Cited by 532Bullying, Victimization, and AggressionImpact of Technology on AdolescentsHate Speech and Cyberbullying Detection

Longitudinal and reciprocal relations of cyberbullying with depression, substance use, and problematic internet use among adolescents

Open access
Gámez-Guadix, Manuel, Orue, Izaskun, Smith, Peter K., Calvete, Esther·2013·Journal of Adolescent Health

Abstract

Purpose To analyze the temporal and reciprocal relationships between being a victim of cyberbullying (CB) and three frequent problems during adolescence: depressive symptoms, substance use, and problematic Internet use; also, to analyze whether the relationship between CB and these psychological and behavioral health problems differs as a function of being only a victim or being both bully and victim.Method A total of 845 adolescents (mean age = 15.2, SD = 1.2) completed measures at T1 and at T2, 6 months apart. The relationship among variables was analyzed using structural equation modeling.Results CB victimization at T1 predicted depressive symptoms and problematic Internet use at T2, and higher depressive symptoms and more substance use at T1 predicted more CB victimization at T2. However, the relationships of CB predicting substance use and problematic Internet use predicting CB were not significant. Bully-victims presented higher levels than victims of all three problem variables, both at T1 and T2.Conclusions CB is predictive of some significant psychological and behavioral health problems among adolescents. Intervention efforts should pay attention to these in the prevention and treatment of consequences of CB.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.jadohealth.2013.03.030

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

  • Cyberbullying can have physical effects on victims such as weight loss or gain, substance abuse, headache, abdominal pain and sleeping problems.

    “Cyberbullying can also have physical effects on victims such as weight loss or gain, substance abuse, headache, abdominal pain and sleeping problems (Gámez-Guadix et al., 2013;Jang et al., 2014).”

    From A review of cyberbullying and suggestions for online psychological therapy (2015) · cites this paper as Gámez-Guadix et al., 2013

    The Discussion (page unavailable) says substance use predicted later cyberbullying victimization, but cyberbullying did not appear to increase substance use—the opposite of presenting substance abuse as an effect. The paper does not address weight changes, headaches, abdominal pain, or sleeping problems. (LLM, conf=0.86)

    Checked by a reasoning model — may be wrong.

    Experimental — accuracy not yet measured
  • The relationship between psychological problems and cyberbullying victimization is bidirectional.

    “Research indicates that this relationship between psychological problems and cyberbullying victimization is bidirectional, as individuals with pre-existing conditions are more vulnerable to cyberbullying, which in turn exacerbates their symptoms84.”

    From Umbrella review of meta-analyses on the risk factors, protective factors, consequences and interventions of cyberbullying victimization (2024) · cites this paper as [84]

    The Discussion reports a reciprocal relationship between depressive symptoms and cyberbullying victimization among adolescents: each predicts an increase in the other. The Abstract shows that this does not extend to all problems studied: substance use predicted later victimization but not vice versa, while problematic Internet use showed the opposite pattern. The claim is therefore supported for depressive symptoms, but overgeneralizes to psychological problems as a whole. (LLM, conf=0.88)

    Experimental — accuracy not yet measured
  • Both cyber bullies and victims use the Internet as a coping mechanism in which they try to escape or avoid their feelings of distress.

    “research indicates that both cyber bullies and victims use the Internet as a coping mechanism in which they try to escape or avoid their feelings of distress (Gámez-Guadix et al., 2013).”

    From A review of cyberbullying and suggestions for online psychological therapy (2015) · cites this paper as Gámez-Guadix et al., 2013

    The Discussion reports that cyberbullying victimization predicted increased problematic Internet use and suggests that victims may use the Internet to escape distress. It does not establish this coping motive as a fact or extend it to cyberbullies. (LLM, conf=0.88)

    Experimental — accuracy not yet measured
  • The worst psychological impact has been related to being a bully/victim.

    “The worst psychological impact has been related to being a bully/victim.”

    From A review of cyberbullying and suggestions for online psychological therapy (2015) · cites this paper as Gámez-Guadix et al., 2013

  • Gámez-Guadix et al. (2013) reported depressive symptoms among victims (mean age 15.2 years, Spain, N=845).

    “Gámez-Guadix et al. (2013) | 15.2 (mean years) | 845 Spain | Victim | Depressive symptoms”

    From A review of cyberbullying and suggestions for online psychological therapy (2015) · cites this paper as Gámez-Guadix et al. (2013)

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

3 of the 43 references couldn’t be matched to a known paper.

Research works printed but not linked: 3

  1. Spanish Society of Epidemilogy. Una propuesta de medida de clase social (Proposal for a social class measure). Aten Primaria 2000;20:350e63.
  2. Derogatis LR. Brief Symptom Inventory 18: Administration, Scoring and Procedures Manual. Minneapolis, MN: NCS Pearson Inc, 2001.
  3. Ybarra ML, Mitchell KJ. Youth engaging in online harassment: Associations with caregiverechild relationships, Internet use, and personal character- istics. J Adolesc 2004;27:319e36.

Cited by

Sorted by citations

Authors
Gámez-Guadix, M., Orue, I., Smith, P. K., & Calvete, E.
Affiliations
  • Universidad de Deusto (ES)
  • Goldsmiths University of London (GB)
Venue
Journal of Adolescent Health
Publisher
Elsevier BV
Published
2013-10
Volume
53
Issue
4
Pages
446-452
ISSN
1054-139X (ISSN-L)
OpenAlex
W2163169807
Cited by
532
References
43
Citations by year
2026: 21 · 2025: 40 · 2024: 28 · 2023: 48 · 2022: 56 · 2021: 41 · 2020: 48 · 2019: 63 · 2018: 44 · 2017: 45 · 2016: 36 · 2015: 42 · 2014: 17 · 2013: 2
FWCI
47.91
Type
journal article
Language
en
Open access
Locations
  • Journal of Adolescent Health (publishedVersion)
  • PubMed (publishedVersion)
Funders
Ministerio de Economía y Competitividad (PSI2012-31550)
Topics
  • Social Sciences › Psychology › Social Psychology › Bullying, Victimization, and Aggression
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
  • Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
Keywords
cyberbullying, cyber victimization, bully-victims, depressive symptoms, substance use, problematic internet use, adolescents, bidirectional relationship, longitudinal associations, adolescent mental health
MeSH terms
Adolescent, Adolescent Behavior, Depressive Disorder, Female, Humans, Male, Spain, Crime Victims, Substance-Related Disorders, Internet, Bullying

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