Most patients visiting a spine clinic in Seattle say they would be comfortable sharing smartphone-derived biometric data with their care team, yet fewer than four in ten are ready to sign up for passive digital monitoring, according to a new cross-sectional survey published in BMC Digital Health. The study, conducted at the Swedish Neuroscience Institute between February and March 2025, is among the first to systematically ask spine patients whether they would accept digital phenotyping—the automated collection of behavioral and biometric data through personal devices—as a replacement or supplement for traditional patient-reported outcome measures.
The survey was distributed to 210 consecutive patients attending in-person appointments at the spine outpatient clinic, and 183 completed it, a participation rate of 88 percent. Respondents had a mean age of 66.2 years, ranging from 25 to 93, with 100 women and 83 men. Most had at least some college education, and the majority were surveyed during follow-up visits rather than new patient encounters. The instrument covered familiarity with smartphone technology, comfort with health-related data sharing, willingness to participate in digital biometric collection, and concerns about privacy and security.
The headline numbers reveal a striking gap between general comfort and specific commitment. Sixty-one percent of respondents described themselves as somewhat or very comfortable sharing digital biometric data with their spine care team, and only 18 percent reported discomfort. Yet when asked directly about digital phenotyping, just 38 percent expressed willingness to participate, while 36 percent preferred traditional survey strategies such as paper-based or electronic questionnaires. Another 19 percent said they would need more information before deciding, and 7 percent refused outright. The authors suggest this discrepancy likely reflects unfamiliarity: only 7.7 percent of patients had even heard the term digital phenotyping before the survey.
Privacy emerged as the dominant barrier. Fifty-eight percent of respondents reported being somewhat or very concerned about data privacy, with 21.9 percent neutral. When asked why they might decline to participate, 27.3 percent cited privacy concerns, followed by unfamiliarity with technology at 23.0 percent, uncertainty about benefits at 16.9 percent, perceived time burden at 12.0 percent, and cost at 11.5 percent. Privacy concerns did not differ significantly by gender or education, though there was a trend toward greater concern among older respondents that approached but did not reach statistical significance.
Comfort levels with data sharing were remarkably consistent across age groups, defying the researchers’ initial hypothesis that older adults would be more skeptical. When comfort responses were scored numerically, patients aged 75 to 93 actually averaged the highest comfort rating of any age quartile at 3.89, compared with 3.67 for the youngest quartile aged 25 to 58, though analysis of variance showed no significant differences between groups. Multivariable logistic regression confirmed that age, self-reported gender, educational attainment, and current use of biometric technologies were not significantly associated with willingness to participate in digital phenotyping.
Actual technology use told a different story. Nearly all participants owned a smartphone, with only 4.9 percent reporting otherwise, and smartphone ownership declined only modestly with age, from 100 percent in the two youngest quartiles to 87 percent among those aged 75 to 93. But current use of digital health or biometric tools was reported by just 35 percent of respondents overall, and usage dropped significantly with age: 55.6 percent in the youngest quartile versus 30.4 percent in the oldest. After adjusting for education and gender, older patients were less than half as likely to use digital tools as younger patients, with an adjusted odds ratio of 0.45.
The type of data patients were willing to share also varied by sensitivity. More than 80 percent of respondents expressed comfort sharing pain levels, physical activity, heart rate, and sleep data, whereas comfort dropped for diet, medication use, and mood or mental health information. Preferences for how often data would be exchanged were similarly revealing: 31 percent would share daily, 29 percent weekly, and 9 percent monthly, while 18 percent preferred that data be exchanged only during in-person clinic visits and 9 percent were unwilling to share anything at all. The authors note that because digital phenotyping is passive, more frequent uploads impose little additional burden, making the reluctance to share daily likely another expression of privacy concerns.
Digital phenotyping has its roots in mental and behavioral health research, where passive collection of mobility patterns, phone use, heart rate, sleep, and social behavior has been used to predict symptom exacerbation in mood disorders, anxiety disorders, and schizophrenia. In cardiology, continuous wearable sensor data analyzed with machine learning has been described as predicting rehospitalization in heart failure patients with efficacy comparable to implanted sensors. In spine care specifically, prior work has demonstrated the feasibility of monitoring mobility and quality of life through digital phenotyping, and smartphone-derived GPS mobility metrics have been validated against traditional outcome measures in post-surgical patients.
The appeal for spine clinics lies in the well-documented shortcomings of conventional patient-reported outcome measures, which suffer from recall bias, non-response bias, response shift, and substantial administrative costs tied to distribution, transcription, and analysis. Health policy shifts have increasingly tied these questionnaires to reimbursement, raising the stakes of incomplete data. Published completion rates for traditional spine PROMs have averaged around 64.7 percent in large cohorts, declining from 84.5 percent at initial presentation to 44.5 percent by twelve months after surgery. Passive, continuous collection could, in principle, sidestep much of that burden, though the survey data suggest patients would need convincing before that potential is realized.
The study’s authors caution that their findings come with important limitations. The single-center design may not generalize to other spine patient populations, and Seattle’s comparatively technologically literate population may have inflated comfort and willingness estimates relative to rural or resource-limited settings. Most patients were surveyed at follow-up visits, potentially biasing responses toward those already aware of the time demands of traditional questionnaires. Twelve percent of eligible patients did not complete the survey, and some of them may have been uncomfortable with data sharing, which could skew the results. Finally, the survey assessed attitudes toward digital phenotyping in general rather than toward any specific platform, leaving open how patients would respond to concrete tools with fixed data collection parameters. The authors conclude that transparent data governance and flexible, patient-centered participation options will be essential as clinics consider integrating these technologies into routine spine care.
Subject of Research: Patient willingness and barriers to smartphone-based digital phenotyping in spine clinics
Article Title: Modernizing patient-reported outcome measures: are patients willing to share smartphone-derived health data in spine clinics for digital phenotyping?
Article References: Kraemer, M. R., Gambhir, A., Jouppi, L. L., Gerstmeyer, J., Pierre, C., Gold, C., Hogsett, C., Minissale, N., Norvell, D. C., Abdul-Jabbar, A., Oskouian, R. J., & Chapman, J. R. (2026). Modernizing patient-reported outcome measures: are patients willing to share smartphone-derived health data in spine clinics for digital phenotyping?. BMC Digital Health, 4(1), Article 68. https://doi.org/10.1186/s44247-026-00299-0
Image Credits: AI Generated
DOI: 10.1186/s44247-026-00299-0
Keywords: digital phenotyping, spine care, patient-reported outcome measures, smartphone health data, data privacy, cross-sectional survey, digital health, biometric data, patient attitudes, health technology adoption, Modernizing, patient-reported
News Source: Denise Maddox. (October 29, 2026). Spine Patients Open to Sharing Smartphone Health Data, but Privacy Worries Linger. Scienmag.
