Evidence map›Paper›PMID 41191871›Full record

Observational studyJMIR aging2025

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.

Chi Zhang, Longxuan Lin, Li Wang, Han Hu, Heyang Zhang

Abstract readObservational Study
In one paragraph

Observational study in JMIR aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Chi ZhangLanzhou University, No. 222, Tianshui South Road, Chengguan District, Lanzhou, Gansu Province, 730000, China, 86 18759217889.ORCID http://orcid.org/0000-0003-1431-7722
Longxuan LinLanzhou University, No. 222, Tianshui South Road, Chengguan District, Lanzhou, Gansu Province, 730000, China, 86 18759217889.ORCID http://orcid.org/0009-0004-1546-6134
Li WangSchool of Philosophy and Sociology, Northwest Normal University, Lanzhou, China.ORCID http://orcid.org/0009-0003-7106-5127
Han HuSchool of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China.ORCID http://orcid.org/0000-0001-8500-1536
Heyang ZhangLanzhou University, No. 222, Tianshui South Road, Chengguan District, Lanzhou, Gansu Province, 730000, China, 86 18759217889.ORCID http://orcid.org/0009-0004-6005-8527

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 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. Objective: 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. Methods: 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). Results: 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. Conclusions: 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.

Indexed as

Internet AccessInternet UseSleepAgedChinaFemaleHumansLongitudinal StudiesMaleMiddle Agedafternoon napcohort studydigital engagementdigital healthmediation effectsleep durationsleep onset time

Identifiers

PMID41191871
PMCPMC12588592

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.