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Record W2971428706 · doi:10.4309/jgi.2019.42.8

That’s what you get for waking up in Vegas: Fatigue and alcohol consumption are associated with the duration of gambling sessions

2019· article· en· W2971428706 on OpenAlexvenueno aff
Hannah Thorne, Matthew Browne, Matthew Rockloff, Sally A. Ferguson

Bibliographic record

VenueJournal of Gambling Issues · 2019
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyAlcohol consumptionLas vegasAlcoholHarm reductionConsumption (sociology)Sleep (system call)HarmExcessive alcohol consumptionAlcohol intoxicationPsychiatryClinical psychologySocial psychologyMedicineInjury preventionEnvironmental healthPoison controlPublic health

Abstract

fetched live from OpenAlex

Fatigue and intoxication can impair people’s thinking, including their decision-making and assessments of risk. However, little research has specifically examined whether links exist between episodes of gambling, sleep restriction and alcohol consumption. Gambling often occurs in environments where alcohol is served and opening hours are long, making potential interactions between intoxication, fatigue and gambling relevant for exploration from a harm reduction standpoint. The current study tracked the gambling, alcohol consumption and sleep patterns of an online sample of regular gamblers and drinkers (N = 132, 28% female) for six days using online diaries. Results confirm that the three behaviours are related at the individual level; with significant between-subjects correlations between gambling and sleep (r = –.20), gambling and alcohol consumption (r = .22), and sleep and alcohol consumption (r = –.19). However, no strong or reliable within-subjects (day by day) relationships were found. That is, although more intense gamblers slept less and drank more, they were no more likely to drink relatively more or sleep relatively less, on the same days which they gambled. We also observed a negative auto-correlation effect for each behaviour: engaging in more of one behaviour on one day is associated with a reduction of the same behaviour the following day. This result suggests that individual-level traits, rather than contextual or environmental effects, are responsible for observed co-morbidities between these health-related behaviours. Further, that gambling consumption, like alcohol and sleep, is subject to satiation and refractory effects.RésuméLa fatigue et l’intoxication peuvent nuire à la faculté de penser, notamment à la prise de décisions et à l’évaluation des risques. Cependant, peu de recherches ont particulièrement tenté de découvrir s’il existait des liens entre des épisodes de jeu, une privation de sommeil et une consommation d’alcool. Le jeu se produit souvent dans des lieux où l’on sert de l’alcool et les heures d’ouverture sont longues; ces endroits sont donc propices à l’exploration des interactions potentielles entre l’intoxication, la fatigue et le jeu, du point de vue de la réduction des méfaits. La présente étude a suivi les tendances de jeu, de consommation d’alcool et de manque de sommeil d’un échantillon en ligne de joueurs et de buveurs réguliers (N = 132, 28% de femmes) pendant six jours à l’aide de journaux en ligne. Les résultats confirment que les trois comportements sont liés sur le plan individuel, avec des corrélations significatives entre les sujets, notamment entre le jeu et le sommeil (r = –.20), le jeu et la consommation d’alcool (r = 0,22) et le sommeil et la consommation d’alcool (r = –0,19). Cependant, aucune relation intrasujet forte ou fiable (jour après jour) n’a été constatée. Autrement dit, même si les joueurs plus actifs dormaient moins et buvaient plus, ils n’étaient pas plus susceptibles de boire relativement plus ou de dormir moins les jours où ils jouaient. Nous avons également observé un effet d’autocorrélation négatif pour chaque comportement : s’engager intensément dans un comportement le même jour est associé à une réduction du même comportement le jour suivant. Ce résultat laisse croire que les traits individuels, plutôt que les effets contextuels ou environnementaux, sont responsables des comorbidités observées entre ces comportements liés à la santé. De plus, les comportements liés au jeu, comme la consommation d’alcool et le manque de sommeil, sont sujets à des effets de saturation et à des effets réfractaires.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.396
GPT teacher head0.467
Teacher spread0.071 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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