MétaCan
Menu
Back to cohort
Record W2466594047 · doi:10.1037/adb0000102

Trajectories of gambling problems from mid-adolescence to age 30 in a general population cohort.

2015· article· en· W2466594047 on OpenAlexaff
René Carbonneau, Frank Vitaro, Mara Brendgen, Richard E. Tremblay

Bibliographic record

VenuePsychology of Addictive Behaviors · 2015
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversité de MontréalResearch Unit on Children's Psychosocial MaladjustmentUniversité du Québec à MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsPsychologyPopulationCohortAddictionYoung adultDemographyDevelopmental psychologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Studies of gambling starting before adulthood in the general population are either cross-sectional, based on the stability of these behaviors between 2 time points, or cover a short developmental period. The present study aimed at investigating the developmental trajectories of gambling problems across 3 key periods of development, mid-adolescence, early adulthood, and age 30, in a mixed-gender cohort from the general population. Using a semiparametric mixture model, trajectories were computed based on self-reports collected at ages 15 (N = 1,882), 22 (N = 1,785), and 30 (N = 1,358). Two distinct trajectories were identified: 1 trajectory including males and females who were unlikely to have experienced gambling problems across the 15-year period, and 1 trajectory including participants likely to have experienced at least 1 problem over the last 12 months at each time of assessment. Participants following a high trajectory were predominantly male, participated frequently in 3 to 4 different gambling activities, and were more likely to report substance use and problems related to their alcohol and drug consumption at age 30. Thus, gambling problems in the general population are already observable at age 15 in a small group of individuals, who maintain some level of these problems through early adulthood, before moderately but significantly desisting by age 30, while also experiencing other addictive behaviors and related problems.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.135
GPT teacher head0.423
Teacher spread0.288 · 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

Citations36
Published2015
Admission routes1
Has abstractyes

Explore more

Same venuePsychology of Addictive BehaviorsSame topicGambling Behavior and TreatmentsFrench-language works237,207