By Benjamin C. Silverman
Deep phenotyping research procedures pose unique challenges to the informed consent process, particularly because of the passive and boundless nature of the data being collected and how this data collection overlaps with our everyday use of technology.
As detailed elsewhere in this symposium, deep phenotyping in research involves the collection and analysis of multiple streams of behavioral (e.g., location, movement, communications, etc.) and biological (e.g., imaging, clinical assessments, etc.) data with the goal to better characterize, and eventually predict or intervene upon, a number of clinical conditions.
Obtaining voluntary competent informed consent is a critical aspect to conducting ethical deep phenotyping research. We will address here several challenges to obtaining informed consent in deep phenotyping research, and describe some best practices and relevant questions to consider.
Some digital tools utilized in deep phenotyping are identical to commercially available mobile applications commonly used in everyday life, e.g., an activity tracker like Fitbit for measuring step count, or a dietary log like MyFitnessPal for collecting nutrition data. Others use similar backend technologies applied in many commonly-used mobile applications, e.g., GPS tracking for maps and directions, Internet or social media use data for custom advertisements, and accelerometer and gyroscope data for augmented reality games, among others.
These technologies and applications are ubiquitous, and many are unaware of or confused by how their data are being collected and used. This poses a challenge to informed consent; for example, securing consent for a benign secondary use of data that is already being collected becomes much more complicated if an individual does not understand that the data are being collected in the first place.
How much education should investigators provide on currently existing data collection that is part of routine technology use before an individual consents to a deep phenotyping study? It is an ethical requirement for consent to be conducted in a manner understandable to a potential research subject. As such, we believe some basic education about technology data use is required and should be built into informed consent plans.
In addition to describing the already existing, everyday data collection that participants might not be aware of, researchers are encouraged to clearly distinguish how these data will be used differently in the context of the research study. Will it be combined with health data? Does it become protected health information when used in the study? Will it be stored in medical records? Robust consent processes should include clear descriptions of how data will be used and any relevant risks, e.g., to insurability, privacy, or confidentiality.
In addition to changes in research procedures, new information about the clinical meaning of research results, including whether or not such results need to be returned to subjects, would require re-consenting. Researchers should consider these factors in advance and build in methods for both obtaining re-consent and evaluating when re-consent would be required.
Although outside the scope of this post, it is also worth noting that consent in deep phenotyping research in psychiatry, especially in populations with severe, persistent mental illnesses, requires careful and ongoing assessment of capacity and voluntariness, which can fluctuate over time and similarly require re-consent throughout the course of a longitudinal research study.
Benjamin C. Silverman, MD is Senior IRB Chair of Human Research Affairs at Mass General Brigham.
This post is part of our Ethical, Legal, and Social Implications of Deep Phenotyping symposium. All contributions to the symposium are available here.