CoChat
Sign Up
Cited by 10Impact of Technology on AdolescentsSleep and related disordersSubstance Abuse Treatment and Outcomes

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

S100B and Neuron-Specific Enolase Levels as Brain Injury Biomarkers in Internet Addiction: Effect of Sleep

Demirci, Esra, Tastepe, Neslihan, Gul, Melike Kevser, Ozmen, Sevgi, Kilic, Eser·2023·Pediatric Neurology
DOI 10.1016/j.pediatrneurol.2023.08.029
Open this paper in CoChat — free account

Abstract

Background Comorbidity of Internet addiction (IA) with sleep disruptions is common in adolescents. There is evidence that the levels of brain injury markers could be affected by sleep disruptions. In this study, we aimed to evaluate the relationship between sleep quality and these biomarkers within the framework of the relationship between IA and sleep disruptions. Methods A total of 65 drug-free adolescents with newly diagnosed IA, aged 12 to 18 years, were included in the study, and they were divided into two groups considering the comorbidities of attention-deficit/hyperactivity disorder (ADHD) and social anxiety. The control group consisted of 30 healthy children. The participants were asked to complete the Young Internet Addiction Scale, Pittsburgh Sleep Quality Index (PSQI), Morningness Eveningness Questionnaire, Beck's Depression Inventory, Beck's Anxiety Inventory, and Barratt Impulsiveness Scale-11. Blood samples were taken between 8 and 9 am to analyze S100 calcium-binding protein B (S100B) and neuron-specific enolase (NSE) levels with enzyme-linked immunosorbent assay. Results Plasma S100B and NSE levels were found to be statistically significantly higher in the IA with ADHD and the IA with anxiety groups than in healthy controls. NSE and S100B levels were found to be correlated with PSQI scores in both the IA groups. Also, there was a positive correlation between these biomarkers and IA severity. Conclusions Decreased sleep quality and daily sleep duration in IA might cause brain injury, resulting in an increase in the severity of the addiction. Prospective studies with large samples are needed to better explain the IA-sleep-brain injury relationship.

Overview

Integrity signals

Registry

Crossref · 10.1016/j.pediatrneurol.2023.08.029

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

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

Verification

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?

Citations

Cites

Research works printed but not linked: 36

  1. Alimoradi, 2019, Internet addiction and sleep problems: a systematic review and meta-analysis, Sleep Med Rev, 47, 51, 10.1016/j.smrv.2019.06.004 · DOI
  2. Jain, 2020, Study of internet addiction and its association with depression and insomnia in university students, J Family Med Prim Care, 9, 1700, 10.4103/jfmpc.jfmpc_1178_19 · DOI
  3. Cheung, 2011, The effects of insomnia and internet addiction on depression in Hong Kong Chinese adolescents: an exploratory cross-sectional analysis, J Sleep Res, 20, 311, 10.1111/j.1365-2869.2010.00883.x · DOI
  4. Sami, 2018, The effect of sleep disturbances and internet addiction on suicidal ideation among adolescents in the presence of depressive symptoms, Psychiatry Res, 267, 327, 10.1016/j.psychres.2018.03.067 · DOI
  5. Lu, 2023, Network analysis of internet addiction and sleep disturbance symptoms, Prog Neuropsychopharmacol Biol Psychiatry, 125, 110737, 10.1016/j.pnpbp.2023.110737 · DOI
  6. Kitazawa, 2018, Associations between problematic internet use and psychiatric symptoms among university students in Japan, Psychiatry Clin Neurosci, 72, 531, 10.1111/pcn.12662 · DOI
  7. Li, 2017, Insomnia partially mediated the association between problematic internet use and depression among secondary school students in China, J Behav Addict, 6, 554, 10.1556/2006.6.2017.085 · DOI
  8. Yen, 2014, The association of internet addiction symptoms with anxiety, depression, and self-esteem among adolescents with attention-deficit/hyperactivity disorder, Compr Psychiatry, 55, 1601, 10.1016/j.comppsych.2014.05.025 · DOI
  9. Obeid, 2019, Internet addiction among Lebanese adolescents: the role of self-esteem, anger, depression, anxiety, social anxiety, and fear, impulsivity, and aggression—a cross-sectional study, J Nerv Ment Dis, 207, 838, 10.1097/NMD.0000000000001034 · DOI
  10. Bozkurt, 2013, Prevalence and patterns of psychiatric disorders in referred adolescents with Internet addiction, Psychiatry Clin Neurosci, 67, 352, 10.1111/pcn.12065 · DOI
  11. Mayes, 2009, Sleep problems in children with autism, ADHD, anxiety, depression, acquired brain injury, and typical development, Sleep Med Clin, 4, 19, 10.1016/j.jsmc.2008.12.004 · DOI
  12. Peskind, 2001, Cerebrospinal fluid S100B is elevated in the earlier stages of Alzheimer's disease, Neurochem Int, 39, 409, 10.1016/S0197-0186(01)00048-1 · DOI
  13. Schmidt, 2004, Serum S100B in pregnancy-related hypertensive disorders: a case-control study, Clin Chem, 50, 435, 10.1373/clinchem.2003.027391 · DOI
  14. Herrmann, 2000, Release of glial tissue-specific proteins after acute stroke: a comparative analysis of serum concentrations of protein S-100B and glial fibrillary acidic protein, Stroke, 31, 2670, 10.1161/01.STR.31.11.2670 · DOI
  15. Pleines, 2001, 100 β reflects the extent of injury and outcome, whereas neuronal-specific enolase is a better indicator of neuroinflammation in patients with severe traumatic brain injury, J Neurotrauma, 18, 491, 10.1089/089771501300227297 · DOI
  16. Van Eldik, 2003, The Janus face of glial-derived S100B: beneficial and detrimental functions in the brain, Restor Neurol Neurosci, 21, 97
  17. Benedict, 2014, Acute sleep deprivation increases serum levels of neuron-specific enolase (NSE) and S100 calcium-binding protein B (S-100B) in healthy young men, Sleep, 37, 195, 10.5665/sleep.3336 · DOI · Paper page
  18. Zhang, 2018, Patients with chronic insomnia disorder have increased serum levels of neurofilaments, neuron-specific enolase, and S100B: does organic brain damage exist?, Sleep Med, 48, 163, 10.1016/j.sleep.2017.12.012 · DOI
  19. Tao, 2010, Proposed diagnostic criteria for internet addiction, Addiction, 105, 556, 10.1111/j.1360-0443.2009.02828.x · DOI · Paper page
  20. Young, 1998, The relationship between depression and Internet addiction, Cyberpsychol Behav, 1, 25, 10.1089/cpb.1998.1.25 · DOI
  21. Buysse, 1989, The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research, Psychiatry Res, 28, 193, 10.1016/0165-1781(89)90047-4 · DOI · Paper page
  22. Agargun, 2007, Turkish version of morningness-eveningness questionnaire (MEQ), Sleep Hypn, 9, 16
  23. Ardıc, 2020, Fazla Kilolu ve Obez Adolesanların Depresyon Anksiyete ve Stres Düzeyleri, TJFMPC, 14, 384, 10.21763/tjfmpc.665955 · DOI
  24. Tamam, 2013, The study for Turkish version of Barratt Impulsivity Scale Short Form (BIS-11-SF), Arch Neuropsychiatry, 50, 130, 10.4274/npa.y6296 · DOI
  25. Conners, 1998, The revised Conners' Parent Rating Scale (CPRS-R): factor structure, reliability, and criterion validity, J Abnorm Child Psychol, 26, 257, 10.1023/A:1022602400621 · DOI · Paper page
  26. You, 2021, Mediating effects of rumination and bedtime procrastination on the relationship between internet addiction and poor sleep quality, J Behav Addict, 9, 1002, 10.1556/2006.2020.00104 · DOI
  27. Chen, 2016, Sleep problems and internet addiction among children and adolescents: a longitudinal study, J Sleep Res, 25, 458, 10.1111/jsr.12388 · DOI
  28. Moderie, 2017, Circadian phase, dynamics of subjective sleepiness and sensitivity to blue light in young adults complaining of a delayed sleep schedule, Sleep Med, 34, 148, 10.1016/j.sleep.2017.03.021 · DOI
  29. Crowley, 2015, Increased sensitivity of the circadian system to light in early/mid-puberty, J Clin Endocrinol Metab, 100, 4067, 10.1210/jc.2015-2775 · DOI · Paper page
  30. Gau, 2004, Similarities and differences in sleep-wake patterns among adults and their children, Sleep, 27, 299, 10.1093/sleep/27.2.299 · DOI
  31. Kauderer, 2013, Differences in time use among chronotypes in adolescents, Biol Rhythm Res, 44, 601, 10.1080/09291016.2012.721687 · DOI
  32. Vollmer, 2012, Outdoor light at night (LAN) is correlated with eveningness in adolescents, Chronobiol Int, 29, 502, 10.3109/07420528.2011.635232 · DOI
  33. Oades, 2010, Attention-deficit hyperactivity disorder (ADHD) and glial integrity: S100B, cytokines and kynurenine metabolism—effects of medication, Behav Brain Funct, 6, 29, 10.1186/1744-9081-6-29 · DOI · Paper page
  34. Ouadih-Moran, 2023, Is S100B involved in attention-deficit/hyperactivity disorder (ADHD)? Comparisons with controls and changes following a triple therapy containing methylphenidate, melatonin and ω-3 PUFAs, Nutrients, 15, 712, 10.3390/nu15030712 · DOI
  35. Shen, 2022, Combining S100B and cytokines as neuro-inflammatory biomarkers for diagnosing generalized anxiety disorder: a proof-of-concept study based on machine learning, Front Psychiatry, 13, 10.3389/fpsyt.2022.881241 · DOI
  36. Cagatay Kaya, 2015, Serum S100B protein levels in patients with panic disorder: effect of Treatment with selective Serotonine Reuptake Inhibitors, Psychiatry Investig, 12, 260, 10.4306/pi.2015.12.2.260 · DOI

Cited by

Sorted by citations

See all 10

Metadata

Authors
Demirci, E., Tastepe, N., Gul, M. K., Ozmen, S., & Kilic, E.
ORCID
Demirci, Esra
Venue
Pediatric Neurology
Publisher
Elsevier BV
Published
2023-12
Volume
149
Pages
93-99
ISSN
0887-8994 (ISSN-L)
DOI
10.1016/j.pediatrneurol.2023.08.029
OpenAlex
W4386157711
Cited by
10
References
4
Citations by year
2026: 2 · 2025: 5 · 2024: 3
FWCI
4.32
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • Pediatric Neurology (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Erciyes Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi (TSA-2020-9958)
  • Erciyes Üniversitesi
Topics
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
  • Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
Keywords
internet addiction, sleep quality, S100B, neuron-specific enolase, brain injury biomarkers, adolescents, ADHD comorbidity, sleep disruption, impulsivity, addiction severity
MeSH terms
Internet Addiction Disorder, Adolescent, Brain Injuries, Child, Humans, Phosphopyruvate Hydratase, Prospective Studies, Sleep, Biomarkers, Internet, S100 Calcium Binding Protein beta Subunit

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