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Record W1973980080 · doi:10.1037/a0019946

The association between childhood maltreatment and gambling problems in a community sample of adult men and women.

2010· article· en· W1973980080 on OpenAlexaff
David C. Hodgins, Don Schopflocher, Nady el‐Guebaly, David M. Casey, Garry J. Smith, Robert J. Williams, Robert Wood

Bibliographic record

VenuePsychology of Addictive Behaviors · 2010
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyPsychiatryClinical psychologyDistressSubstance abuseInjury preventionPoison controlAssociation (psychology)Suicide preventionMedicinePsychotherapistMedical emergency

Abstract

fetched live from OpenAlex

The association between childhood maltreatment and gambling problems was examined in a community sample of men and women (N = 1,372). As hypothesized, individuals with gambling problems reported greater childhood maltreatment than individuals without gambling problems. Childhood maltreatment predicted severity of gambling problems and frequency of gambling even when other individual and social factors were controlled including symptoms of alcohol and other drug use disorders, family environment, psychological distress, and symptoms of antisocial disorder. In contrast to findings in treatment-seeking samples, women with gambling problems did not report greater maltreatment than men with gambling problems. These results underscore the need for both increased prevention of childhood maltreatment and increased sensitivity towards trauma issues in gambling treatment programs for men and women.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.039
GPT teacher head0.367
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), 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

Citations113
Published2010
Admission routes1
Has abstractyes

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