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Record W2784564520 · doi:10.4309/jgi.2018.38.10

Crossover Effects of Protective Behavioural Strategies for Drinking on Gambling Consequences Among College Gamblers With Alcohol or Drug Abuse

2018· article· en· W2784564520 on OpenAlexvenueno aff
Hollie F. Granato, Jeremy W. Luk, Andrew P. Paves, Irene M. Geisner, Jessica M. Cronce, Jason R. Kilmer, Ty W. Lostutter, Mary E. Larimer

Bibliographic record

VenueJournal of Gambling Issues · 2018
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
FundersNational Institute on Drug AbuseNational Institute on Alcohol Abuse and Alcoholism
KeywordsPsychologyHarmClinical psychologyLimitingPsychiatryHarm reductionEnvironmental healthMedicineSocial psychologyPublic health

Abstract

fetched live from OpenAlex

Protective behavioural strategies (PBS) for drinking are behaviours that individuals engage in to reduce the amount they drink and drinking-related consequences. To date, little is known about associations that PBS might have with other risky behaviours that frequently coincide with drinking, such as gambling. The goal of this study was to examine the associations between three subscales of the Protective Behavioral Strategies Scale (PBSS) and gambling consequences in a college sample of gamblers who also met criteria for alcohol or drug abuse. We hypothesized that engaging in more drinking PBS would be associated with lower levels of gambling consequences. A sample of 316 students (55% female) completed an online survey and met criteria for problematic gambling behaviour (3 or more on the South Oaks Gambling Screen and 1 or more consequences on the Gambling Problem Index). Those endorsing a higher score on the Serious Harm Reduction subscale (but not the Stopping or Limiting Drinking or Manner of Drinking subscales) showed a lower level of lifetime gambling consequences, suggesting a crossover effect. Strategies to reduce serious harm represent a treatment target that could potentially reduce negative consequences associated with both drinking and gambling.Résumé Les personnes aux prises avec des problèmes d’abus d’alcool adoptent des stratégies comportementales de protection pour réduire leur consommation et ses conséquences. À ce jour, on sait peu de choses sur les possibles associations entre ces comportements et d’autres comportements à risque qui coïncident souvent avec l’abus d’alcool, comme le jeu. L’objectif de cette étude était d’examiner les associations entre trois sous-échelles de stratégies comportementales et les conséquences du jeu à l’aide d’un échantillon de joueurs universitaires qui répondaient également aux critères de consommation abusive d’alcool/de drogue. On a émis l’hypothèse que le fait d’adopter des stratégies comportementales à l’égard de la consommation d’alcool diminuerait l’importance des conséquences relatives au jeu. Un échantillon de 316 étudiants sondés en ligne (55 % de femmes) a répondu aux critères de comportement de jeu problématique (3 critères ou plus sur le South Oaks Gambling Screen [SOGC] et une ou plusieurs conséquences sur l’Indice de jeu excessif [PGSI]). Les personnes qui entrent dans des sous-échelles de réduction importante des méfaits (mais pas les sous-échelles d’arrêt ou de limitation de consommation ou de mode de consommation) ont montré, au fil du temps, une diminution des effets du jeu, ce qui laisse croire à un certain effet de croisement. On aborde dans cet article la portée de cette analyse sur la prévention et l’intervention.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.195
GPT teacher head0.435
Teacher spread0.240 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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