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Record W4405725635 · doi:10.1080/0144929x.2024.2440779

Emotion regulation, need satisfaction, passion and problematic video game play during difficult times

2024· article· en· W4405725635 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBehaviour and Information Technology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPassionVideo gamePsychologyAffect (linguistics)Context (archaeology)Social psychologyCognitive psychologyMultimediaComputer scienceCommunication

Abstract

fetched live from OpenAlex

There is growing recognition of the role video games can play in helping people through challenging times, however many still argue that video game play can lead to adverse and problematic behaviours when relied upon to manage negative affect. This study sought to explore a number of factors that may play a role in influencing the likelihood one develops problematic habits of play, particularly in the context of difficult and stressful times. Specifically, this study utilised Self-Determination Theory and the Dualistic Model of Passion to explore the relationships between emotion regulation, psychological need satisfaction and frustration, passion for video games, and problematic video game play during times of difficulty and stress. A path analysis was conducted using data from 440 participants and found that, overall, emotion regulation may be associated with whether or not problematic play is likely to occur, particularly through its relationship with need satisfaction (and frustration) and video game passion.

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.

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)0.000
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 score0.562
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.005
GPT teacher head0.251
Teacher spread0.245 · 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