Digital tools for assessing bipolar disorder: A scoping review of the current landscape

This scoping review synthesizes current evidence on the use of digital tools to assess bipolar disorder across clinical, behavioral, physiological, and psychosocial domains. An electronic search of Ovid, CINAHL, ClinicalTrials.gov, and OpenGrey, completed in March 2026, yielded 374 articles for full-text evaluation. Of which 214 studies met the inclusion criteria and were included in the final review. Most studies were conducted in the Global North, particularly the United States, Denmark, the United Kingdom, and Germany. Participant samples varied widely, although cohorts were typically comprised of young adults and predominantly female, with implications for the contexts in which digital markers have been evaluated across illness stages and demographic groups, and for the extent to which these findings can be generalized. Across studies, mood, sleep, and activity were the most frequently assessed domains, whereas physiological signals, cognitive performance, and communication-based features were less frequently examined, highlighting several underdeveloped but clinically relevant areas. Common measurement approaches included self-report questionnaires and ecological momentary assessment, whilst passive sensing approaches, such as accelerometry, geolocation, device-use metrics, speech features, and actigraphy, captured continuous indicators of sleep-wake cycles, mobility, and activity rhythms. The present synthesis reveals a clear temporal shift: since 2015, the field has transitioned from primarily active, self-report study designs toward multimodal, sensor-based methodologies, driven by advances in smartphones, wearable technologies, and sophisticated data-processing pipelines. Overall, this review highlights substantial progress in digital monitoring for bipolar disorder, with emerging tools offering ecologically valid, continuous assessment of core symptom dimensions. These developments lay essential groundwork for multimodal digital biomarkers with potential applications in early detection, tailored intervention, improved patient outcomes, and longitudinal care.