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Record W4379656144 · doi:10.54254/2753-7048/6/20220647

Factors that Predispose Teens to Video Game Addiction during COVID-19

2023· article· en· W4379656144 on OpenAlexaff
Zhouhong Li

Bibliographic record

VenueLecture Notes in Education Psychology and Public Media · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAddictionEntertainmentPsychologyIsolation (microbiology)Video gameCoronavirus disease 2019 (COVID-19)PandemicSocial isolationSocial psychologyDevelopmental psychologyInternet privacyMedicinePsychiatryPolitical scienceMultimediaComputer science

Abstract

fetched live from OpenAlex

In today's world, video games are a common source of entertainment, particularly among teens. Teenage gaming addiction has gradually become a very common thing. In recent years, with the outbreak of COVID-19, the emergence of many external factors has led to a gradual increase in video game addiction among teenagers. This is what this paper needs to discuss. External factors such as family factors, friends, social needs factors, and other environmental factors are discussed in this paper. In the article, the content of various studies is analysed and finds that adolescent video game addiction is related to external factors during COVID-19. The relationship between a child and a parent and the loss of a loved one during the pandemic can have an impact on a child's behavior. Friends are also an indispensable factor. The desire to seek socializing with the outside world during the epidemic will also be a reason. Because of this pandemic, both isolation and online classes have greatly affected people's lives, including on the topic of teenage video game addiction. This provides some ideas and theoretical basis for the exact related research later.

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.051
GPT teacher head0.390
Teacher spread0.339 · 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.

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
Published2023
Admission routes1
Has abstractyes

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