Personalized sensor data can help monitor and ease tension among resident physicians, despite privacy concerns about who sees the information and for what purposes it should be processed, according to collaborative research from Cornell Tech.
Burnout is on the rise in all types of workplaces in the United States, with “great resignation” and “silent quit” entering the lexicon in recent years. This is especially true in the healthcare industry, which has been strained beyond measure by the COVID-19 pandemic.
Stress is physical as well as mental, and evidence of stress can be measured through the use of smartphones, wearable devices, and personal computers. But data collection and analysis—and the larger questions of who should have access to that information, and for what purpose—raise myriad sociotechnical questions.
“We looked at whether we could measure stress in workplaces with these types of devices, but do these individuals really want that kind of system? That was the impetus for us to talk to these actual workers,” said Daniel Adler, co-author. Lead author with PhD colleague Emily Zeng of “Burnout and the Quantified Workplace: Tensions about Interpersonal Sensing Interventions for Stress in Resident Clinicians,” published in the November 11 issue of ACM Proceedings on Human-Computer Interaction.
The paper is being presented at the ACM Conference on Computer-Supported Collaborative Work (CSCW) and Social Computing, which will be held virtually November 8-22.
Adler and Tseng worked with senior author Tanzeem Choudhury, the Roger and Joel Purnell Professor of Integrated Health and Technology at the Jacobs Cornell Technion Institute at Cornell Tech. Contributors came from the Zucker School of Medicine at Hofstra/Northwell Health and Zucker Hillside Hospital.
A resident physician’s work environment is slightly different from a traditional apprenticeship situation in that their supervisor, the attending physician, is also their mentor. It can blur the lines between the two.
“This is a new context,” Zeng said. “We don’t really know what the actual boundaries are there, or what they look like when these new technologies are introduced either. So you need to try to define those criteria to determine if this flow of information is appropriate in the first place.”
Chowdhury and her group addressed these issues through a study of physician residents at an urban hospital in New York City. After hour-long interviews with residents on Zoom, residents and their attendees were given mockups of the Resident Wellbeing Tracker, a dashboard containing behavioral data on residents’ sleep, activity, and working time; self-reported data on fatigue levels in the population; and a text box where residents can describe their well-being.
Zeng said residents are open to the idea of using technology to promote well-being. “They’ve also been very interested in the issue of privacy, and how we can use technologies like this to achieve those positive ends while balancing privacy concerns,” she said.
The study involved two cross-use use cases: self-reflection, in which residents view their behavioral data, and data sharing, in which the same information is shared with attendees and program managers for the purposes of the intervention.
Among the key findings: residents were reluctant to share their data without assurance that moderators would use it to enhance their well-being. There’s also the issue of anonymity, which was more likely with more participation. But increased participation would hurt the potential benefit of the program, because supervisors would not be able to identify the population that was struggling.
“The process of sharing personal data is a bit complicated,” Adler said. “There’s a lot of interesting ongoing work that we’re involved in that looks at this issue of privacy, and how you present yourself with your data in more traditional mental health care settings. It’s not as simple as, ‘They’re my doctor,’ so I’m comfortable sharing that data.” “
The authors conclude by noting “the urgent need for more work to set new standards around data-driven workplace wellbeing management solutions that better focus on workers’ needs, and provide protections for the workers they intend to support.”
Other contributors include Emanuel Moss, postdoctoral researcher at Cornell Tech. David Mohr, MD, professor at Northwestern University’s Feinberg School of Medicine. In addition to Dr. John Kane, Dr. John Young and Dr. Khatia Moon of Zucker Hillside Hospital.
The research was supported by grants from the National Institute of Mental Health, the National Science Foundation, and the Digital Living Initiative at Cornell Tech.