No consensus yet exists on how to handle incidental fnd-ings in human subjects research. Yet empirical studies document IFs in a wide range of research studies, where IFs are fndings beyond the aims of the study that are of potential health or reproductive importance to the individual research participant. This paper reports recommendations of a two-year project group funded by NIH to study how to manage IFs in genetic and genomic research, as well as imaging research. We conclude that researchers (...) have an obligation to address the possibility of discovering IFs in their protocol and communications with the IRB, and in their consent forms and communications with research participants. Researchers should establish a pathway for handling IFs and communicate that to the IRB and research participants. We recommend a pathway and categorize IFs into those that must be disclosed to research participants, those that may be disclosed, and those that should not be disclosed. (shrink)

Investigators and institutional review boards should integrate plans about the appropriate disclosure of individual genetic results when designing research studies. The ethical principles of beneficence, respect, reciprocity, and justice provide justification for routinely offering certain results to research participants. We propose a result-evaluation approach that assesses the expected information and the context of the study in order to decide whether results should be offered. According to this approach, the analytic validity and the clinical utility of a specific result determine whether (...) it should be offered routinely. Different results may therefore require different decisions even within the same study. We argue that the threshold of clinical utility for disclosing a result in a research study should be lower than the threshold used for clinical use of the same result. The personal meaning of a result provides additional criteria for evaluation. Finally, the context of the study allows for a more nuanced analysis by addressing the investigators' capabilities for appropriate disclosure, participants' alternative access to the result, and their relationship with the investigators. This analysis shows that the same result may require different decisions in different contexts. (shrink)

Biological kin share up to half of their genetic material, including predisposition to disease. Thus, variants of clinical significance identified in each individual’s genome can implicate an exponential number of relatives at potential risk. This has renewed the dilemma over family access to research participant’s genetic results, since prevailing US practices treat these as private, controlled by the individual. These individual-based ethics contrast with the family-based ethics – in which genetic information, privacy, and autonomy are considered to be familial – (...) endorsed in UK genomic medicine and by participants in a multi-method study of US research participants presented here. The dilemma reflects a conflict between US legal and ethical frameworks that privilege “the individual” and exclude “the family” versus actual human genetics that are simultaneously individual and familial. Can human genetics succeed in challenging bioethics’ hegemonic individualism to recognize and place the family at the center of the room where bioethics happens? (shrink)

Digital phenotyping is the term given to the capturing and use of user log data from health and wellbeing technologies used in apps and cloud-based services. This paper explores ethical issues in making use of digital phenotype data in the arena of digital health interventions. Products and services based on digital wellbeing technologies typically include mobile device apps as well as browser-based apps to a lesser extent, and can include telephony-based services, text-based chatbots, and voice-activated chatbots. Many of these digital (...) products and services are simultaneously available across many channels in order to maximize availability for users. Digital wellbeing technologies offer useful methods for real-time data capture of the interactions of users with the products and services. It is possible to design what data are recorded, how and where it may be stored, and, crucially, how it can be analyzed to reveal individual or collective usage patterns. The paper also examines digital phenotyping workflows, before enumerating the ethical concerns pertaining to different types of digital phenotype data, highlighting ethical considerations for collection, storage, and use of the data. A case study of a digital health app is used to illustrate the ethical issues. The case study explores the issues from a perspective of data prospecting and subsequent machine learning. The ethical use of machine learning and artificial intelligence on digital phenotype data and the broader issues in democratizing machine learning and artificial intelligence for digital phenotype data are then explored in detail. (shrink)

The internet of things is increasingly spreading into the domain of medical and social care. Internet-enabled devices for monitoring and managing the health and well-being of users outside of traditional medical institutions have rapidly become common tools to support healthcare. Health-related internet of things (H-IoT) technologies increasingly play a key role in health management, for purposes including disease prevention, real-time tele-monitoring of patient’s functions, testing of treatments, fitness and well-being monitoring, medication dispensation, and health research data collection. H-IoT promises many (...) benefits for health and healthcare. However, it also raises a host of ethical problems stemming from the inherent risks of Internet enabled devices, the sensitivity of health-related data, and their impact on the delivery of healthcare. This paper maps the main ethical problems that have been identified by the relevant literature and identifies key themes in the on-going debate on ethical problems concerning H-IoT. (shrink)