation functions as a space for interaction between knowledge (...) communication and knowledge production. The paper argues that we should understand science communication as a social practice, which allows scientists and nonscientists to cooperate in performing science as an important part of society. The aim is to add a new kind of analysis to traditional criticisms of deficit-thinking and popularization by asking what can we say more about science communication if we understand it as part of science as a social activity. (shrink)

BackgroundPrecision medicine development is driven by the possibilities of next generation sequencing, information technology and artificial intelligence and thus, raises a number of ethical questions. Empirical studies have investigated such issues from the perspectives of health care professionals, researchers and patients. We synthesize the results from these studies in this review.MethodsWe used a systematic strategy to search, screen and assess the literature for eligibility related to our research question. The initial search for empirical studies in five data bases provided 665 (...) different records and we selected 92 of these publications for inclusion in this review. Data were extracted in a spreadsheet and categorized into different topics representing the views on ethical issues in precision medicine.ResultsMany patients and professionals expect high benefits from precision medicine and have a positive attitude towards it. However, patients and professionals also perceive some risks. Commonly perceived risks include: lack of evidence for accuracy of tests and efficacy of treatments; limited knowledge of patients, which makes informed consent more difficult; possible unavailability of access to precision medicine for underprivileged people and ethnic minorities; misuse of data by insurance companies and employers, potential of racial stigmatization due to genetic information; unwanted communication of incidental findings; changes in doctor-patient-relationship through focusing on data; and the problem that patients could feel under pressure to optimize their health.ConclusionsNational legislation and guidelines already minimize many risks associated with precision medicine. However, from our perspective some problems require more attention. Should hopes for precision medicine’s benefits be fulfilled, then the ethical principle of justice would require an unlimited access to precision medicine for all people. The potential for autonomous patients’ decisions must be greatly enhanced by improvements in patient education. Harm from test results must be avoided in any case by the highest possible data security level and communication guidelines. Changes in the doctor-patient relationship and the impact of precision medicine on the quality of life should be further investigated. Additionally, the cost-effectiveness of precision medicine should be further examined, in order to avoid malinvestment. (shrink)

Precision medicine and digital phenotyping are two prominent data-based approaches within digital medicine. While precision medicine historically used primarily genetic data to find targeted treatment options, digital phenotyping relies on the usage of big data deriving from digital devices such as smartphones, wearables and other connected devices. This paper first focusses on the aspect of data type to explore differences and similarities between precision medicine and digital phenotyping. It outlines different ways of data collection and production and the consequences thereof. (...) Second, it shows how these sorts of data influence dominant beliefs in the field: The field of precision medicine relying on the dominant understanding of ‘genetic determinism’ imported from genetics, digital phenotyping building on the logic of ‘data fundamentalism’. In the end, the analysis shows how digital data informs potentials as well as challenges of precision medicine and digital phenotyping: a better health care for individuals connected with individualisation and responsibilisation for all, with a prognosed shift from reactive to preventive medicine. Additionally, data-based approaches might facilitate epistemological and ontological redirections for the whole field of medicine that will also affect knowledge production and a reassessment of the value of different types of knowledge with all its consequences. Institutionally, it might lead to shifts in distribution of power to experts in big data related technologies, i.e. private companies. (shrink)