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This paper is in the following e-collection/theme issue:

Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (3203) Prevention and Health Promotion (2257) Cross-Sectional Studies in Public Health (1288) Insomnia and Sleep Hygiene (309) Internet Access and Digital Technology Use in an Elderly Population (614) Sleep Monitoring, Sleep Quality, Sleep Disorders (345) Mental Health Issues in Elderly Patients and Geriatric Psychiatry (307)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71030, first published .
Elderly man sleeping peacefully in a comfortable bed

Association Between Internet Use and Sleep Health Among Middle-Aged and Older Chinese Individuals: Nationwide Longitudinal Study

Association Between Internet Use and Sleep Health Among Middle-Aged and Older Chinese Individuals: Nationwide Longitudinal Study

Authors of this article:

Xueqin Li1, 2 Author Orcid Image ;   Jin Liu3, 4 Author Orcid Image ;   Ning Huang5 Author Orcid Image ;   Wanyu Zhao5 Author Orcid Image ;   Hongbo He1, 2 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Pan Y, Zhang K, Wei Y, Huang Y, Long C, Yang C, Tang S. Associations Between Short-Video Platform Use and Health Across Health Distribution and Usage Behaviors in China: Cross-Sectional Questionnaire Study. Journal of Medical Internet Research 2026;28:e86526 View
  2. Mu T, Xu R, Zhu Q. Gender Differences in Sleep Deprivation and Quality Among Spousal Caregivers of Disabled Partners: A Nationwide Cross-Sectional Study. INQUIRY: The Journal of Health Care Organization, Provision, and Financing 2026;63 View
  3. Wu Y, Yang Y, Bosurgi R. Relationship Between Internet Use Purposes and Depressive Symptoms Among Chinese Older Adults: A Cross‐Lagged Panel Network Analysis. Depression and Anxiety 2026;2026(1) View
  4. Wang F, Qiao H, Zheng Y, Wu S, Ni Y, He X. Sleep duration, sleep quality, and daytime napping in relation to incident cardiometabolic multimorbidity across three national aging cohorts: a prospective, interpretable machine learning study. Frontiers in Nutrition 2026;13 View