Smartphones and Wearables Could Track Mental Health in Cancer Patients, Review Finds

Cancer care has always been as much about the mind as it is about the tumor. Anxiety, depression, and pervasive fear shadow patients from the moment of diagnosis through chemotherapy, radiotherapy, and long into survivorship, yet the tools used to detect these struggles remain stubbornly old-fashioned: a questionnaire filled out in a clinic waiting room, a brief conversation between appointments, a snapshot taken weeks apart. Now a sweeping review published in BMC Cancer argues that the devices already sitting in patients’ pockets and strapped to their wrists could close that gap, capturing the psychological weather of daily life continuously and passively.

The review, led by Xiling Li, Cunyue Gong, Hegen Li, and Heng Yang of the Department of Oncology at Longhua Hospital, Shanghai University of Traditional Chinese Medicine, is a scoping review of the emerging field known as digital phenotyping. The technique involves harvesting behavioral and physiological signals from smartphones, wearable sensors, and other consumer devices without requiring patients to do anything beyond live their ordinary lives. Accelerometers log movement, GPS receivers trace patterns of mobility and isolation, and screen-use records reveal changes in how people interact with their devices. Together, these data streams form a kind of behavioral fingerprint that can shift measurably when mental health deteriorates.

To map the state of the field, the researchers searched five major biomedical databases, PubMed, Web of Science, CINAHL, the Cochrane Library, and Embase, from their earliest records through July 2026, supplementing the systematic search with a targeted sensitivity search. Two reviewers independently screened records and extracted data on study design, participant characteristics, data collection methods, mental health outcomes, and the assessment tools used to validate them. The team adhered to the PRISMA extension for scoping reviews, a reporting standard designed to make such evidence syntheses transparent and reproducible, and the full protocol was made publicly available for scrutiny.

The harvest from that search was modest but telling: 17 studies encompassing 829 participants with cancer. The numbers themselves are a finding. For a disease that affects millions of people worldwide each year, and for which psychological distress is among the most common and disabling burdens, the evidence base for passive digital monitoring remains strikingly thin and fragmented. Most of the included studies were small, used heterogeneous methods, and focused on depression and anxiety, the outcomes most frequently assessed with validated instruments such as the Hospital Anxiety and Depression Scale and the Patient Health Questionnaire-9.

Technically, the studies converged on a familiar toolkit. Wearable devices and smartphones dominated passive data collection, with accelerometers and GPS sensors being the most commonly deployed hardware. From raw sensor streams, researchers derived features across five broad domains: physical activity, location and mobility, sleep, cardiac physiology, and device-use behavior. Step counts and measures of moderate-to-vigorous physical activity quantified how much patients moved; GPS trajectories yielded metrics of mobility range and time spent at home versus places of interest; actigraphy captured sleep duration and the regularity of rest-activity rhythms; and heart rate and heart rate variability offered windows into autonomic nervous system function, which is known to shift with stress and mood.

The consistent signal emerging from these studies is that the body’s movement tells a story about the mind. Higher levels of physical activity were generally associated with lower depression, anxiety, sadness, and psychological distress across the reviewed studies. Conversely, greater sedentary behavior and disrupted sleep or flattened rest-activity rhythms were associated with higher psychological symptom levels. These associations echo a much broader literature in psychiatric digital phenotyping, where reduced mobility, social withdrawal reflected in GPS data, and disturbed circadian patterns have repeatedly been shown to correlate with depressive states. What the new review adds is evidence that the same relationships hold in a population whose activity and sleep are already perturbed by tumors and toxic therapies.

That complication matters. Cancer treatment itself alters sleep, saps energy, and confines patients to their homes, so a naive interpretation of digital markers borrowed from healthy populations risks misreading treatment side effects as psychological decline. The review’s authors are careful on this point, noting that the current evidence is insufficient to support routine clinical implementation of digital phenotyping in oncology. Passive data can describe what is happening, but translating those descriptions into clinical decisions, determining when a drop in step count or a fragmentation of sleep warrants an intervention, requires validation studies that these small, heterogeneous investigations cannot yet provide.

The methodological challenges are considerable. Sensor data are noisy, affected by device type, wear time, and individual habits. Feature definitions vary from study to study, making results difficult to pool or compare. Privacy and consent raise their own questions: continuous location tracking and behavioral surveillance, even for benevolent purposes, demand robust safeguards and clear communication with patients. And because depression and anxiety were overwhelmingly the chosen outcomes, domains such as fear of cancer recurrence and psychological distress during rehabilitation remain comparatively unexplored, despite being central to the lived experience of survivorship.

Still, the potential of the approach is difficult to overstate. Conventional assessment places the burden on patients to complete questionnaires and on clinicians to administer them at intervals, an arrangement that both burdens patients and misses the dynamic, day-to-day fluctuations in psychological state that predict clinical deterioration. Digital phenotyping inverts that model. Data accumulate silently in the background, and patterns that unfold over days rather than months become visible. Combined with brief ecological momentary assessments, in which patients answer short prompts on their phones, passive sensing could eventually give oncology teams a continuous, ecologically valid picture of mental health that no clinic-based scale can match.

The review’s authors call for larger-scale, standardized, multicenter prospective studies to move the field forward, and that prescription is likely to shape the next phase of research. If such trials confirm that sensor-derived features can anticipate psychological crises before patients report them, digital phenotyping could become a routine part of supportive cancer care, alerting clinicians to intervene earlier and more precisely. For now, the message of this careful synthesis is one of measured optimism: the technology works, the early signals are coherent, and the infrastructure to make it clinical medicine is the task that remains.

Subject of Research: Use of digital phenotyping with smartphones and wearables to monitor mental health outcomes in patients with cancer

Article Title: Digital phenotyping for monitoring mental health outcomes in patients with cancer: a scoping review

Article References: Li, X., Gong, C., Li, H., & Yang, H. (2026). Digital phenotyping for monitoring mental health outcomes in patients with cancer: a scoping review. BMC Cancer. https://doi.org/10.1186/s12885-026-17160-2

Image Credits: AI Generated

DOI: 10.1186/s12885-026-17160-2

Keywords: digital phenotyping, cancer, mental health, depression, anxiety, wearable technology, smartphones, psychological distress, scoping review, GPS tracking, sleep monitoring, oncology