Data from health apps offers opportunities and obstacles to researchers
Researchers are eager to tap into the steadily expanding pool of health information collected from users by products like Fitbit, Clue, and the Apple Watch. But while these datasets could be a scientific treasure trove for scientists, they also pose ethical challenges that need to be addressed.
"There are huge opportunities. I think that's the attraction," says Ida Sim, director of digital health for the Division of General Internal Medicine at the University of California, San Francisco. Sim explains that part of the appeal for scientists is that the apps and tech are designed to appeal to the general public. A commercial app or device with an easy, attractive interface is primed for long-term use by far more people than can usually be included in a research study. "As opposed to a clunky research wristband, which is ugly, and people won't wear it," she says.
“我们面临着巨大机遇，我认为这是其特点之一，”位于旧金山的加利福尼亚大学内科综合部的数字健康主任艾达·西姆（Ida Sim）说道。西姆解释道，应用和科技旨在迎合大众，这是吸引科学家的地方 。一个商业应用或设备，其界面简单、有吸引力，已可以为大众长期服务，其服务人数比一项研究所涉及的受试者更多 。“这与研究所涉及的既笨重又不美观的表带相反，没人愿意带这种表带，”她说道 。
Researchers are taking advantage of the better design of their corporate counterparts, and in some cases, companies are especially eager to collaborate. This spring, the period tracking app Clue offered funds to researchers hoping to use Clue users' cycle tracking data to answer scientific questions. The company had previously provided data to researchers who approached it directly, but the grants marked a formalization of their existing program.
"It's been an evolving conversation," says Amanda Shea, research collaborations manager at Clue. "Our dataset is big enough now, and we have more of the proper protocols in place can ensure users aren't at risk through data sharing, that we can more actively participate in research."
Unlike academic researchers, app companies like Clue are explicitly designed and have the resources to collect and maintain large amounts of data. On the other hand, commercial apps usually aren't designed for research, which demands predictable, transparently collected, and granular data. Sometimes, that means app-generated information is actually less useful to researchers, says Olivia Walch, a postdoctoral student studying mathematics and circadian rhythms at the University of Michigan.