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Record W2990733058 · doi:10.1037/adb0000531

Patterns of gambling and substance use initiation in African American and White adolescents and young adults.

2019· article· en· W2990733058 on OpenAlexaff
Kimberly B. Werner, Renee M. Cunningham‐Williams, Manik Ahuja, Kathleen K. Bucholz

Bibliographic record

VenuePsychology of Addictive Behaviors · 2019
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsInstitute of Health Services and Policy Research
FundersNational Institute on Drug AbuseNational Institute on Alcohol Abuse and AlcoholismNational Institutes of Health
KeywordsPsychologyCannabisAlcohol use disorderSubstance abuseSubstance useYoung adultPsychiatryAlcoholCohortVulnerability (computing)Cannabis DependenceClinical psychologyDevelopmental psychologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

= 317) enriched for risk for alcohol use disorder and includes those who were assessed for gambling behaviors and problems: AA (360 males, 390 females) and White (287 males, 312 females). Findings indicated racial differences in the overall prevalence of gambling behaviors and substance use as well as patterns of initiation-particularly within gambling/alcohol and gambling/tobacco for males. Survival models revealed some similarities as well as differences across race and gender groups in associations of gambling with initiation of substances, as well as substances with initiation of gambling. Alcohol use (AA males only) and cannabis use (AA males and White females) elevated the hazards of initiating gambling. In contrast, gambling significantly elevated the hazards of initiation alcohol across 3 of 4 groups and of cannabis use in AA males only. The results highlight some overlapping as well as distinct risk factors for both gambling and substance use initiation in this cohort enriched for vulnerability to alcohol use disorder (AUD). These findings have implications for integrating gambling prevention into existing substance use prevention and intervention efforts-particularly but not exclusively for young AA males. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.870

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.051
GPT teacher head0.362
Teacher spread0.310 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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