Journal of activity, sedentary and sleep behaviors · 2026
Not all screen time is sedentary: evidence from aligned smartphone sensing and accelerometry data in adults.
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Culverhouse Joshua, Finnegan Olivia L, Bowen Kaia, Nelakuditi Srihari, Ghosal Rahul, Radesky Jenny S, Adair Taylor, Restino Meghan, White James W, Zhong Zifei, Hadj-Amar Beniamino, Holmes Anthony, Kiely Keagan, Burkart Sarah, Adams Elizabeth L, Weaver R Glenn, Beets Michael, Armstrong Bridget
Аннотация
BACKGROUND: Screen time is frequently used as a proxy for sedentary behaviour in physical activity and public health research, an assumption largely derived from television viewing. However, because smartphones are portable, screentime can occur across diverse physical contexts. This raises uncertainty about whether it reliably reflects sedentary behaviour at the momentary level.
METHODS: This opportunistic analysis used data from an ongoing cohort study of adult caregivers of preschool-aged children. Smartphone screen time was objectively assessed using the Android-based passive sensing app Chronicle, and movement behaviour was assessed using wrist-worn accelerometers. Accelerometer data were processed using GGIR and the SedUp algorithm to classify epochs as sedentary or non-sedentary. Smartphone and movement data were aligned at 5-s epochs during waking wear time. Primary outcomes included the proportion of smartphone screen-use time occurring during sedentary versus non-sedentary behaviour. Secondary analyses examined inactive versus active behaviour during non-sedentary screen use, and app-level differences.
RESULTS: The analytic sample included 63 participants contributing 785 person-days (3.3-million 5-s epochs). At the participant level, the median proportion of smartphone use occurring during non-sedentary behaviour was 25.9%, with substantial inter-individual variability (range: 5.6-73.7%). Among non-sedentary screen-use epochs, 52.1% occurred during inactive behaviour and 47.9% occurred during active behaviour. App-level analyses revealed that social media applications were predominantly sedentary, whereas apps such as Phone, Maps, Camera, and YouTube showed higher proportions of non-sedentary use.
CONCLUSIONS: Smartphone screen time fails as a momentary proxy for sedentary behaviour because a substantial, variable, and app-dependent proportion occurs during non-sedentary behaviour. These findings may have implications for both the measurement and development of interventions aimed at reducing sedentary behaviour and/or smartphone use.
METHODS: This opportunistic analysis used data from an ongoing cohort study of adult caregivers of preschool-aged children. Smartphone screen time was objectively assessed using the Android-based passive sensing app Chronicle, and movement behaviour was assessed using wrist-worn accelerometers. Accelerometer data were processed using GGIR and the SedUp algorithm to classify epochs as sedentary or non-sedentary. Smartphone and movement data were aligned at 5-s epochs during waking wear time. Primary outcomes included the proportion of smartphone screen-use time occurring during sedentary versus non-sedentary behaviour. Secondary analyses examined inactive versus active behaviour during non-sedentary screen use, and app-level differences.
RESULTS: The analytic sample included 63 participants contributing 785 person-days (3.3-million 5-s epochs). At the participant level, the median proportion of smartphone use occurring during non-sedentary behaviour was 25.9%, with substantial inter-individual variability (range: 5.6-73.7%). Among non-sedentary screen-use epochs, 52.1% occurred during inactive behaviour and 47.9% occurred during active behaviour. App-level analyses revealed that social media applications were predominantly sedentary, whereas apps such as Phone, Maps, Camera, and YouTube showed higher proportions of non-sedentary use.
CONCLUSIONS: Smartphone screen time fails as a momentary proxy for sedentary behaviour because a substantial, variable, and app-dependent proportion occurs during non-sedentary behaviour. These findings may have implications for both the measurement and development of interventions aimed at reducing sedentary behaviour and/or smartphone use.