The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Fear of missing out and sleep: Cognitive behavioural factors in adolescents' nighttime social media use
Open accessAbstract
INTRODUCTION: Social media use has been linked to poor adolescent sleep outcomes, but the mechanisms behind this association are not yet well understood. This study examines links between adolescents' social media habits, fear of missing out and sleep outcomes, using path analysis to evaluate a model of proposed underlying mechanisms. METHODS: Adolescents aged 12-18 years (N = 101) completed questionnaire measures. RESULTS: Nighttime social media use was associated with later bedtimes, increased pre-sleep cognitive arousal, longer sleep onset latency and shorter sleep duration. Path analysis supported a model whereby fear of missing out predicted shorter sleep duration via two distinct mechanisms: (1) at a behavioural level, by driving late night social media use, which delays bedtimes; (2) at a cognitive level, by increasing pre-sleep cognitive arousal, thus further delaying sleep onset. CONCLUSIONS: Efforts to develop and evaluate intervention strategies should therefore consider not only social media behaviours but also underlying cognitive factors, such as fear of missing out.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“Third, electronic device use may cause more difficulties falling asleep by increasing cognitive and affective arousal at bedtime, which may, in turn, lead to more difficulty falling asleep and poorer sleep quality [25].”
From A serial mediation model of social media addiction and college students' academic engagement: the role of sleep quality and fatigue (2023) · cites this paper as [25]
In the citing paper
“Bedtime social media use can delay sleep onset,14 with some adolescents reporting difficulties disengaging from social media to sleep.13”
From Social media use and adolescent sleep patterns: cross-sectional findings from the UK millennium cohort study (2019) · cites this paper as [14]
In the citing paper
“Social media use may also impact on the quality of sleep via increased arousal, not simply through light exposure,18 but particularly via cognitive and social activity.12 14 19”
From Social media use and adolescent sleep patterns: cross-sectional findings from the UK millennium cohort study (2019) · cites this paper as [14]
In the citing paper
“Available research on social media use and sleep is often left questioning whether reported effects could be explained by other individual factors: for example, if more anxious, depressed or sedentary adolescents may tend to both use social media more and report poorer sleep.12 14”
From Social media use and adolescent sleep patterns: cross-sectional findings from the UK millennium cohort study (2019) · cites this paper as [14]
In the citing paper
“sleep onset latency and presleep cognitive arousal is predicted by underlying concerns about potentially missing out, rather than social media behaviour itself.14”
From Social media use and adolescent sleep patterns: cross-sectional findings from the UK millennium cohort study (2019) · cites this paper as [14]
In the citing paper
“This has been one area of development in the sleep literature over the last 5 years, with more studies examining not only the time that participants spend using social media, but also their experiences of-and motivations for-these interactions [8,12,17,38].”
From Understanding Links Between Social Media Use, Sleep and Mental Health: Recent Progress and Current Challenges (2019) · cites this paper as [12]
In the citing paper
“This underlying fear of missing out has been linked to shorter sleep duration via both a behavioural pathway (by driving late night social media use, which delays bedtimes) and a cognitive pathway (by increasing pre-sleep cognitive arousal, thus further delaying sleep onset) [12].”
From Understanding Links Between Social Media Use, Sleep and Mental Health: Recent Progress and Current Challenges (2019) · cites this paper as [12]
Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
Principles and Practice of Structural Equation Modeling
Tabri, N., & Elliott, C. M. (2012) · Canadian Graduate Journal of Sociology and Criminology · doi:10.15353/cgjsc.v1i1.3787 · Cited by 39,094
(1998) · Cited by 36,049
lavaan : An R Package for Structural Equation Modeling
Rosseel, Y. (2012) · Journal of Statistical Software · doi:10.18637/jss.v048.i02 · Cited by 27,955
Alternative Ways of Assessing Model Fit
Browne, M. W., & Cudeck, R. (1992) · Sociological Methods & Research · doi:10.1177/0049124192021002005 · Cited by 27,200
Kennedy, P. (1979) · Cited by 4,340
Motivational, emotional, and behavioral correlates of fear of missing out
Przybylski, A. K., Murayama, K., DeHaan, C. R., & Gladwell, V. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.02.014 · Cited by 3,932
The Efficacy of Cognitive Behavioral Therapy: A Review of Meta-analyses
Hofmann, S. G., Asnaani, A., Vonk, I. J. J., Sawyer, A. T., & Fang, A. (2012) · Cognitive Therapy and Research · doi:10.1007/s10608-012-9476-1 · Cited by 3,445
Information bias in health research: definition, pitfalls, and adjustment methods
Althubaiti, A. (2016) · Journal of Multidisciplinary Healthcare · doi:10.2147/jmdh.s104807 · Cited by 3,018
Cited by
Sorted by citations
Does time spent using social media impact mental health?: An eight year longitudinal study
Coyne, S. M., Rogers, A. A., Zurcher, J. D., Stockdale, L., & Booth, M. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2019.106160 · Cited by 701
Franchina, V., Vanden Abeele, M., Van Rooij, A. J., Lo Coco, G., & De Marez, L. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15102319 · Cited by 411
Gupta, M., & Sharma, A. (2021) · World Journal of Clinical Cases · doi:10.12998/wjcc.v9.i19.4881 · Cited by 520
Social media use and mental health and well-being among adolescents: a scoping review
Schønning, V., Hjetland, G. J., Aarø, L. E., & Skogen, J. C. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01949 · Cited by 288
Fear of missing out and social networking sites use and abuse: A meta-analysis
Fioravanti, G., Casale, S., Benucci, S. B., Prostamo, A., Falone, A., Ricca, V., & Rotella, F. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.106839 · Cited by 367
Metadata
- Authors
- Scott, H., & Woods, H. C.
- Affiliations
- University of Glasgow (GB)
- Corresponding author
- Scott, Holly
- Venue
- Journal of Adolescence
- Publisher
- Wiley
- Published
- 2018-07-20
- Volume
- 68
- Issue
- 1
- Pages
- 61-65
- ISSN
- 0140-1971 (ISSN-L)
- 1095-9254
- OpenAlex
- W2883926495
- Cited by
- 248
- References
- 22
- Citations by year
- 2026: 31 · 2025: 26 · 2024: 39 · 2023: 34 · 2022: 32 · 2021: 37 · 2020: 22 · 2019: 24 · 2018: 3
- FWCI
- 28.15
- Type
- journal article
- Language
- en
- Open access
- green
- eprints.gla.ac.uk
- Licence
- Locations
- Journal of Adolescence (publishedVersion)
- PubMed (publishedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
- 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
- fear of missing out, sleep, adolescents, sleep latency, sleep duration, bedtime, sleep interventions
- MeSH terms
- Adolescent, Adolescent Behavior, Child, Fear, Female, Humans, Male, Surveys and Questionnaires, Sleep Deprivation, Time Factors, Social Media
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
