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Record W1999956565 · doi:10.4236/ojmp.2014.34032

Gambling and Impulsivity: An Exploratory Study in a French Adolescent Population

2014· article· en· W1999956565 on OpenAlexaboutno aff
Lucía Romo, Gayatri Kotbagi, Sophie Platey, Adélaïde Coëffec, Francesco Boz, Laurence Kern

Bibliographic record

VenueOpen Journal of Medical Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsImpulsivitySensation seekingPsychologyPopulationPathologicalClinical psychologyNoticeExploratory researchDevelopmental psychologySocial psychologyDemographyMedicine

Abstract

fetched live from OpenAlex

Pathological gambling can be a serious problem, more so to a vulnerable population such as adolescents and youth. This study aims to investigate the links between gambling behaviours and impulsivity through a multidimensional approach in a French adolescent population. A secondary aim of this study is to find out the prevalence of pathological gambling behaviour amongst adolescents who are not meant to have legal access to such games. We administered the UPPS Impulsive behaviour Scale (UPPS-P) and the Canadian Pathological Gambling Index CPGI to 1800 adolescents aged between 11 to 17 years. Our results indicate that 33% of subjects have gambled at least once during the last year and that girls gamble as much as boys (17% and 16% respectively). Scratch games are the most common games played by adolescents (81.4%). We also notice that 1.6% of our population has problematic gambling behaviour. Although we found that many dimensions of impulsivity (Urgency, Positive urgency and Sensation seeking) are correlated to gambling behaviour, only sensation seeking seems to be a good predictor of pathological gambling severity. These results can be taken into account in the development of prevention programs.

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)0.000
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 score0.175
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.205
GPT teacher head0.514
Teacher spread0.309 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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