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Record W2114743580 · doi:10.1037/a0021109

Predicting early gambling in children.

2011· article· en· W2114743580 on OpenAlexaff
Frank Vitaro, Brigitte Wanner

Bibliographic record

VenuePsychology of Addictive Behaviors · 2011
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversité de MontréalResearch Unit on Children's Psychosocial Maladjustment
Fundersnot available
KeywordsPsychologyImpulsivityDisinhibitionAnxietyDevelopmental psychologyPopulationClinical psychologyPsychiatryDemography

Abstract

fetched live from OpenAlex

This large population-based study (N = 1,125) examined whether low inhibition (i.e., low anxiety) predicted early gambling, above and beyond disinhibition (i.e., impulsivity) and whether the two personal dispositions operated independently or interactively. It also examined whether the predictive role of these personal dispositions towards early gambling depended on parent gambling. Children's personal dispositions were assessed at ages 6, 7, and 8 years through teacher ratings. Parent gambling participation and gambling problems were assessed when the children were 8 years old. Finally, children's early gambling was measured through self-reports when the children were 10 years old. Results showed that teacher-rated impulsivity predicted early gambling for both genders. In addition, low anxiety predicted early gambling behavior, above and beyond impulsivity and control variables, albeit only in boys. Impulsivity and anxiety did not interact with each other, nor did they interact with parent gambling in predicting early gambling. However, parent gambling participation, but not problems, additively predicted early gambling for boys and for girls. The theoretical and practical implications of these findings are discussed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.118
GPT teacher head0.400
Teacher spread0.282 · 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

Citations33
Published2011
Admission routes1
Has abstractyes

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