# The Double-Edged Sword of Digital Engagement—How Digital Access and Internet Use Reshape Sleep Schedules and Underlying Mechanisms in Older Adults: Longitudinal Observational Study

**Authors:** Chi Zhang, Longxuan Lin, Li Wang, Han Hu, Heyang Zhang

PMC · DOI: 10.2196/79731 · JMIR Aging · 2025-11-05

## TL;DR

Digital engagement, like internet use, is linked to shorter sleep and later sleep times in older adults, with different effects for men, women, and urban vs. rural populations.

## Contribution

This study longitudinally examines how digital access and internet use affect sleep schedules in older adults, identifying underlying mechanisms and subgroup differences.

## Key findings

- Digital access and internet use are associated with shorter nocturnal and nap sleep durations in older adults.
- Digital engagement delays sleep onset time and has stronger effects on men and urban residents.
- Mechanisms include nonfarm employment, protein intake, memory, and daily living activities.

## Abstract

Given the rapid development of the digital economy and the sustained proliferation of the internet, digital engagement in older adults has garnered mounting attention from the academic community. However, research has yet to systematically examine the impact of digital engagement on sleep in this demographic.

This study aims to examine the association of digital engagement—operationalized as digital access and internet use duration—with the sleep schedules (nocturnal sleep duration, afternoon nap duration, and sleep onset time) of older adults in China, using longitudinal data and robust statistical modeling to explore longitudinal associations and potential mechanisms.

Data were derived from 4 waves (2014, 2016, 2018, and 2020) of the China Family Panel Studies, involving 16,784 older adults (≥60 y). We used panel fixed effects models and a random-effects ordered logit model to analyze the effects on continuous outcomes (nocturnal and nap sleep duration), controlling for time-invariant individual characteristics. As sleep onset time is an ordinal variable, a random-effects ordered logit model was used for this outcome. Moderation analyses were conducted by introducing interaction terms (digital engagement×sex and digital engagement×residence) into the models to examine heterogeneity across subgroups (urban or rural, men or women). Mediation analyses were performed using the Sobel test with year-fixed effects and the nonparametric bootstrap method (1000 resamples) to assess the significance of indirect effects via mechanistic pathways (nonfarm employment, protein intake, memory, depressive mood, and instrumental activities of daily living).

The study included a total of 16,784 older adults, with an average age of 69 (SE 6.946) years, including 9100 (54.22%) women and 7684 (45.78%) men. The results showed that both digital access (β=−.15, 95% CI −.25 to −.06; P=.002) and internet use time (β=−.07, 95% CI −.13 to −.01; P=.027) were significantly associated with significantly shorter sleep duration of older adults. Digital access was significantly associated with a significant reduction in the length of afternoon naps among older adults, while internet use did not have this effect; both digital access and internet use were significantly associated with a significant delay in older adults’ sleep onset time. Digital access was associated with older adults’ sleep schedules through its correlations with nonfarm employment, protein intake, memory, depressive mood, and instrumental activities of daily living. Digital access had a greater and more significant impact on men and urban older adults, while internet use had a greater and more significant impact on women and urban older adults.

The study indicates that digital engagement, such as the use of electronic devices, is associated with a reduction in both daily and nap sleep duration, as well as a delay in sleep onset, among older adults.

## Full-text entities

- **Diseases:** depressive mood (MESH:D003866)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## References

65 references — full list in the complete paper: https://tomesphere.com/paper/PMC12588592/full.md

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Source: https://tomesphere.com/paper/PMC12588592