# Sleep and smartphone use: Within and between-person relationships from an objective longitudinal smartphone and wearable data donation study

**Authors:** Paulien Decorte, Karolien Poels, Cedric Vuye, Jonas Lembrechts, Ablenya Barros, Karolien Couscheir, Gert-Jan De Bruijn

PMC · DOI: 10.1371/journal.pdig.0001232 · PLOS Digital Health · 2026-02-13

## TL;DR

This study finds that smartphone use and sleep are linked through daily habits, with in-bed phone use sometimes associated with longer sleep.

## Contribution

The study uses objective longitudinal data to reveal within- and between-person relationships between smartphone use and sleep.

## Key findings

- More total smartphone use increases same-day in-bed smartphone use.
- Greater in-bed smartphone use is linked to slightly longer sleep duration the same night.
- Strong day-to-day associations suggest stable individual habits in smartphone use and sleep.

## Abstract

Poor sleep is common and detrimental to health. Smartphone use is often noted as a sleep disruptor, but evidence remains limited and inconsistent. This necessitates research focused on objective, longitudinal designs, as well as analytical approaches that can reveal lagged and reciprocal relationships that capture within- and between-person effects. To address these gaps, the current study investigated within- and between-person lagged and reciprocal effects of sleep duration and smartphone use of 68 participants through longitudinal and objective data donated from iPhones and Apple Watches across 14 consecutive days. Apple Watches objectively measured total sleep and sleep stage durations (REM, core, and deep sleep), while iPhones assessed total smartphone use duration and in-bed smartphone use. Two Dynamic Structural Equation Models (DSEMs), one with total sleep and one with sleep broken down into three sleep stages, were conducted. At the within-person level, more total smartphone use increased same-day in-bed smartphone use, β = .25 (95% CI .20, .31), which in turn led to more same-day overall sleep, β = .08 (95% CI .02, .14). Additionally, results indicated stable between-person habits, with strong day-to-day associations for each variable with its own next-day value, β = .53-.82 (95% CI .47, .88). Findings contradict the perspective of smartphones as sleep disruptors, despite leaving open whether this added sleep means poorer rest or a real benefit of in-bed smartphone use. Furthermore, the strength of the between-person results emphasizes the importance of habits in this relationship. In studying day-to-day smartphone use and sleep, these findings provide nuanced empirical insights supporting health and policy recommendations regarding smartphone use and sleep hygiene.

Poor sleep is widespread and linked to many health problems. Smartphone use is often blamed for making sleep worse. However, past findings have been mixed, and many studies rely on self-reports or short-term designs. In this study, we examined how daily smartphone use and sleep relate to each other over time using objective data. We analyzed two weeks of real-world data from iPhones and Apple Watches worn by 68 adults. This allowed us to track how much people used their phones, how often they used them in bed, and how long they slept each night, including different types of sleep.

We found that on days when people used their smartphones more overall, they were also more likely to use them in bed. Surprisingly, greater in-bed smartphone use was linked to slightly longer sleep duration the same night. These patterns suggest that smartphones may not always reduce sleep time, as is commonly assumed. At the same time, we observed strong and stable individual habits: people who tended to sleep or use their phones more on one day were likely to do so again the next day. Overall, our findings highlight the importance of daily habits and suggest a more nuanced relationship between smartphone use and sleep than simple disruption.

## Full-text entities

- **Diseases:** Poor sleep (MESH:D012893)

## Full text

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## Figures

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## References

38 references — full list in the complete paper: https://tomesphere.com/paper/PMC12904418/full.md

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Source: https://tomesphere.com/paper/PMC12904418