The impact of social networks on sleep among a cohort of college students
Open accessAbstract
BACKGROUND: Sleep duration and quality are associated with physical and mental wellbeing. This paper examines social network effects on individual level change in the sleep quantity and quality from late adolescence to emerging adulthood and its associated factors, including the influence of peers on sleep behavior and the impact of changes in network size. METHODS: We use sleep data from 619 undergraduates at the University of Notre Dame obtained via Fitbit devices as part of the NetHealth project. The data were collected between August 16, 2015 and May 13, 2017. We model trends in sleep behaviors using latent growth-curve models. RESULTS: Controlling for the many factors known to impact sleep quantity and quality, we find two social network effects: increasing network size is associated with less sleep and a student's sleep levels are influenced by his or her peers. While we do not find any consistent decline in sleep quantity over the 637 days, daily fluctuations in sleep quantity are associated with changes in network size and the composition of a student's network. As a student's network gets bigger, s/he sleeps less, and when a student's contacts sleep more (or less) than s/he does, the student becomes more like his or her contacts and sleeps more (or less). CONCLUSIONS: Social networks can and do impact sleep, especially sleep quantity. In contexts where students want to have larger networks, the difficulties of increasing network size and maintaining larger networks negatively impact sleep. Because of peer influence, the effectiveness of interventions designed to improve sleep practices could be increased by leveraging student social networks to help diffuse better sleep habits.
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The first year of college is a major life transition period for many college students, marked by greater independence and autonomy, academic workload, efforts to establish new sleep habits outside the childhood home, and formation of new friendships.
“The first year of college is a major life transition period for many college students (15), marked by greater independence and autonomy, academic workload, efforts to establish new sleep habits outside the childhood home (8), and formation of new friendships (16).”
From Nightly sleep duration predicts grade point average in the first year of college (2023) · cites this paper as [16]
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- Authors
- Wang, C., Mattingly, S., Payne, J., Lizardo, O., & Hachen, D. S.
- Affiliations
- Wayne State University (US)
- University of Notre Dame (US)
- Corresponding author
- Wang, Cheng
- Venue
- SSM - Population Health
- Publisher
- Elsevier BV
- Published
- 2021-12
- Volume
- 16
- Pages
- 100937
- ISSN
- 2352-8273 (ISSN-L)
- PMC
- PMC8502769
- OpenAlex
- W3204227584
- Cited by
- 18
- References
- 68
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 5 · 2023: 2 · 2022: 5
- FWCI
- 2.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- SSM - Population Health (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
- Funders
- National Institutes of Health (1 R01 L117757-01A1)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Health Sciences › Health Professions › General Health Professions › Health and Lifestyle Studies
- Keywords
- social networks, sleep duration, sleep quality, peer influence, network size, university students, emerging adulthood, late adolescence, Fitbit, sleep behavior change, network composition, health behavior interventions
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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