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Record W3181789871 · doi:10.1007/s10899-021-10053-y

Measuring Gambling Outcome Expectancies in Adolescents: Testing the Psychometric Properties of a Modified Version of the Gambling Expectancy Questionnaire

2021· article· en· W3181789871 on OpenAlexaff
Maria Anna Donati, Jeffrey L. Derevensky, Beatrice Cipollini, Laura Di Leonardo, Giuseppe Iraci Sareri, Caterina Primi

Bibliographic record

VenueJournal of Gambling Studies · 2021
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsMcGill University
FundersRegione ToscanaUniversità degli Studi di Firenze
KeywordsPsychologyConfirmatory factor analysisExpectancy theoryLikert scaleScale (ratio)Clinical psychologyPsychometricsReliability (semiconductor)Developmental psychologyStructural equation modelingSocial psychologyStatistics

Abstract

fetched live from OpenAlex

The Gambling Expectancy Questionnaire (GEQ; Gillespie et al. 2007a) is a 23-item scale assessing three positive outcome expectancies (Enjoyment/Arousal, Money, Self-Enhancement) and two negative outcome expectancies (Over-Involvement, Emotional Impact) related to gambling. It is the most used instrument to assess gambling outcome expectancies in adolescents and it has good psychometric properties. To allow a greater and more useful application of the scale, the present study aimed to modify the GEQ to make it usable with all adolescents, regardless of their gambling behaviour and to verify its psychometric properties. To that aim, the items were modified and the response scale was reduced from a seven-point to a five-point Likert scale. To verify the adequacy of the modified scale, two studies were conducted among Italian adolescents. In the first study (n = 501, 75% males, Mage = 16.74, SD = .88), after having removed four items and relocating another through explorative factor analysis, the original five-factor structure of the scale was confirmed by applying a confirmatory factor analysis. Reliability and validity evidence were also provided. The second study (n = 1894, 61% males, Mage = 15.68, SD = .71) attested its invariance across gambling behaviour status and gender. The modified version of the GEQ (GEQ - MOD) can be profitably used for research and preventive purposes with youth.

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)0.004
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 score0.054
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.351
GPT teacher head0.410
Teacher spread0.059 · 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
Published2021
Admission routes1
Has abstractyes

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