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Record W3121407317 · doi:10.4309/jgi.2021.46.12

The role of video gaming motives in the relationship between personality risk traits and Internet Gaming Disorder

2021· article· en· W3121407317 on OpenAlexvenueno aff
Roberta Biolcati, Stefano Passini, Virginia Pupi

Bibliographic record

VenueJournal of Gambling Issues · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyHumanitiesAddictionSocial psychologyPsychiatryArt

Abstract

fetched live from OpenAlex

The main aim of this study is to improve our knowledge on Internet Gaming Disorder (IGD), contributing to a common discourse concerning its risk profiles. Specifically, the study aims to assess the prevalence of addicted gamers among Italian online and offline gamers, accounting for gender and to investigate the mediation role of gaming motives on the relationship between personality risk traits and IGD. A total of 627 videogame players (55% women; mean age 27 years) recruited from social networking sites took part in the study and filled a questionnaire including gaming characteristics, the Internet Gaming Disorder Scale (IGDS9-SF), the Substance Use Risk Profile Scale (SURPS) and the Motives for Online Gaming Questionnaire (MOGQ). The prevalence rate of Internet gaming disorder was 5.3%. Hopelessness was the personality dimension that most differentiates gaming addicts from non-addicts. Results of the mediation model suggested that Hopelessness was both directly and indirectly (via escape, fantasy and recreational motives) associated with IGD. The motivations Escape and Fantasy also mediate between Anxiety sensitivity and IGD while Competition mediate between Sensation seeking trait and IGD. The evidence suggests that IGD is motivated by psychological mechanisms similar to those compelling substance abuse, but with its own unique features.RésuméCette étude a pour but d’améliorer notre connaissance de la dépendance au jeu sur Internet (DJI) afin d’enrichir le discours sur ses profils de risque. Elle vise plus précisément à évaluer la prévalence des joueurs dépendants parmi les joueurs italiens en ligne et hors ligne, en tenant compte du genre et en examinant le rôle de médiation des raisons qui motivent la pratique des jeux dans la relation entre les traits de personnalité présentant des risques et la DJI. En tout, 627 joueurs de jeux vidéo (55 % de femmes d’une moyenne d’âge de 27 ans) recrutés sur des sites de réseaux sociaux ont participé à l’étude et rempli un questionnaire comprenant des caractéristiques liées au jeu, l’échelle de la dépendance au jeu sur Internet (IGDS9-SF), l’échelle de profil de risque de consommation de substances psychoactives (SURPS) et le questionnaire sur les raisons de jouer en ligne (MOGQ). Le taux de prévalence de la dépendance au jeu sur Internet s’établissait à 5,3 %. Le désespoir constituait l’aspect de la personnalité qui distinguait le plus les personnes dépendantes au jeu des personnes non dépendantes. Les résultats du modèle de médiation donnaient à penser que le désespoir était associé directement et indirectement (raisons liées à la fuite, à l’imaginaire et aux loisirs) à la DJI. Les raisons Fuite et Imaginaire assurent la médiation entre la sensibilité à l’anxiété et la DJI, tandis que la concurrence assure la médiation entre la recherche de sensations et la DJI. Tout indique que la DJI est motivée par des mécanismes psychologiques similaires à ceux qui incitent à la toxicomanie, mais possède ses propres caractéristiques.

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)0.007
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 score0.043
Threshold uncertainty score0.802

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.091
GPT teacher head0.388
Teacher spread0.297 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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