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Record W2901414297

Violent Video Gaming, Parent and Child Risk Factors, and Aggression in School-Age Children

2018· article· en· W2901414297 on OpenAlexfundaboutno aff
Erin Romanchych

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
FundersUniversity of Windsor
KeywordsAggressionPsychologyDevelopmental psychologyHuman factors and ergonomicsPoison controlInjury preventionSuicide preventionMedicineMedical emergency
DOInot available

Abstract

fetched live from OpenAlex

The present study examined links between children’s violent video game exposure and aggression, and the influence of parent and child risk factors (i.e., children’s negative affect and hostile attribution bias, parental monitoring, and children’s gender). Participants were 122 Canadian parent-child dyads (99 unique parents) including children between 7 and 10 years of age (41 girls, 81 boys; 72 mothers, 26 fathers). Parents completed pencil-and-paper questionnaires assessing children’s violent video game exposure, aggressive behaviour, negative affect, and parental monitoring of children’s media use (i.e., parental involvement, limit setting, and communication). Children completed pencil-and-paper questionnaires assessing violent video game exposure and hostile attribution bias. Parents’ perceptions about children’s video gaming and links with aggression were also explored during semi-structured interviews with 15 of the parents (10 mothers, 5 fathers). The analyses revealed that higher levels of parent-reported children’s violent video game exposure predicted higher levels of aggression. In addition, higher levels of children’s negative affect predicted higher levels of children’s aggression. Children’s negative affect was found to mediate the relation between children’s violent video game exposure (parent report) and aggression, such that higher levels of children’s violent video game exposure indirectly related to higher levels of children’s aggression, through higher levels of negative affect. Children’s hostile attribution bias was not predictive of children’s aggression, nor did it mediate the link between children’s violent video game exposure and aggression. In terms of parental monitoring, higher levels of children’s violent video game exposure were related to higher levels of parental involvement and communication. None of the parental monitoring variables (i.e., parental involvement, limit setting, and communication) were related to children’s aggression. The relation between children’s violent video game exposure and aggression did not vary based on levels of parental monitoring or children’s gender. Results from the thematic analysis of the interview data supported these findings. Parents believed that exposure to children’s violent video games would increase their risk of engaging in real world violence and imitating aggressive or violent behaviours from the video games. Parents also reported that children experienced negative reactions, such as aggression, to playing video games -- including violent video games. Parents thought that children’s reactions to playing violent video games varied based on children’s temperament, and that children might be at greater risk of experiencing negative reactions if they had certain traits (e.g., overly emotional, angry). In terms of parental monitoring, parents were more likely to monitor children’s gaming if parents, themselves, were interested in gaming or if children were playing games with violent content. Parents were more likely to discuss gaming with their children when children played video games with violent content. Similarly, parents tended to set limits on the content children were exposed to (i.e., violent games); however, most children were exposed to violence in video games. Overall, these findings identify parent and child factors (i.e., children’s negative affect, parental involvement and communication) that may mitigate or exacerbate the effects of playing violent video games, which can be useful for education on media use, intervention programs, and directions for future research.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.008
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.016
GPT teacher head0.244
Teacher spread0.228 · 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

Citations1
Published2018
Admission routes2
Has abstractyes

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