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Record W3126523774 · doi:10.4309/jgi.2021.46.11

Are Some Subtypes of Video Gamer More at Risk for Gambling Issues? A Latent Class Analysis of a Canadian Sample of University Students

2021· article· en· W3126523774 on OpenAlexaffvenueabout
Jeffery C. S. Biegun, Jason D. Edgerton, Matthew T. Keough

Bibliographic record

VenueJournal of Gambling Issues · 2021
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsYork UniversityUniversity of Manitoba
Fundersnot available
KeywordsHumanitiesPsychologyVideo gameArtMultimediaComputer science

Abstract

fetched live from OpenAlex

Recently there has been growing interest in identifying links between video game playing and problem gambling. As video games continue to take on more gambling-like elements such as loot boxes, there is rising concern that they represent a potential pathway towards problem gambling. In this study, we explored video gamer profiles in a sample of Canadian undergraduate university students (n = 687) to examine whether subgroups of gamers had different risk profiles for problem video gaming and/or problem gambling. Three predominant subgroups emerged: universal, free-to-play, and general gamer classes. Whereas the free-to-play class was associated with higher average amounts of time spent playing video games, the universal class was associated with higher average scores on measures of problem video gaming, problem gambling, and impulsivity. Although motivational differences were evident, there were no significant mental health differences among subgroups in this sample.RésuméOn s’intéresse de plus en plus depuis peu de temps à l’établissement de liens entre la pratique des jeux vidéo et le jeu compulsif. À mesure que les jeux vidéo comportent davantage d’éléments de jeux de hasard comme des coffres à butin, on s’inquiète davantage du fait qu’ils puissent mener au jeu compulsif. Cette étude a examiné le profil de joueurs de jeux vidéo parmi un échantillon d’étudiants canadiens de premier cycle (n = 687) afin de déterminer si les sous-groupes de joueurs présentaient un profil de risque différent pour le jeu vidéo compulsif et/ou le jeu compulsif. Trois sous-groupes prédominants sont ressortis : universel, gratuit et général. Le groupe des jeux gratuits était associé à une plus grande quantité de temps consacrée à jouer à des jeux vidéo, le groupe universel était associé pour sa part à un pointage moyen plus élevé au titre des paramètres de mesure du jeu vidéo compulsif, du jeu compulsif et de l’impulsivité. Les différences de motivation étaient évidentes, mais les sous-groupes de cet échantillon ne présentaient aucune différence importante sur le plan de la santé mentale.

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 score0.017
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
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 head0.209
GPT teacher head0.427
Teacher spread0.218 · 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

Citations2
Published2021
Admission routes3
Has abstractyes

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