CoChat
Sign Up
Cited by 24Sleep and related disordersImpact of Technology on AdolescentsChild Development and Digital Technology

Are smartphones detrimental to adolescent sleep? an electronic diary study of evening smartphone use and sleep.

Open access
Tkaczyk, Michał, Lacko, David, Elavsky, Steriani, Tancoš, Martin, Smahel, David·2023·Computers in Human Behavior
DOI 10.1016/j.chb.2023.107946
Open this paper in CoChat — free account

Abstract

Previous research associated smartphone use with worsened sleep among adolescents. However, the prior findings were mainly based on cross-sectional, self-reported data, and a between-person level of analysis. This study examined between- and within-person associations for adolescents' smartphone use and multiple sleep outcomes: sleep onset time, sleep onset latency, sleep duration, subjective sleep quality, and subjective daily sleepiness. The participants were 201 Czech adolescents (aged 13–17) who daily reported their sleep outcomes, daily stressors, and other media use for 14 consecutive days via a custom-made research app on their smartphones. The app also collected logs of the participants' smartphone use. We found that interindividual differences within the average volume of smartphone use before sleep were not associated with differences in sleep outcomes. At the within-person level, we found that, when adolescents used smartphones before sleep for longer than usual, they went to sleep earlier and slept longer. However, these two associations were weak. No other sleep outcomes were affected by the increased use of a smartphone before sleep on a given day. We found no interaction effects for age, gender, insomnia symptoms, media use, or daily stressors. However, the association between smartphone use and earlier sleep onset time was stronger on nights before a non-school day. Our findings suggest that the link between smartphone use and adolescent sleep is more complex, and not as detrimental, as claimed in some earlier studies.

Integrity signals

Registry

Crossref · 10.1016/j.chb.2023.107946

Cites

103 of 103 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Many studies compared average screen time with average sleep and thus could not determine whether variation in screen time was associated with subsequent sleep that night.

    “Many studies compared average screen time with average sleep and thus could not determine whether variation in screen time was associated with subsequent sleep that night.17,18”

    From Screen Use at Bedtime and Sleep Duration and Quality Among Youths (2024) · cites this paper as [17]

  • The repeated-measures design and within-person analysis accounted for night-to-night variability, providing considerable advantages over studies that rely on between-person and aggregated data, which can introduce substantial confounding.

    “Importantly, our repeated-measures design and within-person analysis accounted for night-to-night variability, providing considerable advantages over studies that rely on between-person and aggregated data, which can introduce substantial confounding.17”

    From Screen Use at Bedtime and Sleep Duration and Quality Among Youths (2024) · cites this paper as [17]

  • Aggregated data provide a less accurate depiction of the association between screen use and sleep.

    “However, this research used aggregated data, which provide a less accurate depiction of the association between screen use and sleep.17”

    From Screen Use at Bedtime and Sleep Duration and Quality Among Youths (2024) · cites this paper as [17]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Tkaczyk, M., Lacko, D., Elavsky, S., Tancoš, M., & Smahel, D.
Affiliations
Masaryk University (CZ)
Corresponding author
Tkaczyk, Michał
ORCID
Venue
Computers in Human Behavior
Publisher
Elsevier BV
Published
2023-12
Volume
149
Pages
107946
ISSN
0747-5632 (ISSN-L)
DOI
10.1016/j.chb.2023.107946
OpenAlex
W4386392876
Cited by
24
References
103
Citations by year
2026: 8 · 2025: 10 · 2024: 6
FWCI
5.80
Type
journal article
Language
en
Open access
Licence
Locations
Computers in Human Behavior (publishedVersion, cc-by)
Funders
Grantová agentura České republiky (GX19–27828X)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
  • Social Sciences › Education › Child Development and Digital Technology
Keywords
smartphone use, adolescent sleep, sleep latency, sleep duration, subjective sleep quality, daytime sleepiness, within-person associations, between-person associations, insomnia symptoms, daily hassles

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 ›

Are you an author, or do you see a problem with this page? Request a review