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Record W4414402550 · doi:10.22215/cujs.v5i2.5308

Stuck in a Loop: Rumination as a Mediator in the Relationship Between High School Bullying Victimization and Depression

2025· article· en· W4414402550 on OpenAlexaffabout
Tina Daniels, Lisa Sarraf

Bibliographic record

VenueCarleton undergraduate journal of science. · 2025
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsCarleton University
Fundersnot available
KeywordsRuminationMental healthPsychological interventionDepression (economics)MindfulnessSuicide preventionInjury preventionAssociation (psychology)

Abstract

fetched live from OpenAlex

Victims of bullying are more likely to engage in persistent negative thoughts about their experiences, which can include intrusive and deliberate rumination. Rumination is problematic since it can exacerbate adverse mental health outcomes over time, including depression. The current study investigated whether either of these types of rumination would mediate the association between high school victimization and depression in early adulthood. Intrusive and deliberate rumination were separately analyzed to contribute to limited research analyzing intrusive thoughts in rumination, and mixed findings implicating deliberate rumination with improved mental health outcomes. Undergraduate students from a large Canadian university (N = 485, Mage = 19.08) completed an online questionnaire assessing high school bullying victimization, event-related rumination, and depression. The results revealed that both intrusive and deliberate rumination partially mediated the relationship between high school bullying victimization and depression. These findings suggest that rumination, whether intrusive or deliberate, is a risk factor for mental health problems following victimization, which can persist in the long term. Therefore, interventions aimed at enhancing mindfulness and reducing rumination should be provided to victims of bullying to mitigate the risk of negative psychological outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.322
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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