The research, published in the Journal of Activity, Sedentary and Sleep Behaviors, paired two kinds of objective measurement that are rarely captured simultaneously: passive smartphone sensing and wrist-worn accelerometer data. Instead of asking people to recall their habits, the team recorded, second by second, when a phone’s screen was actually in use and whether the person wearing the accelerometer was sitting still or moving. The result is one of the most granular portraits yet of how digital device use and physical behavior intertwine in everyday life.

The study drew on an ongoing cohort of adult caregivers of preschool-aged children, a population whose days are punctuated by childcare demands, errands and fragmented activity. Smartphone screen time was captured objectively with Chronicle, an Android-based passive sensing application that logs device usage without relying on user self-report. Movement behavior, meanwhile, was assessed with wrist-worn accelerometers, the small motion sensors that have become the gold standard for measuring physical activity and sedentary time in free-living conditions.

The technical processing was correspondingly detailed. Accelerometer signals were analyzed using GGIR, a widely used open-source pipeline, together with the SedUp algorithm, which classifies brief time epochs as sedentary or non-sedentary based on the posture and motion information embedded in the wrist signal. The researchers then aligned the two data streams at an unusually fine resolution: five-second epochs, restricted to waking wear time. Across the analytic sample of 63 participants, this alignment produced 785 person-days of data, or roughly 3.3 million individual five-second windows in which both smartphone state and body movement were known at once.

The headline finding is striking in its simplicity: a substantial share of smartphone screen time happens while people are not sedentary. At the participant level, the median proportion of smartphone use occurring during non-sedentary behavior was 25.9 percent. That means roughly one in every four seconds of phone use, for the typical person in this study, took place while the body was up and about. The range of individual differences was enormous, stretching from 5.6 percent to 73.7 percent, suggesting that for some people the phone is almost entirely a couch companion, while for others it functions nearly as a mobile device in the literal sense.

The researchers dug further into what was happening during those non-sedentary moments of screen use. Among the epochs in which people used their phones while not sedentary, 52.1 percent occurred during inactive behavior and 47.9 percent during active behavior. The distinction matters because non-sedentary is not automatically synonymous with physically active; someone standing still at a kitchen counter is not sedentary, but neither are they accumulating meaningful movement. Even so, the finding that nearly half of non-sedentary screen time occurred during genuine activity challenges the deepest layer of the screen-time-as-sitting assumption.

Perhaps the most intuitive results emerged at the level of individual apps. Social media applications were predominantly used during sedentary behavior, fitting the popular image of endless scrolling from a seated position. But utility and media apps told a different story. The Phone, Maps, Camera, and YouTube applications all showed higher proportions of non-sedentary use, a pattern that maps neatly onto how people actually live: checking directions while walking, photographing a moment on the go, or watching a video while standing in a queue. Screen time, in other words, is not a single behavior but a bundle of behaviors with distinct postural signatures.

The implications reach well beyond measurement pedantry. Sedentary behavior is an established risk factor for cardiometabolic disease, and interventions designed to reduce sitting time often use screen time as both a target and a proxy outcome. If a quarter or more of phone use occurs during movement, then studies that equate screen time with sedentary time may systematically misclassify behavior, potentially underestimating sedentary levels in some people and overestimating them in others. Momentary misclassification of this kind can distort the estimated effectiveness of interventions, obscure real relationships between screen habits and health, and misdirect resources toward reducing screen use when the actual problem, for a given individual, is prolonged sitting.

The study’s authors argue that smartphone screen time fails as a momentary proxy for sedentary behavior because the proportion occurring during non-sedentary activity is substantial, highly variable between individuals, and dependent on which apps a person uses. That variability itself is a finding: any fixed correction factor applied to self-reported or passively sensed screen time would misfit a large share of the population. The work also hints at more sophisticated future interventions, in which app-level context could inform whether a nudge to move more, or a nudge to put the phone down, is actually warranted in a given moment.

There are, of course, limits to what a single study can settle. The sample consisted of 63 adult caregivers of young children, a group whose smartphone and movement patterns may differ from those of retirees, office workers or adolescents, and the analysis focused on Android users whose devices could run the sensing application. The researchers describe their work as an opportunistic analysis within an ongoing cohort, and the findings will need replication across more diverse populations and device ecosystems. But the methodological template, aligning passive phone sensing with accelerometry at five-second resolution, offers a way forward that does not depend on fallible human recall. As screens migrate from fixed locations into every pocket, the study suggests that the science of sedentary behavior must follow, measuring where the body is, not just where the eyes are.

Subject of Research: The alignment of smartphone screen-time sensing with accelerometer data to test whether screen time is a valid momentary proxy for sedentary behavior in adults

Article Title: Not all screen time is sedentary: evidence from aligned smartphone sensing and accelerometry data in adults

Article References: Culverhouse, J., Finnegan, O. L., Bowen, K., Nelakuditi, S., Ghosal, R., Radesky, J. S., Adair, T., Restino, M., White, J. W., III, Zhong, Z., Hadj-Amar, B., Holmes, A., Kiely, K., Burkart, S., Adams, E. L., Weaver, R. G., Beets, M., & Armstrong, B. (2026). Not all screen time is sedentary: evidence from aligned smartphone sensing and accelerometry data in adults. Journal of Activity, Sedentary and Sleep Behaviors. https://doi.org/10.1186/s44167-026-00109-y

Image Credits: AI Generated

DOI: 10.1186/s44167-026-00109-y

Keywords: screen time, sedentary behaviour, smartphone use, physical activity, accelerometry, passive sensing, GGIR, SedUp algorithm, public health, mobile apps, measurement, adults