By Stacey Kusterbeck
Technologies such as wearable fitness trackers and home-based air sensors are increasingly being used to collect research participant data. This poses some new ethical challenges for researchers. “Digital health technologies may improve recruitment, engagement, and retention in the clinical trial,” says Donna Snyder, MD, MBE, executive physician at WCG. The technology makes it possible for some people to participate in the study who otherwise would have been unable to. However, some participants who are not digitally literate may be reluctant to participate; others may lack the necessary network resources. “Either can be inadvertently excluded from the trial,” says Snyder. Researchers may want to consider ways to include such individuals by supplying them with the appropriate tools or additional training, suggests Snyder.
Institutional Review Boards (IRBs) also face some unique concerns when reviewing study protocols for digital health research. One important question is whether there might be adverse events that could occur as a result of using the technology. For example, study participants might undergo unnecessary testing because of false-positive results. A glucometer that provides an erroneous high blood sugar reading could give too much insulin to correct the perceived high blood sugar. Consequently, the blood sugar may be lowered too much, prompting other therapy and testing to normalize the blood sugar.
IRBs also must consider how the participant’s personal information, including health information, is protected. “The most common risks associated with digital technology are related to privacy and confidentiality,” says Snyder. Participants should be informed on how their personal information will be protected, and if the personal information they are providing will be used for future research — and whether it will be identifiable.
“When possible, the participant should be able to opt out of any sharing of their data beyond the research study itself, or for any future use of their data in research or for other purposes — such as training new algorithms when AI [artificial intelligence] is part of the research,” recommends Snyder.
Digital health research also poses unique challenges for informed consent processes. “It’s important to think about the role that technology literacy and data literacy play in the consent process,” says Camille Nebeker, EdD, MS, professor of public health and founder and director of UC San Diego’s Research Center for Optimal Digital Ethics Health (ReCODE Health).
Using commercial products for data collection adds a layer of complexity to the informed consent process. Researchers must be able to convey product terms of service and privacy policies to study participants, since data practices can influence risk of downstream harms. “Conveying complex data management practices requires some creativity, if they are to be accessible and meaningful to someone considering participation,” says Nebeker.
As novel computing systems, such as AI, become more common in digital health, educating people about the purpose, procedures, risks, and benefits associated with a study will only become more burdensome for researchers, predicts Brian McInnis, PhD, an assistant professor of social informatics at the University of Texas at Austin in the School of Information. “Text-heavy, long, and litigious consent forms can confuse people,” says McInnis.
According to Nebeker, “the research ecosystem as a whole needs a reset. Our practices that support ethical and responsible research need to change with the times. The way informed consent is currently practiced is transactional — and needs to be interactional and dynamic to align with the needs of those considering participation.”
Nebeker, McInnis, and colleagues recently conducted online focus groups of 19 prospective study participants, about preferences for receiving study information, experiences with informed consent, and ideas for alternative approaches to informed consent.1 Study participants wanted to understand two things in particular: How the technologies worked and how their personal information would be collected, stored, and shared.
Participants suggested that multimodal learning — for example, short videos or interactive tutorials — would be useful to teach about technology and data management practices. Participants also expressed a desire for ongoing communication with the research team to learn the outcomes of the study. “The idea of a ‘one and done’ consent approach is not the desired relationship that participants would like to have with the research team,” says Nebeker.
Many people who volunteer their time and energy to scientific research want to remain involved in some way. That could simply mean learning about the results of a study when the research has concluded. Researchers can take simple, low-cost steps, such as sending a thank you note or returning study results to participants.
“Our work contributes to a recent push in the research community to reframe how scientists think about the people who participate in digital health studies, from ‘human subjects’ to ‘partners’ in research,” concludes McInnis.
Reference
1. McInnis BJ, Pindus R, Kareem D, et al. Considerations for the design of informed consent in digital health research: Participant perspectives. J Empir Res Hum Res Ethics. 2024;19(4-5):175-185.
Technologies such as wearable fitness trackers and home-based air sensors are increasingly being used to collect research participant data. This poses some new ethical challenges for researchers.
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