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Sociodemographic factors and lifestyle behaviours associated with bullying victimization and perpetration in a sample of Brazilian adolescents

2024· article· en· W4396862304 on OpenAlexaff
Bruno Nunes de Oliveira, Bruno Gonçalves Galdino da Costa, Marcus Vinícius Veber Lopes, Rafael Martins da Costa, Kelly Samara da Silva

Bibliographic record

VenueCiência & Saúde Coletiva · 2024
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsNipissing University
FundersFundação de Amparo à Pesquisa do Estado do AmazonasConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsPsychological interventionPsychologyLogistic regressionClinical psychologyOddsInjury preventionHuman factors and ergonomicsSuicide preventionOccupational safety and healthPoison controlAlcohol consumptionMedicinePsychiatryAlcoholEnvironmental health

Abstract

fetched live from OpenAlex

This article aims to identify the association of sociodemographic factors and lifestyle behaviours with bullying perpetration and victimization among high school students. The adolescents (n=852) answered a questionnaire about bullying (victims and perpetrators), sociodemographic factors (sex, age, maternal education, and participant's work status), tobacco use, alcohol use, illicit drug experimentation, physical activity, screen time, and sleep duration. Multilevel logistic regression models were performed. Older adolescents were less likely to be victims of bullying. Females were less likely to be perpetrators or victims of bullying. Adolescents who were working were more likely to be involved in bullying in both forms. Participation in non-sport activities and alcohol consumption were associated with higher odds of bullying victimization. We have identified specific populational subgroups that are more susceptible to being victims and/or perpetrators of bullying, which could support tailor-specific interventions to prevent bullying.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.265
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2024
Admission routes1
Has abstractyes

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