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Record W2604200846 · doi:10.1186/s40405-017-0022-7

Gambling behavior among Macau college and university students

2017· article· en· W2604200846 on OpenAlexaboutno aff
Sut Mei Kam, Irene Wong, Ernest Moon Tong So, David Kin Cheong Un, Chris Hon Wa Chan

Bibliographic record

VenueAsian Journal of Gambling Issues and Public Health · 2017
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySensation seekingLotteryAffect (linguistics)EntertainmentSocial psychologyAdvertisingClinical psychologyArtPersonalityStatistics

Abstract

fetched live from OpenAlex

This survey investigated gambling behavior among Chinese students studying in Macau colleges and universities. It also aimed to examine the relationship between problem gambling, affect states and sensation seeking propensity. A convenience sample of 999 students (370 men, 629 women) filled a self-administered questionnaire consisted of the Problem Gambling Severity Index (PGSI) (Ferris and Wynne in The Canadian problem gambling index: User manual. Canadian Centre on Substance Abuse, Toronto 2001a), the 8-item Brief Sensation Seeking Scale (BSSS-8) (Hoyle et al. Pers Individ Diff 32(3): 401–414, 2002), Bradburn’s Affect Balance Scale (BABS) (Bradburn in The structure of psychological well-being. Aldine, Chicago 1969) and questions on gambling activities. The response rate is 65%. Results indicate 32.3% (n = 323) of the survey participants wagered on mahjong (61.8%), soccer matches (40.2%), Mark Six lottery (37.2%), card games (28.1%), land-based casino gambling (13.1%), slot machines (7.5%) and online casino games (2.0%). The average monthly stake was MOP $411. Seeking entertainment (18.7%), killing time (12.5%) and peer influence (11.1%) were the three main reasons for gambling. Using the PGSI, 3.6 and 5.3% of the students could be identified as moderate-risk and problem gamblers respectively. Men were significantly more vulnerable to gambling problems (X2(1) = 35.00, p < 0.01) than women. Most of the problematic gamblers (76%) made their first bet before 14 years. The PGSI scores are significantly correlated with the BSSS-8 scores (r = 0.23, p < 0.01) but not with the overall ABS scores (r = −0.06, p > 0.05). The study findings inform campus prevention programs and future research.

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 score0.038
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.209
GPT teacher head0.460
Teacher spread0.251 · 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

Citations16
Published2017
Admission routes1
Has abstractyes

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