The term citizen science refers to scientific research that is advanced through crowdsourced data or the actions of volunteers from the general public. The first documented modern example of citizen science took place in 1989, when the Audubon Society recruited 225 participants from around the United States to collect and measure the acidity of rainwater samples in their respective locations. The study helped draw more attention to the pervasiveness of acid rain.
Over the years, citizen science has reached a range of fields, from astronomy to ornithology, but where it may be making the biggest impact is in medical research. People are now able to use their medical data to help advance scientific research and fuel medical breakthroughs.
How Can You Advance Medical Research?
Medical research relies heavily on patient participation in clinical trials. However, clinical trials often have strict eligibility criteria, which can create significant barriers. Presently, fewer than 5 percent of cancer patients enroll in clinical trials. This low rate participation ultimately hinders scientific progress. Also, there’s a low rate of diversity in clinical trials. For example, in 1997, less than 10% of the participants came from ethnically diverse backgrounds; in 2014, this figure was only around 14%.
While research still needs traditional clinical trials, a relatively new strategy is patient-participatory (or citizen scientist) research, where research questions are built from the perspective of individuals who live with or are affected by particular conditions in partnership with researchers, not removed. These studies differ from experimental trials in that participants are observed, but they are not given treatment. With the amount of data people collect through various consumer technologies, medical tests, and self-reported surveys, researchers are now tapping into this resource and using artificial intelligence (AI) and machine learning to find patterns in all of this information.
For example, at doc.ai, we are conducting a Digital Health Trial with more than 2000 citizen scientists who self-report allergy symptoms. We already have the first learnings from the trial delivered by our advisors from Harvard Medical School. We are also collaborating with patients who have inflammatory bowel diseases, such as Crohn’s disease and ulcerative colitis, to learn more about these chronic conditions that affect more than 3 million people in the United States.
Mining data from pooled volunteers is leading to medical breakthroughs and has spurred new research projects, many of which never would have been imagined without research volunteers and the powerful computing technology now available. Some large-scale projects include the All of Us Research Program, which was launched in 2016 by the National Institutes of Health with the goal of recruiting 1 million or more people to participate in various federally funded research using medical and self-reported data. Another is the Dr. Susan Love Research Foundation’s Army of Women, which so far has encouraged nearly 400,000 women and men to participate in breast cancer research, often through surveys or mail-in samples that are analyzed by researchers who submit proposals to the organization.
Research Your Research Options
With the popularity of crowdsourced science and the ease of providing health data, the influx of research studies using these data points have skyrocketed. But not all studies are the same. Always remember to research studies to determine where your time and health data are best spent. In addition, consider these important questions before joining a study.
- Who is conducting the research? Who is sponsoring it?
- Does the study have an Institutional Review Board (IRB) approval? Does it have a patient consent form to sign? (These features signify compliance, ethical processes and best-practices.)
- Is your health data secure and protected? Will your data be shared with any third parties?
- Will you be informed of the results after the study has been concluded? If so, how will you be notified?
- If you have questions about the study, who can you contact?
Because of the large number of volunteers needed for Digital Health Trials, participants are often asked to volunteer their time, data, and energy to participate. One of the special features of health research at doc.ai is that we provide incentives to participate: by sharing their data, users earn points that can be redeemed in the doc.ai marketplace.
Don’t Forget to Follow Up
Along with the rise of citizen scientists comes the quest for open access, transparency, and information-sharing. More Clinical and Digital Health Trial participants and research study volunteers are asking, “Where are the results?”
They want to know the impact of the study in which they were involved. Studies can take several years to reach conclusive results, but participants should be able to request that the sponsor or researcher share the results of the trial when it is complete. With the doc.ai interface, participants securely receive visualization of their data, as well as an individualized summary report for what they tracked in the trial.
In addition, some participants want to know whether they have the right to learn about their individual results. For decades, the answer has been no. But after much debate, the National Academy of Sciences, Engineering and Medicine issued a report in 2018 recommending that researchers at least consider sharing individual study results with participants. We believe that medical research shouldn’t be a black box for participants anymore and we are already providing Digital Health trials to participants with a visualized and individual report that reflects the data they’ve tracked at the end of the research. Moreover, participants can share the report with their care provider if they want to.
Join a Digital Health Trial or AI Training
At doc.ai, we help citizen scientists participate in health research through Digital Health Trials and AI training. Here are some examples of the ways in which you can take part in one of our research studies.