BACKGROUND
The occupational burnout epidemic is a growing issue, and in the United States, up to 60 percent of medical students, residents, physicians, and registered nurses experience symptoms. Wearable technologies may provide an opportunity to predict the onset of burnout and other forms of distress using physiological markers.
OBJECTIVE
This study team conducted a scoping review to identify physiological biomarkers of burnout, and establish what gaps are currently present in the use of wearable technologies for burnout prediction among healthcare professionals (HCPs).
METHODS
A comprehensive search of several databases was performed on June 7, 2022. No date limits were set for the search. The databases were: Ovid: MEDLINE(R), Embase, Healthstar, APA PsycInfo, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Web of Science Core Collection via Clarivate Analytics, Scopus via Elsevier, EBSCOhost: Academic Search Premier, CINAHL with Full Text, and Business Source Premier. Studies observing anxiety, burnout, stress, and depression utilizing a wearable device worn by a HCP were included, with HCP defined as medical students, residents, physicians, and nurses. Bias was assessed using the Newcastle Ottawa Quality Assessment Form for Cohort Studies.
RESULTS
The initial search yielded 505 articles, from which 10 (1.95%) studies were included in this review. The majority (n=8) described observational cohort studies, with a low risk of bias. There is a lack of long-term studies with a large sample size and wearable data that may be combined with system-level information. Reporting standards were also insufficient, particularly in device adherence and sampling frequency used for physiological measurements.
CONCLUSIONS
Future digital health studies exploring utility of wearable technologies for burnout prediction should address these limitations.